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1
Maestre Vidal, Jorge, and Marco Antonio Sotelo Monge. "Obfuscation of Malicious Behaviors for Thwarting Masquerade Detection Systems Based on Locality Features." Sensors 20, no. 7 (2020): 2084. http://dx.doi.org/10.3390/s20072084.
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In recent years, dynamic user verification has become one of the basic pillars for insider threat detection. From these threats, the research presented in this paper focuses on masquerader attacks, a category of insiders characterized by being intentionally conducted by persons outside the organization that somehow were able to impersonate legitimate users. Consequently, it is assumed that masqueraders are unaware of the protected environment within the targeted organization, so it is expected that they move in a more erratic manner than legitimate users along the compromised systems. This feature makes them susceptible to being discovered by dynamic user verification methods based on user profiling and anomaly-based intrusion detection. However, these approaches are susceptible to evasion through the imitation of the normal legitimate usage of the protected system (mimicry), which is being widely exploited by intruders. In order to contribute to their understanding, as well as anticipating their evolution, the conducted research focuses on the study of mimicry from the standpoint of an uncharted terrain: the masquerade detection based on analyzing locality traits. With this purpose, the problem is widely stated, and a pair of novel obfuscation methods are introduced: locality-based mimicry by action pruning and locality-based mimicry by noise generation. Their modus operandi, effectiveness, and impact are evaluated by a collection of well-known classifiers typically implemented for masquerade detection. The simplicity and effectiveness demonstrated suggest that they entail attack vectors that should be taken into consideration for the proper hardening of real organizations.
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., Sonika, Sandeep Kumar Arora, and Mahedi Masud. "Review on Security Based Vehicular Ad-Hoc Network." International Journal of Engineering & Technology 7, no. 3.8 (2018): 125. http://dx.doi.org/10.14419/ijet.v7i3.8.16846.
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VANET a vehicular ad-hoc network provides the security to vehicles. To provide security in VANET, we are using Elliptical curve cryptography. In this paper we are going to discuss various techniques of cryptography, the techniques such are Advanced Encryption Standard, Data Encryption Standard, and Triple Data Encryption Standard. These techniques are part of symmetric and asymmetric cryptography. In addition to this there are some attacks which we are discussing in this paper like, masquerade attack, replay attack, insider attack, mutual authentication attack, and parallel session attack. These attacks are on different layer. At the end we are comparing these attacks with each other and compare their quality of services.
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Hatture, Sanjeeva Kumar M., and Shweta Policepatil. "Masquerade Attack Analysis for Secured Face Biometric System." International Journal of Recent Technology and Engineering (IJRTE) 10, no. 2 (2021): 225–32. http://dx.doi.org/10.35940/ijrte.b6309.0710221.
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Biometrics systems are mostly used to establish an automated way for validating or recognising a living or nonliving person's identity based on physiological and behavioural features. Now a day’s biometric system has become trend in personal identification for security purpose in various fields like online banking, e-payment, organizations, institutions and so on. Face biometric is the second largest biometric trait used for unique identification while fingerprint is being the first. But face recognition systems are susceptible to spoof attacks made by nonreal faces mainly known as masquerade attack. The masquerade attack is performed using authorized users’ artifact biometric data that may be artifact facial masks, photo or iris photo or any latex finger. This type of attack in Liveness detection has become counter problem in the today's world. To prevent such spoofing attack, we proposed Liveness detection of face by considering the countermeasures and texture analysis of face and also a hybrid approach which combine both passive and active liveness detection is used. Our proposed approach achieves accuracy of 99.33 percentage for face anti-spoofing detection. Also we performed active face spoofing by providing several task (turn face left, turn face right, blink eye, etc) that performed by user on live camera for liveness detection.
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Shweta, Policepatil, and Kumar M. Hatture Sanjeeva. "Masquerade Attack Analysis for Secured Face Biometric System." International Journal of Recent Technology and Engineering (IJRTE) 10, no. 2 (2021): 225–32. https://doi.org/10.35940/ijrte.B6309.0710221.
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Biometrics systems are mostly used to establish an automated way for validating or recognising a living or nonliving person's identity based on physiological and behavioural features. Now a day’s biometric system has become trend in personal identification for security purpose in various fields like online banking, e-payment, organizations, institutions and so on. Face biometric is the second largest biometric trait used for unique identification while fingerprint is being the first. But face recognition systems are susceptible to spoof attacks made by nonreal faces mainly known as masquerade attack. The masquerade attack is performed using authorized users’ artifact biometric data that may be artifact facial masks, photo or iris photo or any latex finger. This type of attack in Liveness detection has become counter problem in the today's world. To prevent such spoofing attack, we proposed Liveness detection of face by considering the countermeasures and texture analysis of face and also a hybrid approach which combine both passive and active liveness detection is used. Our proposed approach achieves accuracy of 99.33 percentage for face anti-spoofing detection. Also we performed active face spoofing by providing several task (turn face left, turn face right, blink eye, etc) that performed by user on live camera for liveness detection.
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Li, Biao. "Research on Computer Network Security and Prevention Strategy." Applied Mechanics and Materials 608-609 (October 2014): 526–30. http://dx.doi.org/10.4028/www.scientific.net/amm.608-609.526.
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With the development and popularization of the computer network, the security problem has increasingly become the focus of common concern. The computer network safety problems mainly include: protocol design issues, awareness, management system and technical operation. Hackers on the computer network attack techniques: Deceptive attack, masquerade attacks, vulnerability attack, covert attack and technical attack. Accordingly, we should take the corresponding safety countermeasures: strengthen network security education, using the network protection technology, detection technology and anti-virus technology. This paper mainly analyzes the defects and the security problems of computer network, discusses about the maintenance of computer network security and the way for computer network attack technology defense strategy.
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Ayeni, Olaniyi, O. Owolafe, and O. P. Ogunjobi. "A Security System for Detecting Denial of Service (DDoS) and Masquerade Attacks on Social Networks." Journal of Information Security and Cybercrimes Research 5, no. 1 (2022): 80–86. http://dx.doi.org/10.26735/gmey8791.
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This study on a security system for detecting denial of service (DDoS) and masquerade attacks on social networks specifically describes how a Convolutional Neural Network (CNN) algorithm was employed. The dataset used for this research is the CICIDS2017 dataset, which contains benign data (no attack present) and the most up-to-date, frequent attacks which resemble true, real-world data. The feature extraction method used was recursive feature elimination (RFE), which reduced 77 columns of the dataset to 10 columns. This research was motivated by the limitation of Alguliyev and Abdullayeva 2019, which focused on the prediction of DDoS attack occurrence by getting related texts in social media. It has a limited attack class that focuses solely on DDoS attacks, and it does not perform social media network prediction in general. The objective of this research is to develop a security system for detecting DDoS and masquerade attacks and evaluate the detection model on social media networks. The system was tested on Facebook and Instagram. The result of the training accuracy that we derived from this research is 99.53%, while the testing accuracy is 99.52%. The result of this research is compared with previous studies’ results. This study recommends that the model implemented can be enhanced more effectively by comparing the accuracy of alternative deep learning algorithms to that of the CNN utilized in the current prediction model.
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Babkin, Sergey, and Anna Epishkina. "One-Time Passwords: Resistance to Masquerade Attack." Procedia Computer Science 145 (2018): 199–203. http://dx.doi.org/10.1016/j.procs.2018.11.040.
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Tapiador, Juan E., and John A. Clark. "Masquerade mimicry attack detection: A randomised approach." Computers & Security 30, no. 5 (2011): 297–310. http://dx.doi.org/10.1016/j.cose.2011.05.004.
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Almanza-Ortega, Nelva Nely, Joaquin Perez-Ortega, Monterrubio Sergio Mauricio Martínez, and Juan A. Recio-Garcia. "Clustering-Based Cyber Situational Awareness: A Practical Approach for Masquerade Attack Detection." Journal of Artificial Intelligence and Computing Applications 2, no. 1 (2024): 35–39. https://doi.org/10.5281/zenodo.14933955.
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Cyber Situational Awareness (CSA) is crucial for detecting and mitigating security threats in evolving digital environments. Traditional intrusion detection systems face challenges related to computational efficiency, scalability, and interpretability, particularly in the detection of masquerade attacks, where attackers mimic legitimate user behavior. This exploratory study conducts a preliminary investigation into a clustering-based approach that integrates OK-Means, an optimized variant of K-Means, with k-Nearest Neighbors (k-NN) to improve intrusion detection. The proposed approach is evaluated using the Windows-Users and Intruder Simulations Logs (WUIL) dataset to assess its feasibility and preliminary performance. Experimental results suggest that this method can achieve up to 99\% recall in masquerade attack detection while reducing execution time by 85\% compared to conventional k-NN classifiers. Additionally, the integration of explainability mechanisms, such as clustering visualization and attack introspection tools, provides security analysts with interpretable insights into system decisions. As an initial exploration, this study provides early-stage insights into clustering-based CSA methods and lays the groundwork for future research. The findings suggest that this approach can be further developed and extended to other cybersecurity domains, such as phishing and malware detection, contributing to AI-driven security frameworks.Cyber Situational Awareness (CSA) is crucial for detecting and mitigating security threats in evolving digital environments. Traditional intrusion detection systems face challenges related to computational efficiency, scalability, and interpretability, particularly in the detection of masquerade attacks, where attackers mimic legitimate user behavior. This exploratory study conducts a preliminary investigation into a clustering-based approach that integrates OK-Means, an optimized variant of K-Means, with k-Nearest Neighbors (k-NN) to improve intrusion detection. The proposed approach is evaluated using the Windows-Users and Intruder Simulations Logs (WUIL) dataset to assess its feasibility and preliminary performance. Experimental results suggest that this method can achieve up to 99\% recall in masquerade attack detection while reducing execution time by 85\% compared to conventional k-NN classifiers. Additionally, the integration of explainability mechanisms, such as clustering visualization and attack introspection tools, provides security analysts with interpretable insights into system decisions. As an initial exploration, this study provides early-stage insights into clustering-based CSA methods and lays the groundwork for future research. The findings suggest that this approach can be further developed and extended to other cybersecurity domains, such as phishing and malware detection, contributing to AI-driven security frameworks.
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Wei, Guo-heng, Yan-lin Qin, and Wei Fu. "An Improved Security Authentication Protocol for Lightweight RFID Based on ECC." Journal of Sensors 2022 (February 8, 2022): 1–6. http://dx.doi.org/10.1155/2022/7516010.
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The security, privacy, and operation efficiency of radio frequency identification (RFID) must be fully measured in practical use. A few RFID authentication schemes based on elliptic curve cryptography (ECC) have been proposed, but most of them cannot resist the existing attacks. The scheme presented by Qian et al. could not resist impersonation attack according to our security analysis. Then, we propose a novel lightweight RFID authentication scheme, which is proved that it can resist server spoofing attack, tag masquerade attack, and provide other security properties of a RFID authentication scheme. Comparisons of computation and communication cost demonstrate that the proposed scheme is more suitable for the resource-constrained RFID authentication.
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Chang, Wenson. "On the Performance of the DNPS-Based Relay Networks under Masquerading Attack." Wireless Communications and Mobile Computing 2018 (July 17, 2018): 1–13. http://dx.doi.org/10.1155/2018/4602146.
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In the relay networks, two typical issues of physical layer security are selfishness and garbling. As a matter of fact, a certain nontypical but severely harmful misbehavior can also remove the cooperative diversity gain. Here, we coin the masquerading attack to indicate this kind of misbehavior. A masquerade relay can always pretend to be the best one to forward signals and, in consequence, deprive the others of the opportunities to cooperate. To the best of our knowledge, the impact of the masquerading attack has not yet been fully investigated. In this paper, multiple masquerade relays with random masquerading behavior are taken into account. Also, the complete channel effects, including the effects of the flat Rayleigh fading, log-normal shadowing, and path loss, are considered such that the geographical effects of the network topology can be completely captured. At last, the impact of the masquerade relays are evaluated in terms of the outage probability and end-to-end capacity.
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Sivanandhan, Anusha, Bibitha Baby, and Dhanya G S. "Masquerade Attack Identification Via DDSGA-Based Anomaly Detection." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem44275.
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To take advantage of the user services and privileges, a masquerade attacker poses as a legitimate user. The semi- global alignment algorithm (SGA) is one of the most effective and efficient techniques to detect these attacks but it has not yet reached the accuracy and performance required by large scale, multiuser systems. To improve both the effectiveness and the performances of this algorithm, the Data-Driven Semi - Global Alignment, DDSGA approach was proposed. By implementing unique alignment settings for every user, DDSGA enhances the scoring systems from the perspective of security effectiveness. Additionally, by permitting minor adjustments to the low-level representation of the instructions' functionality, it can withstand minor variations in user command sequences. It also adapts to changes in the user behavior by updating the signature of a user according to its current behavior. To optimize the runtime overhead, DDSGA minimizes the alignment overhead and parallelism the detection and the update. Key Words: legal user, DDSGA approach, user services, SGA, DDSGA algorithm
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Hao, Zhuo, Sheng Zhong, and Nenghai Yu. "A Time-Bound Ticket-Based Mutual Authentication Scheme for Cloud Computing." International Journal of Computers Communications & Control 6, no. 2 (2011): 227. http://dx.doi.org/10.15837/ijccc.2011.2.2170.
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<p>Cloud computing is becoming popular quickly. In cloud computing, people store their important data in the cloud, which makes it important to ensure the data integrity and availability. Remote data integrity checking enables the client to perform data integrity verification without access to the complete file. This service brings convenience to clients, but degrades the server’s performance severely. Proper schemes must be designed to reduce the performance degradation.<br /> In this paper, a time-bound ticket-based mutual authentication scheme is proposed for solving this problem. The proposed authentication scheme achieves mutual authentication between the server and the client. The use of timebound tickets reduces the server’s processing overhead efficiently. The correspondence relationship between the digital ticket and the client’s smart card prevents user masquerade attack effectively. By security analysis, we show that the proposed scheme is resistant to masquerade attack, replay attack and password guessing attack. By performance analysis, we show that the proposed scheme has good efficiency. The proposed scheme is very suitable for cloud computing.</p>
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MIZANUR RAHMAN, SK MD, and KHALIL EL-KHATIB. "SECURE ANONYMOUS COMMUNICATION FOR WIRELESS SENSOR NETWORKS BASED ON PAIRING OVER ELLIPTIC CURVES." Journal of Interconnection Networks 10, no. 04 (2009): 459–79. http://dx.doi.org/10.1142/s0219265909002662.
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The nature of wireless communication makes it susceptible to a number of security threats, disclosing the identities of the communicating parties in the network. By revealing the identity of nodes in the network, outside parties can setup severe targeted attacks on specific nodes. Such targeted attacks are more harmful to sensor networks as sensing nodes (sensors) have limited computing and communication power prohibiting them from using robust security mechanisms. Anonymous communication is one of the key primitives for ensuring the privacy of communicating parties in a group or network. In this paper, we propose a novel secure anonymous communication protocol based on pairing over elliptic curves for wireless sensor networks (WSNs). Using this protocol, only the legitimate nodes in the sensor network can authenticate each other without disclosing their real identities. The proposed protocol is extremely efficient in terms of key storage space and communication overhead. Security analysis of our protocol shows that it provides complete anonymity for communicating nodes. The analysis also shows that the proposed protocol is robust against a number of attacks including the masquerade attack, wormhole attack, selective forwarding attack and message manipulation attack.
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Menon, MeenaGopinath, Priyanka Sudhakar, and Nidhi Dubey. "Idiopathic posterior scleritis: A masquerade of acute angle-closure attack." TNOA Journal of Ophthalmic Science and Research 60, no. 1 (2022): 52. http://dx.doi.org/10.4103/tjosr.tjosr_60_21.
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Elmasry, Wisam, Akhan Akbulut, and Abdul Halim Zaim. "Comparative evaluation of different classification techniques for masquerade attack detection." International Journal of Information and Computer Security 13, no. 2 (2020): 187. http://dx.doi.org/10.1504/ijics.2020.108848.
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Zaim, Abdul Halim, Akhan Akbulut, and Wisam Elmasry. "Comparative Evaluation of Different Classification Techniques for Masquerade Attack Detection." International Journal of Information and Computer Security 11, no. 4/5 (2019): 1. http://dx.doi.org/10.1504/ijics.2019.10020664.
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Jo, Hyo Jin, Jin Hyun Kim, Hyon-Young Choi, Wonsuk Choi, Dong Hoon Lee, and Insup Lee. "MAuth-CAN: Masquerade-Attack-Proof Authentication for In-Vehicle Networks." IEEE Transactions on Vehicular Technology 69, no. 2 (2020): 2204–18. http://dx.doi.org/10.1109/tvt.2019.2961765.
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Almanza-Ortega, Nelva Nely, Joaquin Perez-Ortega, Monterrubio Sergio Mauricio Martínez, and Juan A. Recio-Garcia. "An Explainable Clustering-Based Approach for Cyber Situational Awareness on Masquerade Attacks Detection." Journal of Artificial Intelligence and Computing Applications 2, no. 2 (2024): 48–59. https://doi.org/10.5281/zenodo.15098302.
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Masquerade attacks pose a significant challenge in cybersecurity, as intruders mimic legitimate user behavior to evade detection. In dynamic, data-intensive environments, traditional intrusion detection systems often struggle to provide both timely and interpretable results, limiting their usefulness for effective Cyber Situational Awareness (CSA). This article presents a clustering-based approach for detecting masquerade attacks using OK-Means—a variant of K-Means optimized for faster convergence—combined with a nearest neighbor classifier and noise reduction techniques. The proposed Intrusion Detection System (IDS) reduces computational overhead while enhancing explainability, leading to more reliable and transparent Cyber Threat Intelligence (CTI) decisions.
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Carryl, Clyde, Bassem Alhalabi, Taghi M. Khoshgoftaar, and Lofton Bullard. "Verifying the Security Characteristics of a Secure Physical Access Control Protocol." International Journal of Reliability, Quality and Safety Engineering 23, no. 02 (2016): 1650006. http://dx.doi.org/10.1142/s0218539316500066.
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Physical access control protocols provide a structured method of controlling the behavior of physical devices which in many cases are not only remotely located with respect to the accessing entity, but require the exchange of messages over one or more untrusted networks, such as the internet. Therefore, if it is necessary to prevent unauthorized access to the controlled physical devices, it is essential that the physical access control protocol exhibit certain verifiable security properties. We studied the Universal Physical Access Control System (UPACS) and used the formal protocol verification tool Proverif to verify that it possesses several key security properties. We also conducted a security analysis of the protocol and verified that it was resilient or otherwise invulnerable to several known forms of security attack, including Attacks on User Privacy and Anonymity, Session Key Security Attacks, Password Guessing Attacks, De-Synchronization Attacks, Replay Attacks, Eavesdropping Attacks, Denial-of-Service Attacks, User and Server Masquerade Attacks, Stolen Verifier Attacks and Stolen Password Attacks.
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Shaik, Hedayath Basha, Arun C, Ganesh Sekar Jai, Nimitha N, and Kiran Tatineni Sai. "An Intelligent Secure Image Transmission System Using Elliptic Curve Cryptography." International Journal of Microsystems and IoT 1, no. 3 (2023): 156–62. https://doi.org/10.5281/zenodo.8359476.
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In the fast-changing and developing world, it is very much essential to have a fast, secure intelligent communication system for data transmission. In the proposed work the author designed a traditional intelligent secured software-based digital image transmission system with elliptic curve cryptography and Diffie-Hellman key exchange protocol with smaller key size. Secret key is shared intelligently using the Diffie-Hellman key exchange protocol between the two end-users. The encryption process of the digital image is done on every pixel value of an image using an intelligent mapping table and hence it is very secure against an intruder. The decryption process is done pixel-wise using the same intelligent mapping table and secured shared keys by the authentic sender, the average process of image encryption and decryption takes 45.3210 seconds. The vulnerability of the intelligent communication system is verified using various active and passive attacks. Proposed work is robust to passive attacks like eavesdropping attack, network analysis, and traffic analysis also to the repudiation active attack. It is semi-fragile to active attacks like modification of messages, denial of service, and masquerade.
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Feng, Yi C., Meng-Hui Lim, and Pong C. Yuen. "Masquerade attack on transform-based binary-template protection based on perceptron learning." Pattern Recognition 47, no. 9 (2014): 3019–33. http://dx.doi.org/10.1016/j.patcog.2014.03.003.
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Choi, Younsung, Junghyun Nam, Donghoon Lee, Jiye Kim, Jaewook Jung, and Dongho Won. "Security Enhanced Anonymous Multiserver Authenticated Key Agreement Scheme Using Smart Cards and Biometrics." Scientific World Journal 2014 (2014): 1–15. http://dx.doi.org/10.1155/2014/281305.
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An anonymous user authentication scheme allows a user, who wants to access a remote application server, to achieve mutual authentication and session key establishment with the server in an anonymous manner. To enhance the security of such authentication schemes, recent researches combined user’s biometrics with a password. However, these authentication schemes are designed for single server environment. So when a user wants to access different application servers, the user has to register many times. To solve this problem, Chuang and Chen proposed an anonymous multiserver authenticated key agreement scheme using smart cards together with passwords and biometrics. Chuang and Chen claimed that their scheme not only supports multiple servers but also achieves various security requirements. However, we show that this scheme is vulnerable to a masquerade attack, a smart card attack, a user impersonation attack, and a DoS attack and does not achieve perfect forward secrecy. We also propose a security enhanced anonymous multiserver authenticated key agreement scheme which addresses all the weaknesses identified in Chuang and Chen’s scheme.
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Zhang, Jiayuan, Rongxin Guo, Yifan Shi, and Wanting Tang. "An anti-impersonation attack electronic health record sharing scheme based on proxy re-encryption and blockchain." Mathematical Biosciences and Engineering 21, no. 6 (2024): 6167–89. http://dx.doi.org/10.3934/mbe.2024271.
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<abstract><p>Many current electronic medical record (EMR) sharing schemes that use proxy re-encryption and blockchain do not fully consider the potential threat of malicious node impersonation attacks. This oversight could lead to data leakage as attackers masquerade as legitimate users or proxy nodes during the sharing process. To deal with this problem, we propose an EMR sharing scheme based on proxy re-encryption and blockchain to protect against impersonation attacks. First, we prevent the potential threat of impersonation attacks by generating a shared temporary key and assigning tasks to multiple proxy nodes. Second, we use a random function to ensure that the selection of encrypted proxy nodes is fair. Third, we use a combination of blockchain and the InterPlanetary File System to solve the problem of insufficient storage capacity of shared processes and ensure the storage security of EMRs. Through the security proof, our scheme guarantees anti-impersonation, anti-collusion, and anti-chosen plaintext attack capability in the sharing process of EMRs. Additionally, experiments on the blockchain platform, namely Chain33, show that our scheme significantly increases efficiency.</p></abstract>
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Dušek, Otakar, Marek Fichtl, Lucie Rezková, et al. "Acute Elevation of Intraocular Pressure in Patient with Hyperlipidemic Myeloma." Czech and Slovak Ophthalmology 76, no. 4 (2020): 172–80. http://dx.doi.org/10.31348/2020/27.
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Purpose: To introduce a rare case of patient with hyperlipidemic myeloma and ocular manifestation in the form of masquerade syndrome with acute elevation of intraocular pressure (IOP) and hyperviscous retinopathy. Results: 55-year-old man with newly diagnosed hyperlipidemic myeloma and hyperviscous syndrome was acutely referred to our glaucoma outpatient clinic due to problems with his left eye: sudden pain, blurred vision, redness of the eye and IOP of 44 mm Hg. We excluded attack of angle closure glaucoma and found the presence of whitish material in the anterior chamber and blood obstructing the iridocorneal angle. Glaucoma therapy was initiated and lavage of the anterior chamber of the left eye with sampling of the aqueous humour for biochemical and cytological examination was performed. Identification of trace amount of cryoprotein in the samples of humour proved diagnosis of masquerade syndrome. Finding of the hyperviscous retinopathy and nonperfusion of wide peripheral areas of retina in both eyes was indicated to laser coagulation of these areas. The patient underwent in the meantime three times plasmapheresis, four cycles of biological therapy and autologous stem cell transplantation reaching complete remission of the myeloma. Local and systemic therapy led to significant clinical finding improvement on the anterior segment and fundus of both eyes. Conclusions: Masquerade syndrome can be complicated by acute elevation of IOP. Diagnostic lavage of the anterior chamber, local therapy, systemic therapy and close interdisciplinary cooperation contributed to right diagnosis, IOP normalisation, ocular and general condition improvement.
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Cui, Jianming, Xiaojun Zhang, Ning Cao, Dexue Zhang, Jianrui Ding, and Guofu Li. "An improved authentication protocol–based dynamic identity for multi-server environments." International Journal of Distributed Sensor Networks 14, no. 5 (2018): 155014771877765. http://dx.doi.org/10.1177/1550147718777654.
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The age of Internet of things gives rise to more challenges to various secure demands when designing the protocols, such as object identification and tracking, and privacy control. In many of the current protocols, a malicious server may cheat users as if it was a legal server, making it vital to verify the legality of both users and servers with the help of a trusted third-party, such as a registration center. Li et al. proposed an authentication protocol based on dynamic identity for multi-server environment, which is still susceptible to password-guessing attack, eavesdropping attack, masquerade attack, and insider attack etc. Besides, their protocol does not provide the anonymity of users, which is an essential request to protect users’ privacy. In this article, we present an improved authentication protocol, depending on the registration center in multi-server environments to remedy these security flaws. Different from the previous protocols, registration center in our proposed protocol is one of parties in authentication phase to verify the legality of the users and the servers, thus can effectively avoid the server spoofing attack. Our protocol only uses nonce, exclusive-OR operation, and one-way hash function in its implementation. Formal analysis has been performed using the Burrows–Abadi–Needham logic to show its security.
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Kalaiselvi, R., and P. Meenakshi Sundaram. "Unified framework for sybil attack detection in mobile ad hoc networks using machine learning approach." Scientific Temper 16, no. 02 (2025): 3774–82. https://doi.org/10.58414/scientifictemper.2025.16.2.09.
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Independent wireless communication is possible in a "mobile ad hoc network" regardless of any predefined administrative or physical framework. The comprehensive enhancement of services for these networks depends on protecting their interactions. The Sybil attack creates numerous counterfeit identities to disrupt the system's remote functionalities. Implementing a security plan necessitates the establishment of a trust model that delineates the confidence relationships among entities. The trust structure in mobile ad hoc network security has been extensively researched. Mobile ad hoc networks are intrinsically more vulnerable to security breaches than wired networks because of their wireless characteristics. The primary factors contributing to this are energy limitations and security vulnerabilities. A comprehensive methodology has been established to improve the identification of Sybil attacks in MANETs. The system employs two advanced machine learning approaches, Ensemble Regressive Arboretum and AdaBagging, alongside network-feature extraction. Numerous trust models have been developed by integrating AdaBagging and the Ensemble Regressive Arboretum, while most known approaches rely on a singular framework. A Sybil assault transpires when a few numbers of individuals masquerade as numerous peers to obtain unauthorized access to a significant portion of the system. This research employs a machine learning methodology to identify Sybil attacks in MANETs by collecting network metrics such as traffic characteristics, communication patterns, and node activities.
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Patel, Maitri, and Rajan Patel. "Improved Identity Based Encryption System (IIBES): A Mechanism for Eliminating the Key-Escrow Problem." Emerging Science Journal 5, no. 1 (2021): 77–84. http://dx.doi.org/10.28991/esj-2021-01259.
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A revolutionary change to public-key cryptography can be considered as an Identity Based Cryptography (IBC) in which identity of the receiver is being used as a public key for encrypting a message and Key Generation Centre (KGC). IBC will generate and distribute the private key to each user to decrypt a message. The thought behind presenting the scheme was to improve and reduce the complexity of certificate and key management, but it also gives rise to key escrow problem, access to encrypted information to unauthorized users. The paper represents Improved Identity-Based Encryption Scheme (IIBES) for Domain Name System (DNS) security which provides confidentiality and authentication through modified identity based encryption and identity based digital signatures. The IIBES comprises key revocation mechanism for non-revoked users and also eliminates key escrow problem. Thus, the IIBES aids to implement the identity-based cryptography more safely in reality and protects DNS against cache poisoning, spoofing attack and masquerade attack. Doi: 10.28991/esj-2021-01259 Full Text: PDF
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Zhang, Nan, Jian Hua Zhang, and Jun Yang. "RFID Mutual Authentication Protocol Based on Chaos Key." Advanced Materials Research 846-847 (November 2013): 1519–23. http://dx.doi.org/10.4028/www.scientific.net/amr.846-847.1519.
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While radio frequency identification (RFID) is evolving as a major technology enabler for identifying and tracking goods and assets around the world, its security issues are also increasingly exposed. A Hash-based RFID mutual authentication protocol was put forward. The key was joined into the hash algorithm, and chaos sequences were used to update the key. The protocol enhances the security of the RFID system with low cost. Experiments show that the chaos system has the character of initial value sensitivity, which can be used to distribute and update the secret key. Safety analysis show that the mutual authentication protocol can solve security issues including eavesdropping, illegal access, masquerade, spoofing attack, position tracking.
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Jadoaa, Sawsan H., Rasha H. Ali, Wisal Hashim Abdulsalam, and Emad M. Alsaedi. "The Impact of Feature Importance on Spoofing Attack Detection in IoT Environment." Mesopotamian Journal of CyberSecurity 5, no. 1 (2025): 240–55. https://doi.org/10.58496/mjcs/2025/016.
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The Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tree (DT) and mutual information (MI). For classification, adaptive boosting (AdaBoost), XGBoost and categorical boosting (CatBoosting) are used to categorize incoming data as normal or spoofing. The experimental results indicate the efficiency of the suggested approach for correctly identifying spoofing attacks with high accuracy, fewer false positives, and reduced time needed. By utilizing feature importance and robust classification algorithms, the system can accurately differentiate between legitimate and malicious IoT traffic, thereby improving the overall security of IoT networks. The CatBoost classifier outperformed the AdaBoost and XGBoost classifiers in terms of accuracy.
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Bonavia, Luke John, Justin Jackson, and Richard Jurevics. "Posterior reversible encephalopathy syndrome in acute pancreatitis: a rare stroke mimic." BMJ Case Reports 13, no. 9 (2020): e232228. http://dx.doi.org/10.1136/bcr-2019-232228.
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We report a 71-year-old woman who presented with Posterior Reversible Encephalopathy Syndrome (PRES) in the setting of acute pancreatitis. On day 3 of her admission, she developed transient right-sided upper and lower limb weakness, reduced visual acuity and encephalopathy, initially regarded as an acute stroke. Brain MRI fluid-attenuated inversion recovery (FLAIR) T2 imaging performed the same day confirmed occipital and parietal hyperdensities consistent with PRES. Her blood pressure never exceeded 150/75 mm Hg throughout the course of the admission. Our case demonstrates PRES in the setting of acute pancreatitis with only a relatively moderate elevation in blood pressure. In order to prevent unnecessary intervention in the setting of presumed acute stroke, it is important to consider the potential differential diagnoses including PRES as rare masquerade of acute stroke or transient ischaemic attack.
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Lakhani, Leena. "PROTECTIVE COLORATION IN ANIMALS." International Journal of Research -GRANTHAALAYAH 2, no. 3SE (2014): 1–5. http://dx.doi.org/10.29121/granthaalayah.v2.i3se.2014.3515.
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Animals have range of defensive markings which helps to the risk of predator detection (camouflage), warn predators of the prey’s unpalatability (aposematism) or fool a predator into mimicry, masquerade. Animals also use colors in advertising, signalling services such as cleaning to animals of other species, to signal sexual status to other members of the same species. Some animals use color to divert attacks by startle (dalmatic behaviour), surprising a predator e.g. witheyespots or other flashes of color or possibly by motion dazzle, confusing a predator attack by moving a bold pattern like zebra stripes. Some animals are colored for physical protection, such as having pigments in the skin to protect against sunburn; some animals can lighten or darken their skin for temperature regulation. This adaptive mechanism is known as protective coloration. After several years of evolution, most animals now achieved the color pattern most suited for their natural habitat and role in the food chains. Animals in the world rely on their coloration for either protection from predators, concealment from prey or sexual selection. In general the purpose of protective coloration is to decrease an organism’s visibility or to alter its appearance to other organisms. Sometimes several forms of protective coloration are superimposed on one animal.
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Leena, Lakhani. "PROTECTIVE COLORATION IN ANIMALS." International Journal of Research - GRANTHAALAYAH Composition of Colours, December,2014 (2017): 1–5. https://doi.org/10.5281/zenodo.887485.
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Animals have range of defensive markings which helps to the risk of predator detection (camouflage), warn predators of the prey’s unpalatability (aposematism) or fool a predator into mimicry, masquerade. Animals also use colors in advertising, signalling services such as cleaning to animals of other species, to signal sexual status to other members of the same species. Some animals use color to divert attacks by startle (dalmatic behaviour), surprising a predator e.g. with eyespots or other flashes of color or possibly by motion dazzle, confusing a predator attack by moving a bold pattern like zebra stripes. Some animals are colored for physical protection, such as having pigments in the skin to protect against sunburn; some animals can lighten or darken their skin for temperature regulation. This adaptive mechanism is known as protective coloration. After several years of evolution, most animals now achieved the color pattern most suited for their natural habitat and role in the food chains. Animals in the world rely on their coloration for either protection from predators, concealment from prey or sexual selection. In general the purpose of protective coloration is to decrease an organism’s visibility or to alter its appearance to other organisms. Sometimes several forms of protective coloration are superimposed on one animal.
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Reed, Andy, Laurence Dooley, and Soraya Kouadri Mostefaoui. "The Guardian Node Slow DoS Detection Model for Real-Time Application in IoT Networks." Sensors 24, no. 17 (2024): 5581. http://dx.doi.org/10.3390/s24175581.
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The pernicious impact of malicious Slow DoS (Denial of Service) attacks on the application layer and web-based Open Systems Interconnection model services like Hypertext Transfer Protocol (HTTP) has given impetus to a range of novel detection strategies, many of which use machine learning (ML) for computationally intensive full packet capture and post-event processing. In contrast, existing detection mechanisms, such as those found in various approaches including ML, artificial intelligence, and neural networks neither facilitate real-time detection nor consider the computational overhead within resource-constrained Internet of Things (IoT) networks. Slow DoS attacks are notoriously difficult to reliably identify, as they masquerade as legitimate application layer traffic, often resembling nodes with slow or intermittent connectivity. This means they often evade detection mechanisms because they appear as genuine node activity, which increases the likelihood of mistakenly being granted access by intrusion-detection systems. The original contribution of this paper is an innovative Guardian Node (GN) Slow DoS detection model, which analyses the two key network attributes of packet length and packet delta time in real time within a live IoT network. By designing the GN to operate within a narrow window of packet length and delta time values, accurate detection of all three main Slow DoS variants is achieved, even under the stealthiest malicious attack conditions. A unique feature of the GN model is its ability to reliably discriminate Slow DoS attack traffic from both genuine and slow nodes experiencing high latency or poor connectivity. A rigorous critical evaluation has consistently validated high, real-time detection accuracies of more than 98% for the GN model across a range of demanding traffic profiles. This performance is analogous to existing ML approaches, whilst being significantly more resource efficient, with computational and storage overheads being over 96% lower than full packet capture techniques, so it represents a very attractive alternative for deployment in resource-scarce IoT environments.
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Alahmed, Shahad, Qutaiba Alasad, Jiann-Shiun Yuan, and Mohammed Alawad. "Impacting Robustness in Deep Learning-Based NIDS through Poisoning Attacks." Algorithms 17, no. 4 (2024): 155. http://dx.doi.org/10.3390/a17040155.
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The rapid expansion and pervasive reach of the internet in recent years have raised concerns about evolving and adaptable online threats, particularly with the extensive integration of Machine Learning (ML) systems into our daily routines. These systems are increasingly becoming targets of malicious attacks that seek to distort their functionality through the concept of poisoning. Such attacks aim to warp the intended operations of these services, deviating them from their true purpose. Poisoning renders systems susceptible to unauthorized access, enabling illicit users to masquerade as legitimate ones, compromising the integrity of smart technology-based systems like Network Intrusion Detection Systems (NIDSs). Therefore, it is necessary to continue working on studying the resilience of deep learning network systems while there are poisoning attacks, specifically interfering with the integrity of data conveyed over networks. This paper explores the resilience of deep learning (DL)—based NIDSs against untethered white-box attacks. More specifically, it introduces a designed poisoning attack technique geared especially for deep learning by adding various amounts of altered instances into training datasets at diverse rates and then investigating the attack’s influence on model performance. We observe that increasing injection rates (from 1% to 50%) and random amplified distribution have slightly affected the overall performance of the system, which is represented by accuracy (0.93) at the end of the experiments. However, the rest of the results related to the other measures, such as PPV (0.082), FPR (0.29), and MSE (0.67), indicate that the data manipulation poisoning attacks impact the deep learning model. These findings shed light on the vulnerability of DL-based NIDS under poisoning attacks, emphasizing the significance of securing such systems against these sophisticated threats, for which defense techniques should be considered. Our analysis, supported by experimental results, shows that the generated poisoned data have significantly impacted the model performance and are hard to be detected.
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Huang, Xinyu, Yunzhe Tian, Yifei He, et al. "Exposing Spoofing Attack on Flocking-Based Unmanned Aerial Vehicle Cluster: A Threat to Swarm Intelligence." Security and Communication Networks 2020 (December 9, 2020): 1–15. http://dx.doi.org/10.1155/2020/8889122.
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With the rapid development of wireless communication technology and intelligent mobile devices, unmanned aerial vehicle (UAV) cluster is becoming increasingly popular in both civilian and military applications. Recently, a swarm intelligence-based UAV cluster study, aiming to enable efficient and autonomous collaboration, has drawn lots of interest. However, new security problems may be introduced with such swarm intelligence. In this work, we perform the first detailed security analysis to a kind of flocking-based UAV cluster with 5 policies, an upgrade version of the well-known Boids model. Targeting a realistic threat in a source-to-destination flying task, we design a data spoofing strategy and further perform complete vulnerability analysis. We reveal that such design and implementation are highly vulnerable. After breaking through the authentication of ad hoc on-demand distance vector (AODV) routing protocol by rushing attack, an attacker can masquerade as the first-arrival UAV within a specific scope of destination and generate data spoofing of arrival status to the following UAVs, so as to interfere with their normal flying paths of destination arrival and cause unexpected arrival delays amid urgent tasks. Experiments with detailed analysis from the 5-UAV cluster to the 10-UAV cluster are conducted to show specific feature composition-based attack effect and corresponding average delay. We also discuss promising defense suggestions leveraging the insights from our analysis.
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Lee, JoonYoung, SungJin Yu, MyeongHyun Kim, YoungHo Park, SangWoo Lee, and BoHeung Chung. "Secure Key Agreement and Authentication Protocol for Message Confirmation in Vehicular Cloud Computing." Applied Sciences 10, no. 18 (2020): 6268. http://dx.doi.org/10.3390/app10186268.
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With the development of vehicular ad-hoc networks (VANETs) and Internet of vehicles (IoVs), a large amount of useful information is generated for vehicle drivers and traffic management systems. The amount of vehicle and traffic information is as large as the number of vehicles and it is enormous when compared to vehicle calculation and storage performance. To resolve this problem, VANET uses a combined cloud computing technology, called vehicular cloud computing (VCC), which controls vehicle-related data, and helps vehicle drivers directly or indirectly. However, VANETs remain vulnerable to attacks such as tracking, masquerade and man-in-the-middle attacks because VANETs communicate via open networks. To overcome these issues, many researchers have proposed secure authentication protocols for message confirmation with vehicular cloud computing. However, many researchers have pointed out that some proposed protocols use ideal tamper-proof devices (TPDs). They demonstrated that realistic TPDs cannot prevent adversaries attack. Limbasiya et al. presented a message confirmation scheme for vehicular cloud computing using a realistic TPD in order to prevent these problems. However, their proposed scheme still has security weaknesses over a TPD and does not guarantee mutual authentication. This paper proposes a secure key agreement and authentication protocol to address the security weaknesses inherent in the protocol of Limbasiya et al. The suggested protocol withstands malicious attacks and ensures secure mutual authentication for privacy-preserving. We prove that the proposed protocol can provide session key security using Real-Or-Random (ROR) model. We also employed Automated Validation of Internet Security Protocols and Applications (AVISPA) simulation tool to show that the proposed protocol is able to defeat replay and man-in-the-middle attacks. Furthermore, we established that the proposed protocol can resist other malicious attacks by conducting the informal security analysis. We proved that our proposed protocol is lightweight and suitable for VCC environments.
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Algarni, Fahad, and Saeed Ullah Jan. "A lightweight and secure protocol for teleworking environment." PLOS ONE 19, no. 3 (2024): e0298276. http://dx.doi.org/10.1371/journal.pone.0298276.
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The Internet has advanced so quickly that we can now access any service at any time, from any location. As a result of this capability, People around the world can benefit from the popularity and convenience of teleworking systems. Teleworking systems, however, are vulnerable to a range of attacks; as an unauthorized user enters the open communication line and compromises the whole system, that, in turn, creates a big hurdle for the teleworkers. Professional groups have presented numerous mechanisms for the security of teleworking systems to stop any harm, but there are still a lot of security issues like insider, stolen verifier, masquerade, replay, traceability and impersonation threats. In this paper, we propose that one of the security issues with teleworking systems is the lack of a secure authentication mechanism. In order to provide a secure teleworking environment, we have proposed a lightweight and secure protocol to authenticate all the participants and make the requisite services available in an efficient manner. The security analysis of the presented protocol has been investigated formally using the random oracle model (ROM) and ProVerif simulation and informally through illustration/attack discussions. Meanwhile, the performance metrics have been measured by considering computation and communication overheads. Upon comparing the proposed protocol with prior works, it has been demonstrated that our protocol is superior to its competitors. It is suitable for implementation because it achieved a 73% improvement in computation and 34% in communication costs.
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Dodoo, Herbert Cyril. "Deep Learning (DL) Oriented Forensic Analysis." Advances in Multidisciplinary and scientific Research Journal Publication 1, no. 1 (2022): 321–28. http://dx.doi.org/10.22624/aims/crp-bk3-p51.
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Cyber-attacks are now more prevalent than ever before in all aspects of our daily lives. As a result of this circumstance, both individuals and organizations are fighting cybercrime on a regular basis. Furthermore, today's hackers have advanced a step further and are capable of employing complex cyber-attack strategies, exacerbating the problem. Some of these approaches are minute and undetectable, and they frequently masquerade as genuine requests and directives. To combat this threat, cyber security professionals, as well as digital forensic investigators, are constantly compelled to filter through massive and complicated pools of data, also known as Big Data, in order to uncover Potential Digital Forensic Evidence. that can be used as evidence in court. Potential Digital Evidence can then be used to assist investigators in reaching certain conclusions and/or judgments. The fact that Big Data frequently comes from various sources and has diverse file formats makes cyber forensics even more difficult for investigators. When it comes to the processing of vast amounts of complicated data for forensic purposes, forensic investigators typically have less time and budget to fulfil the rising demands. This paper will be studying how to incorporate Deep Learning cognitive computing approaches into Cyber Forensics Keywords: Deep Learning, Forensic Analysis, Artificial Intelligence, Online Safety, Evidence BOOK Chapter ǀ Research Nexus in IT, Law, Cyber Security & Forensics. Open Access. Distributed Free Citation: Herbert Cyril Dodoo (2022): Deep Learning (DL) Oriented Forensic Analysis Book Chapter Series on Research Nexus in IT, Law, Cyber Security & Forensics. Pp 320-328 www.isteams.net/ITlawbookchapter2022. dx.doi.org/10.22624/AIMS/CRP-BK3-P51
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Li, Shuiwang, Qijun Zhao, and Xiangdong Fei. "An Improved AM–FM-Based Approach for Reconstructing Fingerprints from Minutiae." International Journal of Image and Graphics 15, no. 01 (2015): 1550007. http://dx.doi.org/10.1142/s0219467815500072.
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Reconstructing fingerprint images from a given set of minutiae is an important issue in analyzing the masquerade attack of automated fingerprint recognition systems (AFRSs) and in generating large scale databases of synthetic fingerprint images for the performance evaluation of AFRSs. Existing fingerprint reconstruction methods either cannot generate visually plausible or realistic fingerprint images, or suffer from the occurrence of false minutiae in the reconstructed fingerprint images. In this paper, we analyze the underlying reason of false minutiae generated by state-of-the-art amplitude modulation–frequency modulation (AM–FM)-based methods. Furthermore, we propose an improved approach by devising a better way to cope with the branch cuts (or discontinuities) in the fingerprint ridge orientation fields, and by introducing an effective scheme to remove false minutiae from the reconstructed fingerprint images. Compared with previous AM–FM based methods, the proposed method gets rid of block effects and successfully reduces the number of false minutiae. Theoretic proofs are provided with respect to the effectiveness of the proposed method for fingerprints with multiple singular points. The proposed method has also been evaluated on public fingerprint databases. The results demonstrate that it is superior to the existing methods in reconstructing realistic fingerprint images with fewer false minutiae.
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Sun, Da-Zhi, Yi-Na Gao, and Yangguang Tian. "On the Security of a PUF-Based Authentication and Key Exchange Protocol for IoT Devices." Sensors 23, no. 14 (2023): 6559. http://dx.doi.org/10.3390/s23146559.
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Recently, Roy et al. proposed a physically unclonable function (PUF)-based authentication and key exchange protocol for Internet of Things (IoT) devices. The PUF protocol is efficient, because it integrates both the Node-to-Node (N2N) authentication and the Node-to-Server (N2S) authentication into a standalone protocol. In this paper, we therefore examine the security of the PUF protocol under the assumption of an insider attack. Our cryptanalysis findings are the following. (1) A legitimate but malicious IoT node can monitor the secure communication among the server and any other IoT nodes in both N2N authentication and N2S authentication. (2) A legitimate but malicious IoT node is able to impersonate a target IoT node to cheat the server and any other IoT nodes in N2N authentication and the server in N2S authentication, respectively. (3) A legitimate but malicious IoT node can masquerade as the server to cheat any other target IoT nodes in both N2N authentication and N2S authentication. To the best of our knowledge, our work gives the first non-trivial concrete security analysis for the PUF protocol. In addition, we employ the automatic verification tool of security protocols, i.e., Scyther, to confirm the weaknesses found in the PUF protocol. We finally consider how to prevent weaknesses in the PUF protocol.
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Prodeus, Maksym, Andrii Nicheporuk, and Antonina Kashtalian. "Honeypot-Based Information Monitoring, Detection, Response and Protection System." Central Ukrainian Scientific Bulletin. Technical Sciences 1, no. 11(42) (2025): 56–67. https://doi.org/10.32515/2664-262x.2025.11(42).1.56-67.
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The increasing complexity of cyber threats poses significant challenges to existing security measures, which often fail to provide sufficient protection. This paper presents an approach to improving cybersecurity through honeypot-based techniques. The study focuses on the development and deployment of decoy files designed to detect unauthorized access attempts and monitor malicious activities. Honeypots play a crucial role in identifying various attack types, including insider threats and masquerade attacks, which traditional security systems often overlook. The paper also discusses the integration of honeypots into comprehensive security frameworks, examining their optimal use cases and effectiveness in real-world applications. The research explores the design and implementation of an advanced honeypot framework that enhances threat detection and response. The proposed system utilizes dynamic decoy files, which change metadata and content to maintain authenticity and attract malicious actors. Various triggers, such as file access, modification, and unauthorized copying, are employed to detect suspicious behavior. The study also evaluates the effectiveness of automated response mechanisms, including IP blocking and real-time monitoring. The framework's performance is analyzed through experimental deployment across different IT environments, highlighting its advantages over traditional static honeypots. Key performance indicators, including detection accuracy, response time, and false positive rates, are assessed to validate the system's reliability. The results demonstrate that the proposed honeypot-based system significantly improves threat detection and response capabilities while minimizing false alarms. The integration of dynamic honeypots into corporate cybersecurity infrastructures enhances resilience against cyberattacks, including ransomware and advanced persistent threats. However, certain limitations, such as the inability to detect memory-only malware and highly obfuscated threats, remain challenges for future research. The study concludes that adaptive honeypot strategies, combined with automated threat intelligence, can substantially enhance modern cybersecurity defense mechanisms.
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Annadurai, Soorya, and Bhargav J. Bhatkalkar. "Secure Multiparty Device Pairing Using Random Peephole Generations." Journal of Computational and Theoretical Nanoscience 17, no. 1 (2020): 216–21. http://dx.doi.org/10.1166/jctn.2020.8653.
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A secure device pairing mechanism is used to establish a trusted communication channel between unassociated wireless devices. The broadcast nature of wireless communication opens the door for man-in-the-middle (MITM) attacks, and even other subtle forms of masquerader and misfeasor attacks. This paper introduces a simple device pairing approach to tackle such attacks seamlessly. The algorithm is compatible with a multitude of devices, whereas a majority of existing algorithms are based on two devices exclusively. This approach utilizes a human visual channel as an Out-Of-Band (OOB) channel to authenticate the public keys exchanged between the devices. The interactive nature of this approach forces user attention, hence improving the reliability and consistency of the device pairing process. To do so, we introduce the concept of ‘peepholes,’ and mathematically define it before demonstrating the algorithm’s methodology. Subsequent sections also demonstrate its robustness against attacks via misfeasors, masqueraders, and men-in-the-middle.
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LEE, CHENG-CHI, CHUN-TA LI, and SHUN-DER CHEN. "TWO ATTACKS ON A TWO-FACTOR USER AUTHENTICATION IN WIRELESS SENSOR NETWORKS." Parallel Processing Letters 21, no. 01 (2011): 21–26. http://dx.doi.org/10.1142/s0129626411000047.
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Recently, a secure two-factor user authentication scheme for wireless sensor networks (WSN) was proposed by Das. The proposed scheme can resist many logged in users with the same login identity, stolen-verifier, guessing, impersonation and replay threats. In this paper we study the two-factor user authentication scheme for WSN and find that the scheme is insecure against the masquerade attacks. With our masquerade attacks, an attacker can masquerade as any legal user to login the gateway node without knowing the user's password or can masquerade as a gateway node to communicate with the legal user at anytime.
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Das, Sima, Nishi Gupta, and Neeraj Chawla. "Canaliculitis masquerading as Dacryocystitis: Rhinologist's Dilemma." An International Journal Clinical Rhinology 10, no. 2 (2017): 91–92. http://dx.doi.org/10.5005/jp-journals-10013-1315.
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ABSTRACT Aim To highlight canaliculitis masquerading as chronic dacryocystitis that may mislead a rhinologist. Background Canaliculitis is an inflammation of the lacrimal canaliculi caused by infection or as a complication of punctal plug insertion. It is often misdiagnosed, leading to a delay in diagnosis. Case report We report a case of a 20-year-old female patient who presented with complaints of watering from left eye since 1 year and was referred to the Department of Ear, Nose, and Throat for endoscopic dacryocystorhinostomy (DCR). She had a history of silicone punctal plug insertion in the same eye for “dry eye” following an attack of herpes zoster 12 years earlier. She was asymptomatic for 10 years following punctal plug insertion, but started complaining of epiphora since the last 2 years. Punctal plug was removed 1 year back by an ophthalmologist but the epiphora persisted. Regurgitation of purulent discharge on pressure over lacrimal sac area made it look like dacryocystitis. Syringing through lower punctum was blocked while through the upper punctum it was patent. Thus, possibility of nasolacrimal duct block was ruled out. An occuloplasty opinion was sought and a diagnosis of lower canaliculitis with possibility of retained plug was made. Conclusion Canaliculitis should be considered as a differential diagnosis in cases presenting with epiphora as canaliculitis is a close masquerade of dacryocystitis. Clinical significance As more and more rhinologists are getting direct referrals of cases needing endoscopic DCRs, it is important for them to be well aware of other associated pathologies of proximal lacrimal system. This will help them to reach a correct diagnosis before going ahead with endoscopic DCR. How to cite this article Gupta N, Das S, Chawla N. Canaliculitis masquerading as Dacryocystitis: Rhinologist's Dilemma. Clin Rhinol An Int J 2017;10(2):91-92.
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Razo-Zapata, Iván S., Carlos Mex-Perera, and Raúl Monroy. "Masquerade attacks based on user's profile." Journal of Systems and Software 85, no. 11 (2012): 2640–51. http://dx.doi.org/10.1016/j.jss.2012.06.014.
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Ashraf, Zeeshan, Adnan Sohail, and Muddesar Iqbal. "Design and Performance Evaluation of an Authentic End-to-End Communication Model on Large-Scale Hybrid IPv4-IPv6 Virtual Networks to Detect MITM Attacks." Cryptography 8, no. 4 (2024): 49. http://dx.doi.org/10.3390/cryptography8040049.
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After the end of IPv4 addresses, the Internet is moving towards IPv6 address architecture quickly with the support of virtualization techniques worldwide. IPv4 and IPv6 protocols will co-exist long during the changeover process. Some attacks, such as MITM attacks, do not discriminate by appearance and affect IPv4 and IPv6 address architectures. In an MITM attack, the attacker secretly captures the data, masquerades as the original sender, and sends it toward the receiver. The receiver replies to the attacker because the receiver does not authenticate the source. Therefore, the authentication between two parties is compromised due to an MITM attack. The existing authentication schemes adopt complicated mathematical procedures. Therefore, the existing schemes increase computation and communication costs. This paper proposes a lightweight and authentic end-to-end communication model to detect MITM attacks using a pre-shared symmetric key. In addition, we implement and analyze the performance of our proposed security model on Linux-based virtual machines connected to large-scale hybrid IPv4-IPv6 virtual networks. Moreover, security analyses prove the effectiveness of our proposed model. Finally, we compare the performance of our proposed security model with existing models in terms of computation cost and communication overhead.
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Nasser, Hiba Imad, and Mohammed Abdulridha Hussain. "Defending a wireless LAN against ARP spoofing attacks using a Raspberry Pi." Basrah Researches Sciences 48, no. 2 (2022): 123–35. http://dx.doi.org/10.56714/bjrs.48.2.12.
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The Address Resolution Protocol (ARP) is a protocol that converts Internet Protocol (IP) addresses to Media Access Control (MAC) addresses. Due to a security issue known as "Man in the Middle," identity theft is feasible using the ARP protocol. ARP spoofing is one of the weaknesses in wireless networks when an attacker effectively masquerades as a legitimate one. Spoofing attacks will reduce network performance and break several security measures. In networks that use MAC address-based filtering to verify clients, all a spoofer needs is an actual MAC address from an authorised client to gain an unfair advantage. The research recommends developing a security system recognising and preventing ARP spoofing attacks. This system detects ARP spoofing attempts by comparing the static MAC address of the original router to the router's MAC address in the ARP cache table. After detecting the attack using information collected from the router's MAC address in the ARP cache table, the system will conduct a de-authentication attack against the attacker's MAC address. If the attacker is disconnected from the WLAN, they cannot perform ARP spoofing attacks. This system is operated using a Raspberry Pi Model B. Most ARP spoofing attacks can be detected in 0.93 seconds, and responding takes 3.05 seconds.
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Al-janabi, Rana Jumaa Surayh. "Messenger Attack(Problems and Solutions)." Journal of Kufa for Mathematics and Computer 1, no. 2 (2010): 12–22. http://dx.doi.org/10.31642/jokmc/2018/010202.
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For years, people think that the major threat to various companies' computer networks doesn't come from outside hackers,but from internal(often disgruntled) employees. However, a new study disputes that, saying that outside hack attacks are the largest threat. In fact, the outside hackers usethe ability of messenger to not only transfer text messages,but also to files transferring. Consequently, messengers can transfer worms and other malicious software ( malware).This research includes many practical methods and tricks to attack yahoo messenger by sending executable files that are compressed and masqueraded, that files are responsible for converting Yahoo! Musicand other options to malicious web site, and also it is possible to insert messenger into infinite loop, delete messenger after forcing it to close, or convert its path into malicious program path, insuring that done even after restart computer. And also it containsmprotection methods for that attack which are responsible for disabling system program such as (task manager, system restore, system configuration utility etc) to ensure that the user couldn't remove the program that caused attack.Finally in this research, software is designed to break that attack by enabling system tools and that will lead to facilitate the task of ending attack. Actually, this software is considered as a solution towidespread problem caused by many malware.
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Barseghyan, Ghazaros, Yuyu Yuan, and Manawa Anakpa. "Model for Detection of Masquerade Attacks Based on Variable-Length Sequences." IEEE Access 8 (2020): 210140–57. http://dx.doi.org/10.1109/access.2020.3039166.
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