Gotowe bibliografie tematyczne / Malicious attacks

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Gotowa bibliografia na temat „Malicious attacks”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "Malicious attacks"

Wang, Jing Lei. "Research on the Detection Method of the Malicious Attacks on Campus Network." Applied Mechanics and Materials 644-650 (September 2014): 3291–94. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.3291.

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The problem of malicious attacks detection on campus network is studied to improve the accuracy of detection. When detecting malicious attacks on campus network, a conventional manner is usually conducted in malicious attack detection of campus network. If a malicious signature is mutated into a new feature, the conventional detection method cannot recognize the new malicious signature, resulting in a relative low detection accuracy rate of malicious attacks. To avoid these problems, in this paper, the malicious attacks detection method for campus network based on support vector machine algori

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Glancy, Fletcher, David P. Biros, Nan Liang, and Andy Luse. "Classification of malicious insiders and the association of the forms of attacks." Journal of Criminal Psychology 10, no. 3 (2020): 233–47. http://dx.doi.org/10.1108/jcp-03-2020-0012.

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Purpose The authors argue that the current studies about malicious insiders confuse the fact that malicious attacks belong to two different categories, namely, those that launch instrumental attacks and expressive attacks. The authors collect malicious insider data from publicly available sources and use text-mining techniques to analyze the association between malicious insiders’ characteristics and the different types of attack. Design/methodology/approach The authors investigated the relationship between personality characteristics and different types of malicious attacks. For the personali

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Jiang, Yufan, Maryam Zarezadeh, Tianxiang Dai, and Stefan Köpsell. "AlphaFL: Secure Aggregation with Malicious2 Security for Federated Learning against Dishonest Majority." Proceedings on Privacy Enhancing Technologies 2025, no. 4 (2025): 348–68. https://doi.org/10.56553/popets-2025-0134.

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Federated learning (FL) proposes to train a global machine learning model across distributed datasets. However, the aggregation protocol as the core component in FL is vulnerable to well-studied attacks, such as inference attacks, poisoning attacks [71] and malicious participants who try to deviate from the protocol [24]. Therefore, it is crucial to achieve both malicious security and poisoning resilience from cryptographic and FL perspectives, respectively. Prior works either achieve incomplete malicious security [76], address issues by using expensive cryptographic tools [22, 59] or assume t

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Kumari, Ankita, Sandip Dutta, and Soubhik Chakraborty. "A comparative study of different security issues in MANET." International Journal of Experimental Research and Review 31, Spl Volume (2023): 168–86. http://dx.doi.org/10.52756/10.52756/ijerr.2023.v31spl.016.

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In a MANET (Mobile Ad-Hoc Network), an intruder can attempt to gain unlawful access to the network to obtain sensitive information. These attacks can occur at various network layers, and different attacks can be carried out. To mitigate the risks of such attacks, several solutions have been proposed. It can be characterized by dynamic topology, meaning that the network is formed by a group of nodes communicating wirelessly and without centralized control. This feature makes MANETs highly vulnerable to attacks, especially when malicious nodes are introduced into the network. These malicious nod

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S., Tamil Selvi, and Visalakshi P. "Connect attack in IoT-WSN detect through cyclic analysis based on forward and backward elimination." PeerJ Computer Science 10 (June 28, 2024): e2130. http://dx.doi.org/10.7717/peerj-cs.2130.

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IoT-wireless sensor networks (WSN) have extensive applications in diverse fields such as battlegrounds, commercial sectors, habitat monitoring, buildings, smart homes, and traffic surveillance. WSNs are susceptible to various types of attacks, such as malicious attacks, false data injection attacks, traffic attacks, and HTTP flood attacks. CONNECT attack is a novel attack in WSN. CONNECT attack plays a crucial role through disrupting packet transmission and node connections and significantly impacts CPU performance. Detecting and preventing CONNECT attacks is imperative for enhancing WSN effic

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Lee, Kyungroul, Jaehyuk Lee, and Kangbin Yim. "Classification and Analysis of Malicious Code Detection Techniques Based on the APT Attack." Applied Sciences 13, no. 5 (2023): 2894. http://dx.doi.org/10.3390/app13052894.

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According to the Fire-eye’s M-Trends Annual Threat Report 2022, there are many advanced persistent threat (APT) attacks that are currently in use, and such continuous and specialized APT attacks cause serious damages attacks. As APT attacks continue to be active, there is a need for countermeasures to detect new and existing malicious codes. An APT attack is a type of intelligent attack that analyzes the target and exploits its vulnerabilities. It attempts to achieve a specific purpose, and is persistent in continuously attacking and threatening the system. With this background, this paper ana

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Pohane, Miss Mayuri Arvind. "Implementation Paper on Detection of Malicious URLs Using Machine Learning Techniques." International Journal for Research in Applied Science and Engineering Technology 10, no. 4 (2022): 296–98. http://dx.doi.org/10.22214/ijraset.2022.41084.

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Abstract: Detecting and preventing the user from the malicious site attacks are significant tasks. A huge number of attacks have been observed in last few years. Malicious attack detection and prevention system plays an immense role against these attacks by protecting the system’s critical information. The internet security software and fire walls are not enough to provide full protection to the system. Hence efficient detection systems are essential for web security. These existing methods have some drawbacks results into numbers of victims to increase. Hence we developed a system which helps

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Isah, Abdulkadir Onivehu, John Kolo Alhassan, Idris Ismaila, and Olawale Surajudeen Adebayo. "Tracking of Malicious Attacks on Data Online: A Systematic Review." Transactions on Networks and Communications 8, no. 4 (2020): 31–44. http://dx.doi.org/10.14738/tnc.84.9463.

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Tracking of computer network system attacks is a proactive measure to protect against attacks on data, that are basically encrypted for confidential security reasons, while in transit on the computer information channel. Cyber security threat continues to increase in direct proportion to the rate at which internet based services are deployed. In this systematic review, 53 research papers from reputable publishers were downloaded out of which 41 papers that are closely related to tracking of malicious attackers on encrypted data online were review under the consideration of attacks on encrypted

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Boyanov, Petar. "A TAXONOMY OF THE CYBER ATTACKS." Journal scientific and applied research 3, no. 1 (2013): 114–24. http://dx.doi.org/10.46687/jsar.v3i1.73.

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In this paper is made a sophisticated taxonomy of the malicious cyber attacks. The cyber attacks are summarized into several mainly types with additional subtypes for everyone attack. Thanks to the achieved comparative results in this paper many users can find and analyze different flaws and vulnerabilities in their computer and network systems and thereby they could detect and prevent future malicious cyber attacks.

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Aridoss, Manimaran. "Defensive Mechanism Against DDoS Attack to Preserve Resource Availability for IoT Applications." International Journal of Handheld Computing Research 8, no. 4 (2017): 40–51. http://dx.doi.org/10.4018/ijhcr.2017100104.

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The major challenge of Internet of Things (IoT) generated data is its hypervisor level vulnerabilities. Malicious VM deployment and termination are so simple due to its multitenant shared nature and distributed elastic cloud features. These features enable the attackers to launch Distributed Denial of Service attacks to degrade cloud server performance. Attack detection techniques are applied to the VMs that are used by malicious tenants to hold the cloud resources by launching DDoS attacks at data center subnets. Traditional dataflow-based attack detection methods rely on the similarities of

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Rozprawy doktorskie na temat "Malicious attacks"

Opie, Jake Weyman. "Securing softswitches from malicious attacks." Thesis, Rhodes University, 2007. http://hdl.handle.net/10962/d1007714.

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Traditionally, real-time communication, such as voice calls, has run on separate, closed networks. Of all the limitations that these networks had, the ability of malicious attacks to cripple communication was not a crucial one. This situation has changed radically now that real-time communication and data have merged to share the same network. The objective of this project is to investigate the securing of softswitches with functionality similar to Private Branch Exchanges (PBX) from malicious attacks. The focus of the project will be a practical investigation of how to secure ILANGA, an ASTER

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Abu-Bakar, Kamalrulnizam. "Protecting agents against malicious host attacks." Thesis, Aston University, 2004. http://publications.aston.ac.uk/10612/.

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The introduction of agent technology raises several security issues that are beyond conventional security mechanisms capability and considerations, but research in protecting the agent from malicious host attack is evolving. This research proposes two approaches to protecting an agent from being attacked by a malicious host. The first approach consists of an obfuscation algorithm that is able to protect the confidentiality of an agent and make it more difficult for a malicious host to spy on the agent. The algorithm uses multiple polynomial functions with multiple random inputs to convert an a

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Fischer, Benjamin. "Vehicular Group Membership Resilient to Malicious Attacks." Thesis, Linköpings universitet, Programvara och system, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-158086.

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There is a range of tools and techniques in the realm of information security that can be used to enhance the security of a distributed network protocol and some of them introduce new problems. A security analysis of the distributed network protocol SLMP is made and three vulnerabilities are identified; messages can be intercepted and tampered with, nodes can fake id, and leader nodes can do a lot of harm if they are malicious. Three versions of SLMP that aims to remedy these vulnerabilities are implemented and the results show that while they remedy the vulnerabilities some of them introduce

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Casile, Roberta <1986&gt. "GNSS interference management techniques against malicious attacks." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amsdottorato.unibo.it/7025/1/Casile_Roberta_tesi.pdf.

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This thesis collects the outcomes of a Ph.D. course in Telecommunications Engineering and it is focused on the study and design of possible techniques able to counteract interference signal in Global Navigation Satellite System (GNSS) systems. The subject is the jamming threat in navigation systems, that has become a very increasingly important topic in recent years, due to the wide diffusion of GNSS-based civil applications. Detection and mitigation techniques are developed in order to fight out jamming signals, tested in different scenarios and including sophisticated signals. The thesis i

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Sivakumaran, Arun. "Malicious user attacks in decentralised cognitive radio networks." Diss., University of Pretoria, 2020. http://hdl.handle.net/2263/79657.

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Cognitive radio networks (CRNs) have emerged as a solution for the looming spectrum crunch caused by the rapid adoption of wireless devices over the previous decade. This technology enables efficient spectrum utility by dynamically reusing existing spectral bands. A CRN achieves this by requiring its users – called secondary users (SUs) – to measure and opportunistically utilise the band of a legacy broadcaster – called a primary user (PU) – in a process called spectrum sensing. Sensing requires the distribution and fusion of measurements from all SUs, which is facilitated by a variety of arch

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Mahlburg, Karl. "Structure Attacks in Cryptographic Protocols." Scholarship @ Claremont, 2001. https://scholarship.claremont.edu/hmc_theses/130.

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Cryptographic protocols are in general difficult to analyze, and complicated attacks exposing security flaws have remained hidden years after a protocol is developed. Recently developed tools such as strand spaces and inductive logical proofs provide mechanical procedures for analyzing protocols. The key to these methods is that a generous upper bound on the activity of a malicious penetrator is often much easier to work with than a tighter bound. However, these formalizations make strong assumptions about the algebraic structure of the cryptosystem that are never met in a real application. In

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Narasimhan, Mayur Harn Lein. "Protecting a mobile agent from colluded truncation attacks by malicious hosts." Diss., UMK access, 2007.

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Thesis (M.S.)--School of Computing and Engineering. University of Missouri--Kansas City, 2007.<br>"A thesis in computer science." Typescript. Advisor: Lein Harn. Vita. Title from "catalog record" of the print edition Description based on contents viewed May 23, 2008. Includes bibliographical references (leaves 57-58). Online version of the print edition.

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Jolley, Jason. "Attribution, state responsibility, and the duty to prevent malicious cyber-attacks in international law." Thesis, University of Glasgow, 2017. http://theses.gla.ac.uk/8452/.

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Malicious cyber-attacks, those cyber-attacks which do not rise to the level of force in international law, pose a significant problem to the international community. Attributing responsibility for malicious cyber-attacks is imperative if states are to respond and prevent the attacks from continuing. Unfortunately, due to both technical and legal issues attributing malicious cyber-attacks to the responsible state or non-state actor is difficult if not impossible in the vast majority of attacks. Even if an injured state may recursively trace the malicious cyber-attack to the responsible IP addre

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Likarish, Peter F. "Early detection of malicious web content with applied machine learning." Diss., University of Iowa, 2011. https://ir.uiowa.edu/etd/4871.

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This thesis explores the use of applied machine learning techniques to augment traditional methods of identifying and preventing web-based attacks. Several factors complicate the identification of web-based attacks. The first is the scale of the web. The amount of data on the web and the heterogeneous nature of this data complicate efforts to distinguish between benign sites and attack sites. Second, an attacker may duplicate their attack at multiple, unexpected locations (multiple URLs spread across different domains) wit

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Książki na temat "Malicious attacks"

M, Johansson Jesper, ed. Windows vista security: Securing vista against malicious attacks. Wiley Technology Pub., 2007.

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Sun, Kun, and Shu Wang. Secure Voice Processing Systems against Malicious Voice Attacks. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-44748-8.

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Chen, Bo, Tongxiang Li, Wen-An Zhang, and Li Yu. Secure Fusion Estimation and Control for Cyber-Physical Systems Under Malicious Attacks. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-97-9396-9.

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Jiang, Jiaojiao, Sheng Wen, Bo Liu, Shui Yu, Yang Xiang, and Wanlei Zhou. Malicious Attack Propagation and Source Identification. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-02179-5.

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United States. Congress. House. Committee on Science. Subcommittee on Technology. The love bug virus: Protecting lovesick computers from malicious attack : hearing before the Subcommittee on Technology of the Committee on Science, House of Representatives, One Hundred Sixth Congress, second session, May 10, 2000. U.S. G.P.O., 2000.

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Grimes, Roger A., and Jesper M. Johansson. Windows Vista Security: Securing Vista Against Malicious Attacks. Wiley, 2007.

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Grimes, Roger A., and Jesper M. Johansson. Windows Vista Security: Securing Vista Against Malicious Attacks. Wiley & Sons, Incorporated, John, 2008.

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Secure Voice Processing Systems Against Malicious Voice Attacks. Springer, 2023.

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Mauro, Aaron. The Language of Cyber Attacks. Bloomsbury Publishing Plc, 2024. http://dx.doi.org/10.5040/9781350354715.

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Many cyberattacks begin with a lure: a seemingly innocent message designed to establish trust with a target to obtain sensitive information or compromise a computer system. The perils of clicking an unknown link or divulging sensitive information via email are well-known, so why do we continue to fall prey to these malicious messages?This groundbreaking book examines the rhetoric of deception through the lure, asking where its all-too-human allure comes from and suggesting ways in which we can protect ourselves online. Examining practices and tools such as phishing, ransomware and clickbait, t

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Kleymenov, Alexey, and Amr Thabet. Mastering Malware Analysis: A Malware Analyst's Practical Guide to Combating Malicious Software, APT, Cybercrime, and IoT Attacks. Packt Publishing, Limited, 2022.

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Części książek na temat "Malicious attacks"

Yu, Shui. "Malicious Networks for DDoS Attacks." In Distributed Denial of Service Attack and Defense. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-9491-1_2.

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Rong, Qingnan, Jun Zhang, Xiaoqian Sun, and Sebastian Wandelt. "Network Strengthening Against Malicious Attacks." In Complex Networks and Their Applications VIII. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36687-2_63.

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Jiang, Jiaojiao, Sheng Wen, Shui Yu, Bo Liu, Yang Xiang, and Wanlei Zhou. "User Influence in the Propagation of Malicious Attacks." In Malicious Attack Propagation and Source Identification. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02179-5_3.

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Li, Yuping, Jiyong Jang, Xin Hu, and Xinming Ou. "Android Malware Clustering Through Malicious Payload Mining." In Research in Attacks, Intrusions, and Defenses. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66332-6_9.

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Lekies, Sebastian, Nick Nikiforakis, Walter Tighzert, Frank Piessens, and Martin Johns. "DEMACRO: Defense against Malicious Cross-Domain Requests." In Research in Attacks, Intrusions, and Defenses. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33338-5_13.

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Alnabulsi, Hussein, and Rafiqul Islam. "Web Sanitization from Malicious Code Injection Attacks." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98776-7_27.

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Zhu, Yajie, Tai Xin, and Indrakshi Ray. "Recovering from Malicious Attacks in Workflow Systems." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11546924_2.

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Chen, Weitong, Xiaofen Tu, Xin Liu, Jianwei Kong, Xiubo Chen, and Xiaomeng Liu. "Blockchain-Based Voting Scheme Against Malicious Attacks." In Proceedings of the UNIfied Conference of DAMAS, IncoME and TEPEN Conferences (UNIfied 2023). Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-49421-5_80.

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Ray, Indrajit, and Nayot Poolsapassit. "Using Attack Trees to Identify Malicious Attacks from Authorized Insiders." In Computer Security – ESORICS 2005. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11555827_14.

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Sun, Kun, and Shu Wang. "Acoustic Compensation System Against Adversarial Voice Recognition." In Secure Voice Processing Systems against Malicious Voice Attacks. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-44748-8_4.

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Streszczenia konferencji na temat "Malicious attacks"

Abozaid, Fatemah, and Ali Baydoun. "Resilience of Aviation Cyber-Physical Systems to Malicious Attacks." In 2024 International Conference on Computer and Applications (ICCA). IEEE, 2024. https://doi.org/10.1109/icca62237.2024.10927823.

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Wu, Qirui, Yirun Zhang, Zhaohui Yang, and Mohammad Shikh-Bahaei. "Knowledge Distillation-Based Robust UAV Swarm Communication Under Malicious Attacks." In 2024 IEEE International Conference on Communications Workshops (ICC Workshops). IEEE, 2024. http://dx.doi.org/10.1109/iccworkshops59551.2024.10615342.

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Falou, Ammar El. "A Study on Malicious Attacks for RIS-Aided Wireless Systems." In 2025 5th IEEE Middle East and North Africa Communications Conference (MENACOMM). IEEE, 2025. https://doi.org/10.1109/menacomm62946.2025.10911031.

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Mahbooba, Basim, Mohan Timilsina, and Martin Serrano. "Trusting Machine Learning Algorithms in Predicting Malicious Nodes Attacks." In 9th International Conference on Artificial Intelligence and Applications (AIAP 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.120408.

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Identifying network attacks is a very crucial task for Internet of things (IoT) security. The increasing amount of IoT devices is creating a massive amount of data and opening new security vulnerabilities that malicious users can exploit to gain access. Recently, the research community in IoT Security has been using a data- driven approach to detect anomaly, intrusion, and cyber-attacks. However, getting accurate IoT attack data is time-consuming and expensive. On the other hand, evaluating complex security systems requires costly and sophisticated modeling practices with expert security profe

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Wan, Wei, Shengshan Hu, jianrong Lu, Leo Yu Zhang, Hai Jin, and Yuanyuan He. "Shielding Federated Learning: Robust Aggregation with Adaptive Client Selection." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/106.

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Federated learning (FL) enables multiple clients to collaboratively train an accurate global model while protecting clients' data privacy. However, FL is susceptible to Byzantine attacks from malicious participants. Although the problem has gained significant attention, existing defenses have several flaws: the server irrationally chooses malicious clients for aggregation even after they have been detected in previous rounds; the defenses perform ineffectively against sybil attacks or in the heterogeneous data setting. To overcome these issues, we propose MAB-RFL, a new method for robust aggre

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Abdelgawad, Mohamed, and Marianne A. Azer. "Securing Hardware from Malicious Attacks." In 2021 16th International Conference on Computer Engineering and Systems (ICCES). IEEE, 2021. http://dx.doi.org/10.1109/icces54031.2021.9686147.

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Arulsuju, D. "Hunting malicious attacks in social networks." In 2011 Third International Conference on Advanced Computing (ICoAC). IEEE, 2011. http://dx.doi.org/10.1109/icoac.2011.6165172.

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Rayatidamavandi, Maede, Frank Conlon, and Mahshid Rahnamay-Naeini. "Reducing Network Vulnerability to Malicious Attacks." In 2018 International Conference on Computing, Networking and Communications (ICNC). IEEE, 2018. http://dx.doi.org/10.1109/iccnc.2018.8390313.

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Au, Man Ho, Yi Mu, Jing Chen, Duncan S. Wong, Joseph K. Liu, and Guomin Yang. "Malicious KGC attacks in certificateless cryptography." In Asia CCS07: Asia CCS'07 ACM Symposium on Information, Computer and Communications Security. ACM, 2007. http://dx.doi.org/10.1145/1229285.1266997.

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Tejaswi, Chakravarma Sai, Yemireddy Chaitanya, A. Jesudoss, and Prayla Shyry. "Malicious Attacks Detection Using Machine Learning." In 2022 4th International Conference on Inventive Research in Computing Applications (ICIRCA). IEEE, 2022. http://dx.doi.org/10.1109/icirca54612.2022.9985551.

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Raporty organizacyjne na temat "Malicious attacks"

Kelly, Luke. Threats to Civilian Aviation Since 1975. Institute of Development Studies (IDS), 2021. http://dx.doi.org/10.19088/k4d.2021.019.

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This literature review finds that the main malicious threats to civilian aviation since 1975 are attacks by terrorist groups, deliberate or accidental damage arising from conflicts, and incidents caused by people who work for airlines or airports. While the sector has responded to hijackings and bombings with increasing security since the 1970s, actors seeking to attack aircraft have modified their tactics, and new threats such as liquid explosives and cyber attacks have emerged. Civilian aviation has seen relatively fewer accidents and deaths over the years, but threats remain. The review foc

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Christie, Lorna. Physical threats to infrastructure. Parliamentary Office of Science and Technology, 2021. http://dx.doi.org/10.58248/hs23.

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Fekri, Faramarz, E. Ayday, and R. Subramanian. Design Principles for Secure Wireless Sensor Networks: Key Management Schemes and Malicious Attacks. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada533169.

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Desmedt, Yvo. Critical Analysis of the Use of Redundancy to Achieve Survivability in the Presence of Malicious Attacks. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada403635.

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Fedchenko, Vitaly. Nuclear Security During Armed Conflict: Lessons From Ukraine. Stockholm International Peace Research Institute, 2023. http://dx.doi.org/10.55163/zzsp5617.

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The attacks on nuclear installations in Ukraine by the Russian military in 2022 were unprecedented. Nuclear security aims at prevention, detection and response to malicious or unauthorized acts by non-state actors, not the armed forces of a state. However, an international armed conflict creates new circumstances in which a national nuclear security regime must operate. In March 2022 the director general of the International Atomic Energy Agency (IAEA) highlighted ‘seven indispensable pillars of nuclear safety and security’ in extraordinary circumstances. There are three further areas in which

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Tayeb, Shahab. Taming the Data in the Internet of Vehicles. Mineta Transportation Institute, 2022. http://dx.doi.org/10.31979/mti.2022.2014.

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As an emerging field, the Internet of Vehicles (IoV) has a myriad of security vulnerabilities that must be addressed to protect system integrity. To stay ahead of novel attacks, cybersecurity professionals are developing new software and systems using machine learning techniques. Neural network architectures improve such systems, including Intrusion Detection System (IDSs), by implementing anomaly detection, which differentiates benign data packets from malicious ones. For an IDS to best predict anomalies, the model is trained on data that is typically pre-processed through normalization and f

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Belcher, Scott, Terri Belcher, James Grimes, Lusa Holmstrom, and Andy Souders. Does the Transit Industry Understand the Risks of Cybersecurity and are the Risks Being Appropriately Prioritized? Mineta Transportation Institute, 2025. https://doi.org/10.31979/mti.2025.2405.

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The intent of this study is to assess the readiness, resourcing, and capabilities of public transit agencies to detect, identify, be protected from, respond to, and recover from cybersecurity vulnerabilities and threats. This study is an update of the 2020 Mineta Transportation Institute (MTI) study, “Is the Transit Industry Prepared for the Cyber Revolution? Policy Recommendations to Enhance Surface Transit Cyber Preparedness.” In the previous study, the authors found that the transit industry was ill-prepared for cybersecurity attacks. Unfortunately, after four years and the development of n

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Acosta, Jaime C. From Malicious Eyes: A Method for Concise Representation of Ad-Hoc Networks and Efficient Attack Survivability Analysis. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada564943.

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Threat assessment of malicious code and external attacks. National Institute of Standards and Technology, 1992. http://dx.doi.org/10.6028/nist.ir.4939.

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