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Journal articles on the topic 'Adaptive Network Security'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Jesudoss, Sofiya, Auxeeliya Jesudoss, and Ashraph Sulaiman. "An Adaptive Approach to Improve the Accuracy of Packet Pre-Filtering." Advanced Materials Research 367 (October 2011): 241–48. http://dx.doi.org/10.4028/www.scientific.net/amr.367.241.

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The current day networks are under deliberate, continuous and premeditated attacks such as Hacker attacks, DoS attacks, IP Address Spoofing, Phishing, Sniffer attacks etc. The Network Intrusion Detection Systems (NIDS) proved to be reliable in parrying most of the issues and challenges faced by the corporate network security systems. But, the NID systems fall short in providing a completely fool-proof network security environment. False negatives and false positives proved to be considerable bottle necks in securing the networks from the attacks. This paper deals with the introduction of a sof

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2

Khan, Mohammad Tanveer. "MULTI LAYER ADAPTIVE NETWORK SECURITY APPROACH." International Journal of Advanced Research in Computer Science 9, no. 1 (2018): 75–78. http://dx.doi.org/10.26483/ijarcs.v9i1.5231.

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Alanazi, Meshari Huwaytim. "G-GANS for Adaptive Learning in Dynamic Network Slices." Engineering, Technology & Applied Science Research 14, no. 3 (2024): 14327–41. http://dx.doi.org/10.48084/etasr.7046.

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This paper introduces a novel approach to improve security in dynamic network slices for 5G networks using Graph-based Generative Adversarial Networks (G-GAN). Given the rapidly evolving and adaptable nature of 5G network slices, traditional security mechanisms often fall short in providing real-time, efficient, and scalable defense mechanisms. To address this gap, this study proposes the use of G-GAN, which combines the strengths of Generative Adversarial Networks (GANs) and Graph Neural Networks (GNNs) for adaptive learning and anomaly detection in dynamic network environments. The proposed

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Liu, Xiao Wu, Hui Qiang Wang, Bao Xiang Cao, and Ji Guo Yu. "Network Security Situation Awareness Adaptive Control Model Based on Cognitive Network." Applied Mechanics and Materials 26-28 (June 2010): 952–55. http://dx.doi.org/10.4028/www.scientific.net/amm.26-28.952.

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Network Security Situation Awareness (NSSA) helps security analysts to be aware of the actual security situation of their networks. But its adaptive control model and method remain a new research field that needs to be explored. In this paper, we presented a novel NSSA adaptive control model based on cognitive network. The model adopted circle cognitive structure composed of Monitor, Awareness, Decision and Execution (MADE). In the MADE cognitive circle, we described a fusion awareness method based on PSO-DS theory. The decision and execution strategies were also discussed briefly. The experim

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Huang, Chang Wei, and Jin Quan Xiong. "Study of Campus Network Security Based on Dynamic Self-Adaptive Network Security Model." Advanced Materials Research 846-847 (November 2013): 1784–88. http://dx.doi.org/10.4028/www.scientific.net/amr.846-847.1784.

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Taking dynamic self-adaptive network security model system of the whole network as theoretical guidance, this thesis analyzes security risks faced by campus network completely and in full detail, combining with the network system features. The current mainstream of network security technologies such as firewalls, intrusion detection,VPN, certification, and others are carefully studied to illustrate security technologies which shall be focused for the campus network security. Then, taking the Jiangxi Science and Technology Normal University campus network as an example, the specific characteris

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Sharma, Jitender, Sonia, Karan Kumar, Pankaj Jain, Raed H. C. Alfilh, and Hussein Alkattan. "Enhancing Intrusion Detection Systems with Adaptive Neuro-Fuzzy Inference Systems." Mesopotamian Journal of CyberSecurity 5, no. 1 (2025): 1–10. https://doi.org/10.58496/mjcs/2025/001.

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Network security has become increasingly critical in recent years. Among the various aspects of network security and considering several approaches to network security, intrusion detection systems (IDSs) have gained considerable attention. The prominence of this factor, among other factors of network security, is due to its ability to address the complex and uncertain nature of security breaches. Whenever data flow over the network, precise categorization of normal and malicious data is necessary. Past IDS systems lack precise categorization. Thus, the present study focuses on the use of the a

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Ram, M. Sethu, and R. Anandan. "Enhanced Adaptive Security Algorithm (EASA) for optimized performance in smart city networks." Journal of Autonomous Intelligence 7, no. 5 (2024): 1372. http://dx.doi.org/10.32629/jai.v7i5.1372.

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<p>The Enhanced Adaptive Security Algorithm (EASA) is crafted to bolster the robustness of smart city network security, specifically targeting the dynamic and complex nature of these networks. Its primary objective revolves around enhancing the adaptability of network security, focusing particularly on traffic management applications within smart cities. EASA emerges from the foundation of the Adaptive Multi-Layer Security Framework (AMLSF), integrating advanced deep learning techniques and leveraging optimized encryption for a more adaptive and efficient solution. In addressing the limi

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C. Deepika. "Systematic Literature Review on VPN Security: Adaptive Multi-Tunnelling as a Mitigation Strategy." Journal of Information Systems Engineering and Management 10, no. 39s (2025): 760–77. https://doi.org/10.52783/jisem.v10i39s.7296.

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In recent years, virtual private network provides a private and secure network architecture for individuals and organizations by using with the support from Internet. VPN helps in safe data transmissions without the need for dedicated physical connections, allowing to creation of a secure communicational channel between remote users, sites, and corporate offices. The proposed research focused on exploring a systematic literature review on VPN security concerning adaptive multi-tunnelling as a mitigation strategy. The systematic review adopted PRISMA framework to minimizing bias and ensuring th

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Xiang, Ming, William Liu, Quan Bai, and Adnan Al-Anbuky. "The critical role of structural hole in forming trust for Securing Wireless Sensor Networks." International Journal of Information, Communication Technology and Applications 2, no. 1 (2016): 66–84. http://dx.doi.org/10.17972/ijicta20162127.

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The security issues in wireless sensor networks (WSNs) are crucial and the limitation of computing resources and distributed properties of WSN make the traditional security mechanisms no longer feasible in protecting WSN as in the wired networks. There is an emerging research area i.e., trust and reputation mechanisms, has been developed, as an alternative solution to tackle the security issues in WSNs. While the recent studies on trust are mainly focusing on the trust modelling so as to effectively detect and avoid malicious activities. In this paper, we propose to use adaptive network approa

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10

Wang, Yu Lin, and Jin Heng Wang. "Research on Security Technology of Campus Network." Advanced Materials Research 971-973 (June 2014): 1730–34. http://dx.doi.org/10.4028/www.scientific.net/amr.971-973.1730.

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Campus networks are education, research and service with network of operation properties, due to network with connection of diversity，uneven distribution terminal, openness, interconnection, borderless, Freedom and so on, Causes the network vulnerable to attacks by hackers and viruses, and caused a great damage to society, schools. In this paper, Base on network security system dynamic APPDRR model for the theoretical guidance，combined with the characteristics of network system, a brief analysis of campus network security risk. And And the current mainstream network security technology were re

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Ahmad, Malik Basit, and Parul Agarwal. "Viability of Adaptive Network Security Exercising Tradeoff between Performance and Security." Recent Advances in Computer Science and Communications 13, no. 5 (2020): 893–900. http://dx.doi.org/10.2174/2213275912666190628100621.

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Background: The client-server operations involving the financial transactions are liable to be carried in secure and controlled environment which is provided by Secure Socket Layer protocol in order to vanquish possibility of threats and attacks. In this protocol, the handshake mechanism plays an imperative role, negotiating security policy between client and server. The consolidated security policy between the communicating parties depends upon the level of threat or an attack at an instance subject to change. Objective: Transformation of Secure Socket Layer protocol into the Adaptive model w

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RAHMAN, Md Torikur, Mohammad ALAUDDIN, Uttam Kumar DEY, and Dr A. H. M. Saifullah SADI. "ADAPTIVE SECURE AND EFFICIENT ROUTING PROTOCOL FOR ENHANCE THE PERFORMANCE OF MOBILE AD HOC NETWORK." Applied Computer Science 19, no. 3 (2023): 133–59. http://dx.doi.org/10.35784/acs-2023-29.

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Nowadays Mobile Ad Hoc Network (MANET) is an emerging area of research to provide various communication services to end users. Mobile Ad Hoc Networks (MANETs) are self-organizing wireless networks where nodes communicate with each other without a fixed infrastructure. Due to their unique characteristics, such as mobility, autonomy, and ad hoc connectivity, MANETs have become increasingly popular in various applications, including military, emergency response, and disaster management. However, the lack of infrastructure and dynamic topology of MANETs pose significant challenges to designing a s

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Fan, Kai Qi. "Research on Dynamic Self-Adaptive Network Security Model Based on Mobile Agent." Applied Mechanics and Materials 644-650 (September 2014): 2996–99. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.2996.

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The rapid development and wide application of computer network is a new challenge to information security and network security. Traditional security models and single security technology can not keep up with the change of complex network structure and alterable intrusion measure. Based on analysis of some classical security models and technologies, we think network security is a kind of dynamic security. So, this paper presents a dynamic self-adaptive network security model based on mobile agent, and emphases on its structure, control strategy and prototype implementation.

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Yang, Hongyu, Le Zhang, Xugao Zhang, and Jiyong Zhang. "An Adaptive IoT Network Security Situation Prediction Model." Mobile Networks and Applications 27, no. 1 (2021): 371–81. http://dx.doi.org/10.1007/s11036-021-01837-y.

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15

El-Hajj, Mohammed. "Enhancing Communication Networks in the New Era with Artificial Intelligence: Techniques, Applications, and Future Directions." Network 5, no. 1 (2025): 1. https://doi.org/10.3390/network5010001.

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Artificial intelligence (AI) transforms communication networks by enabling more efficient data management, enhanced security, and optimized performance across diverse environments, from dense urban 5G/6G networks to expansive IoT and cloud-based systems. Motivated by the increasing need for reliable, high-speed, and secure connectivity, this study explores key AI applications, including traffic prediction, load balancing, intrusion detection, and self-organizing network capabilities. Through detailed case studies, I illustrate AI’s effectiveness in managing bandwidth in high-density urban netw

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Sharma, Ankita, and Vibhu Sharma. "APPLICATION OF GAME THEORY IN HIERARCHICAL NETWORK SECURITY." International Research Journal of Computer Science 08, no. 08 (2021): 221–26. http://dx.doi.org/10.26562/irjcs.2021.v0808.012.

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Such hierarchical network structures, omnipresent in modern organizations, give rise to particular security challenges. In this paper, we study the application of game theory to model an attacker-defender game in these layered networks. In such models, aiming at optimal resource allocation, threat prediction, and adaptive defense, we discuss game theoretic models of Stackelberg, Bayesian, and Signalling games among others. A survey of recent literature on hierarchical network security demonstrates both strengths and limitations of these models.

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Aslam, Muhammad, Dengpan Ye, Aqil Tariq, et al. "Adaptive Machine Learning Based Distributed Denial-of-Services Attacks Detection and Mitigation System for SDN-Enabled IoT." Sensors 22, no. 7 (2022): 2697. http://dx.doi.org/10.3390/s22072697.

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The development of smart network infrastructure of the Internet of Things (IoT) faces the immense threat of sophisticated Distributed Denial-of-Services (DDoS) security attacks. The existing network security solutions of enterprise networks are significantly expensive and unscalable for IoT. The integration of recently developed Software Defined Networking (SDN) reduces a significant amount of computational overhead for IoT network devices and enables additional security measurements. At the prelude stage of SDN-enabled IoT network infrastructure, the sampling based security approach currently

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Shahriyar, R. "ZERO TRUST ARCHITECTURE IN CORPORATE NETWORKS: A COMPARATIVE ANALYSIS OF IMPLEMENTATION STRATEGIES." Scientific heritage, no. 157 (March 25, 2025): 92–94. https://doi.org/10.5281/zenodo.15085558.

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As digital transformation accelerates, traditional perimeter-based security models have become increasingly ineffective in addressing modern cybersecurity threats. Zero Trust Architecture (ZTA), guided by the principle of "Never Trust, Always Verify," offers a new approach to network security that emphasizes continuous verification, identity-based access controls, and micro-segmentation. Unlike Virtual Private Networks (VPNs), ZTA provides granular and adaptive access to applications and data, reducing the risk of unauthorized access. Despite its growing popularity, organizations remain hesita

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Aziz, Ahmed, and Sanjar Mirzaliev. "Optimizing Intrusion Detection Mechanisms for IoT Network Security." Journal of Cybersecurity and Information Management 13, no. 1 (2024): 60–68. http://dx.doi.org/10.54216/jcim.130106.

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The ubiquity of interconnected devices within the Internet of Things (IoT) paradigm has revolutionized modern connectivity, simultaneously amplifying the susceptibility of networks to diverse security threats. This study addresses the pressing necessity for robust intrusion detection mechanisms tailored for IoT networks. Utilizing a simulated dataset reflecting a spectrum of network intrusions within a military environment, the research employs sophisticated methodologies, notably harnessing Decision Tree (DT) algorithms optimized via Grey Wolf Optimization (GWO) for hyperparameter tuning. The

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Zosimov, Vyacheslav V. "Enhancing Online Search Security Through Bayesian Trust Network Implementation." Control Systems and Computers, no. 1 (301) (April 1, 2023): 65–72. http://dx.doi.org/10.15407/csc.2023.01.065.

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The article focuses on the development of an information search and protection system based on a Bayesian trust network as a measure of document relevance to the user’s query. The result is the development of search system structures and algorithms with relevance evaluation when searching the Internet, the implementation of data transmission with an adaptive database for storing decisions. If the need arises, when the goal set before the user cannot be achieved without involving additional information, the adaptive database sends a request to the search system, which in turn collects the neces

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Wang, Yan Hua, and Xiu Xu. "Marking Certification of Adaptive Probability Packet Based on Hash Function." Advanced Materials Research 468-471 (February 2012): 2002–9. http://dx.doi.org/10.4028/www.scientific.net/amr.468-471.2002.

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Denial of Service Attack is a very important security event in the current network security .Address the problem of DDoS Network Attacks ,researchers have proposed a variety of tracking programs against Denial of Service Attack .Such as IP tracking program, packet marking ,logging ,connection test ,ICMP tracking ,covering networks ,and so on .The marked storage space has been expended by the use of authentication machnism of adaptive probability packet .Increasing marks could store the hash value of the IP addresses of the head node .With the selection of the mentioned two methods above ,the q

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Liu, Ding. "Research and Application of Hybrid Adaptive Forecasting Method Based on SOA." E3S Web of Conferences 213 (2020): 02007. http://dx.doi.org/10.1051/e3sconf/202021302007.

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The current network security situation is becoming more and more severe. In order to improve the accuracy of network security situation prediction, a network security situation prediction method based on crowd search algorithm optimized BP neural network is proposed. This algorithm uses the four characteristics of egoism, altruism, pre-action and uncertain reasoning unique to the crowd search algorithm to determine the search strategy, finds the best fitness individual, obtains the optimal weights and thresholds, and then performs random initialization of the BP neural network The threshold an

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Kotenko, Igor Vitalievich, and Igor Borisovich Parashchuk. "Specific features of operational assessment of security of critical resources based on adaptive neural network filtering." Vestnik of Astrakhan State Technical University. Series: Management, computer science and informatics 2023, no. 3 (2023): 55–64. http://dx.doi.org/10.24143/2072-9502-2023-3-55-64.

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The object of research is a new methodological approach to adaptive neural network filtering as a mathematical tool for improving the accuracy and efficiency of evaluating some properties of complex technical systems. This approach is one of the options for the practical application of adaptive (hybrid) filtering methods. The analysis  of the features of this approach determining the rationality of its application for the operational assessment of the security of critical resources is carried out. The theoretical aspects of the application of a hybrid adaptive approach to the operational

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Apiecionek, Łukasz, and Matusz Biedziak. "Fuzzy Adaptive Data Packets Control Algorithm for IoT System Protection." JUCS - Journal of Universal Computer Science 26, no. (11) (2020): 1435–54. https://doi.org/10.3897/jucs.2020.076.

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One of huge problem for recent IT systems are attacks on their resources called Distributed Denial of Service attacks. Many servers which are accessible from public network were a victim of such attacks or could be in the future. Unfortunately, there is still no effective method for protecting network servers against source of the attack, while such attack could block network resources for many hours. Existing solutions for protecting networks and IoT systems are using mainly firewalls and IDS/IPS mechanisms, which is not sufficient. This article presents the method minimizing the DDoS attacks

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Kizin, V. S., and S. N. Novikov. "Improving video conference security in education." Interexpo GEO-Siberia 6 (May 18, 2022): 88–95. http://dx.doi.org/10.33764/2618-981x-2022-6-88-95.

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In article, which aims to apply communication network security to improve the transmission quality of an educational video conference, an adaptive resource allocation algorithm is used to optimize the transmission quality over the network. The application of the protocol to improve the transmission quality of a video conference can increase the transmission speed, reduce the bit error rate. The algorithm minimizes latency using ant colony optimization and clustering, which ultimately achieves the goal of reducing power consumption and improving security. In order to improve system performance,

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Zhang, Fan, Xing Ming Zhang, and Ke Song. "Design of the Security Component in Reconfigurable Network." Advanced Materials Research 718-720 (July 2013): 2120–24. http://dx.doi.org/10.4028/www.scientific.net/amr.718-720.2120.

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New threats to and requirements of security come forth endlessly while the network technology progresses continually. Security equipment has little adaptive capacity in the existing rigid network. It has bad influence on network security in Mainland China. A reconfigurable security component is designed in this paper. It can fit the coming requirements of network development in the future. A prototype of this security component is implemented and analyzed.

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P.B., Samiullah Khan, Ravi Teja Reddy G., and Selvameena R. "Detection and Localization of Adaptive Hierarchical Cyber Attacks in Active Distribution Systems." Detection and Localization of Adaptive Hierarchical Cyber Attacks in Active Distribution Systems 9, no. 2 (2024): 4. https://doi.org/10.5281/zenodo.10643084.

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As active distribution systems are widely used and complex, securing them with renewable energy can be challenging. To tackle this difficulty, a two-stage methodology is proposed in this research. Deep learning is utilized to identify even the most minor cyber-attacks in electrical waveforms, and a hierarchical localization technique is then applied to determine the attack's source. This technique uses waveform analysis in conjunction with network partitioning to precisely identify attacks. The suggested methodology provides a viable means of improving cyber security in these developing power

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Kiran, Ajmeera, Prasad Mathivanan, Miroslav Mahdal, Kanduri Sairam, Deepak Chauhan, and Vamsidhar Talasila. "Enhancing Data Security in IoT Networks with Blockchain-Based Management and Adaptive Clustering Techniques." Mathematics 11, no. 9 (2023): 2073. http://dx.doi.org/10.3390/math11092073.

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The rapid proliferation of smart devices in Internet of Things (IoT) networks has amplified the security challenges associated with device communications. To address these challenges in 5G-enabled IoT networks, this paper proposes a multi-level blockchain security architecture that simplifies implementation while bolstering network security. The architecture leverages an adaptive clustering approach based on Evolutionary Adaptive Swarm Intelligent Sparrow Search (EASISS) for efficient organization of heterogeneous IoT networks. Cluster heads (CH) are selected to manage local authentication and

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Sravani, Mrs P., K. Shiva Kumar, P. Jai Raj Sai, K. Mohan Aditya, and S. S. K. Chaitanya. "Botnet Attacks in Computer Network Security." International Journal for Research in Applied Science and Engineering Technology 13, no. 3 (2025): 1826–34. https://doi.org/10.22214/ijraset.2025.67676.

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Abstract: This paper introduces a deep learning-oriented framework for identifying and preventing botnet-caused DDoS attacks in Software-Defined Networking (SDN). Conventional security techniques experience high false alarms and slow detection because of the dynamic nature of botnet attacks. To improve this, the system utilizes Convolutional Neural Networks (CNNs) to detect anomalies in real-time and a graph theory-oriented dynamic flow management algorithm for preventing attacks. Experimental assessments with CICIDS 2017 and Bot-IoT datasets and a simulated SDN testbed (Mininet) indicate that

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Raenu, Raenu, Suhas Gupta, Shashikant Patil, Jaymeel Shah, Abhinav Mishra, and N. Gobi. "Comprehensive Analysis of Implementation and Evaluation IoT based Techniques in Networked Security Systems." Journal of Intelligent Systems and Internet of Things 13, no. 2 (2024): 35–51. http://dx.doi.org/10.54216/jisiot.130203.

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This research introduces an advanced network security methodology based on IoT, combining five innovative algorithms: Dynamic Threat Detection (DTD), Adaptive Intrusion Prevention System (AIPS), Anomaly-Based Security Metrics (ABSM), Context-Aware Firewall (CAF), and Cognitive Security Assessment (CSA). Each algorithm contributes specific functionalities, ranging from real-time threat detection and adaptive policy adjustments to anomaly quantification, contextual rule modifications, and holistic security risk assessments. The ablation study conducted on each algorithm reveals critical componen

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Wahyono, Irawan Dwi, Djoko Saryono, Khoirudin Asfani, Muhammad Ashar, and Sunarti Sunarti. "Smart Online Courses Using Computational Intelligence." International Journal of Interactive Mobile Technologies (iJIM) 14, no. 12 (2020): 29. http://dx.doi.org/10.3991/ijim.v14i12.15601.

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Computer network security has become an important issue in recent decades, the government and several international organizations have invested in professional education and training for computer network security. In addition, with the increasing incidence of computer network security crimes, the government and several organizations have taken precautions by providing training to students about computer network security. Some parties develop learning models that are suitable for students and find appropriate learning methods to produce professionals in the field of computer network security th

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Shahzad, Muhammad K., S. M. Riazul Islam, Kyung-Sup Kwak, and Lewis Nkenyereye. "AEF: Adaptive En-Route Filtering to Extend Network Lifetime in Wireless Sensor Networks." Sensors 19, no. 18 (2019): 4036. http://dx.doi.org/10.3390/s19184036.

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Static sink-based wireless sensor networks (WSNs) suffer from an energy-hole problem. This incurs as the rate of energy consumption on sensor nodes around sinks and on critical paths is considerably faster. State-of-the-art en-routing filtering schemes save energy by countering false report injection attacks. In addition to their unique limitations, these schemes generally do not examine energy awareness in underlying routing. Mostly, these security methods are based on a fixed filtering capacity, unable to respond to changes in attack intensity. Therefore, these limitations cause network part

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Majeed, Abdul, Abdullah M. Alnajim, Athar Waseem, et al. "Deep Learning-Based Symptomizing Cyber Threats Using Adaptive 5G Shared Slice Security Approaches." Future Internet 15, no. 6 (2023): 193. http://dx.doi.org/10.3390/fi15060193.

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In fifth Generation (5G) networks, protection from internal attacks, external breaches, violation of confidentiality, and misuse of network vulnerabilities is a challenging task. Various approaches, especially deep-learning (DL) prototypes, have been adopted in order to counter such challenges. For 5G network defense, DL module are recommended here in order to symptomize suspicious NetFlow data. This module behaves as a virtual network function (VNF) and is placed along a 5G network. The DL module as a cyber threat-symptomizing (CTS) unit acts as a virtual security scanner along the 5G network

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Mikryukov, A. A., A. V. Babash, and V. A. Sizov. "Classifcation of events in information security systems based on neural networks." Open Education 23, no. 1 (2019): 57–63. http://dx.doi.org/10.21686/1818-4243-2019-1-57-63.

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Purpose of the research.The aim of the study is to increase the effectiveness of information security and to enhance accuracy and promptness of the classification of security events, security incidents, and threats in information security systems. To respond to this challenge, neural network technologies were suggested as a classification tool for information security systems. These technologies allow accommodating incomplete, inaccurate and unidentified raw data, as well as utilizing previously accumulated information on security issues. To address the problem more effectively, collective met

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Sharma, Himanshu, Prabhat Kumar, and Kavita Sharma. "Recurrent Neural Network based Incremental model for Intrusion Detection System in IoT." Scalable Computing: Practice and Experience 25, no. 5 (2024): 3778–95. http://dx.doi.org/10.12694/scpe.v25i5.3004.

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The security of Internet of Things (IoT) networks has become a integral problem in view of the exponential growth of IoT devices. Intrusion detection and prevention is an approach ,used to identify, analyze, and block cyber threats to protect IoT from unauthorized access or attacks. This paper introduces an adaptive and incremental intrusion detection and prevention system based on RNNs, to the ever changing field of IoT security. IoT networks require advanced intrusion detection systems that can identify emerging threats because of their various and dynamic data sources. The complexity of IoT

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Li, Yunpeng, and Xi Li. "Research on Multi-Target Network Security Assessment with Attack Graph Expert System Model." Scientific Programming 2021 (May 7, 2021): 1–11. http://dx.doi.org/10.1155/2021/9921731.

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With the rapid development of the Internet, network attacks often occur, and network security is widely concerned. Searching for practical security risk assessment methods is a research hotspot in the field of network security. Network attack graph model is an active detection technology for the attack path. From the perspective of the attacker, it simulated the whole network attack scenario and then presented the dependency among the vulnerabilities in the target network in the way of directed graph. It is an effective tool for analyzing network vulnerability. This paper describes in detail t

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G. Sharmila. "Decentralized And Adaptive Blockchain Based Offline Payment System Using Hardhat and Ethereum." Journal of Information Systems Engineering and Management 10, no. 44s (2025): 477–87. https://doi.org/10.52783/jisem.v10i44s.8614.

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The Blockchain technology is a cutting-edge advancement in information technology. Bitcoin, as one of its initial uses, has attracted considerable attention as a cryptocurrency. Alongside Ethereum, which emphasizes blockchain-driven smart contracts, these technologies lie at the heart of modern cryptocurrency innovation. Off -chain transactions offer a scalable solution for blockchain networks, reducing congestion, lowering transaction fees, and improving processing efficiency without compromising decentralization. However, existing off-chain solutions often face security and flexibility chall

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Swapnil Chawande. "Adaptive zero trust with AI and Automation." World Journal of Advanced Engineering Technology and Sciences 13, no. 2 (2024): 751–63. https://doi.org/10.30574/wjaets.2024.13.2.0589.

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Traditional network security approaches built from perimeter-based defenses become increasingly useless because of rapidly accelerating cyber threat patterns. Modern distributed workforce operations, cloud computing infrastructure, and complex IT requirements require organizations to embrace more dynamic security frameworks. A Zero Trust Architecture framework that adapts by using Artificial Intelligence and automation practices presents astute defense solutions against these security challenges. The continuous verification of users' devices and transactions through real-time risk assessments

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Ageev, Sergey, Vladimir Karetnikov, Evgeny Ol’khovik, and Andrey Privalov. "Adaptive method of detecting traffic anomalies in high-speed multi-service communication networks." E3S Web of Conferences 157 (2020): 04027. http://dx.doi.org/10.1051/e3sconf/202015704027.

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In the paper, an adaptive hybrid heuristic (behavioral) method for detecting small traffic anomalies in high-speed multiservice communication networks, which operates in real time, is proposed and investigated. The relevance of this study is determined by the fact that network security management processes in high-speed multiservice communication networks need to be implemented in a mode close to real-time mode, as well as identifying possible network security threats in the early stages of the implementation of possible network attacks. The proposed method and algorithm belong to the class of

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Parveen Shaik, Dr Sajeeda. "Enhancing Cloud Computing Security Through Deep Learning: An Artificial Neural Network Approach." INTERNATIONAL RESEARCH JOURNAL OF ENGINEERING & APPLIED SCIENCES 9, no. 4 (2021): 34–38. http://dx.doi.org/10.55083/irjeas.2021.v09i04009.

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Cloud computing, while offering unparalleled benefits in scalability and efficiency, faces escalating security challenges in the contemporary digital landscape. This paper proposes an innovative approach to fortify cloud computing security through the integration of deep learning, with a specific focus on artificial neural networks (ANNs). By harnessing the adaptive capabilities of ANNs, the study aims to detect and mitigate evolving security threats within diverse cloud environments. The research methodology involves the meticulous selection of neural network architectures, comprehensive trai

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ASLAN, Ömer. "Ransomware Detection in Cyber Security Domain." Bitlis Eren Üniversitesi Fen Bilimleri Dergisi 11, no. 2 (2022): 509–19. http://dx.doi.org/10.17798/bitlisfen.1038966.

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In recent years, ransomware has become highly profitable cyber attacks. This is because, everyday there are several new devices attending to computer networks before testing their security strength. In addition, it is easy to launch ransomware attacks by using Ransomware-as-a-Service. This paper proposed a new method that creates the ransomware specific features by using ransomware behaviors which are performed on file, registry, and network resources. The weights are assigned to the behaviors based upon where the actions are performed. The most feasible features are selected based on the assi

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Лисенко, Сергій Миколайович. "МЕТОД ЗАБЕЗПЕЧЕННЯ РЕЗИЛЬЄНТНОСТІ КОМП’ЮТЕРНИХ СИСТЕМ В УМОВАХ КІБЕРЗАГРОЗ НА ОСНОВІ САМОАДАПТИВНОСТІ". RADIOELECTRONIC AND COMPUTER SYSTEMS, № 4 (25 грудня 2019): 4–16. http://dx.doi.org/10.32620/reks.2019.4.01.

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The dynamic expansion of cyber threats poses an urgent need for the development of new methods, methods, and systems for their detection. The subject of the study is the process of ensuring the resilience of computer systems in the presence of cyber threats. The goal is to develop a self-adaptive method for computer systems resilience in the presence of cyberattacks. Results. The article presents a self-adaptive system to ensure the resilience of corporate networks in the presence of botnets’ cyberattacks. Resilience is provided by adaptive network reconfiguration. It is carried out using secu

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Ugbaja, Unomah Success, Uloma Stella Nwabekee, Wilfred Oseremen Owobu, and Olumese Anthony Abieba. "Conceptual Framework for Role-Based Network Access Management to Minimize Unauthorized Data Exposure Across IT Environments." International Journal of Social Science Exceptional Research 2, no. 1 (2023): 211–21. https://doi.org/10.54660/ijsser.2023.2.1.211-221.

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As organizations increasingly rely on digital infrastructures, managing network access securely has become a critical challenge. Unauthorized data exposure, whether due to insider threats, privilege escalation, or third-party vulnerabilities, poses significant risks to information security. This presents a conceptual framework for role-based network access management (RBNAM) to minimize unauthorized data exposure across IT environments. The framework is built on the principles of role-based access control (RBAC) and incorporates policy-based enforcement mechanisms, continuous monitoring, and a

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Domb, Menachem, Balaji C. G., Menaka S., Gayathri A., and Sujata Joshi. "Securing 5G Networks by Mitigating Cybersecurity Risks for Transformative Applications." International Journal of Interactive Mobile Technologies (iJIM) 19, no. 11 (2025): 227–55. https://doi.org/10.3991/ijim.v19i11.54519.

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The increasing adoption of 5th generation (5G) networks introduces significant cybersecurity challenges due to the expansion of the attack surface, driven by network slicing, edge computing, and a massive number of connected devices. These challenges demand robust access control mechanisms to mitigate potential risks while maintaining network efficiency. This study presents the Secure 5G Access Control (S5GAC) protocol, a comprehensive security framework designed to enhance user and device authentication through multi-factor authentication (MFA), contextual access control, and continuous monit

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Tanriverdiyev, E. "SECURING MILITARY CYBERSPACE: A DETAILED ANALYSIS OF THREAT VECTORS AND STRATEGIC SOLUTIONS FOR BATTLEFIELD NETWORKS." Slovak international scientific journal, no. 89 (November 15, 2024): 11–13. https://doi.org/10.5281/zenodo.14167013.

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While networked information systems are becoming the backbone of military operations, the problems of network system security increase accordingly. Battlefield networks dependent on wireless communication due to mobility have opened up a vast potential for cybersecurity attacks. This paper provides a broad overview of the key cybersecurity threats facing the military battlefield network, with an emphasis on the risks contributed by wireless communication. It further covers advanced protection mechanisms, including encryption, access control, and continuous monitoring of networks. It assesses t

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Kotov, O. "METHODOLOGICAL FRAMEWORK FOR ASSESSING ENTERPRISE COMPETITIVENESS." Slovak international scientific journal, no. 89 (November 15, 2024): 14–18. https://doi.org/10.5281/zenodo.14167017.

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While networked information systems are becoming the backbone of military operations, the problems of network system security increase accordingly. Battlefield networks dependent on wireless communication due to mobility have opened up a vast potential for cybersecurity attacks. This paper provides a broad overview of the key cybersecurity threats facing the military battlefield network, with an emphasis on the risks contributed by wireless communication. It further covers advanced protection mechanisms, including encryption, access control, and continuous monitoring of networks. It assesses t

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Konika Abid. "Adaptive Random Mac Strategy for IoT Security Through Network Forensics Investigation." Journal of Electrical Systems 20, no. 7s (2024): 1740–48. http://dx.doi.org/10.52783/jes.3774.

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In the rapidly evolving landscape of digital systems and networks, ensuring robust cyber security measures is of paramount importance. This study delves into the evaluation of a proposed security method's efficiency through a comprehensive comparative analysis conducted under diverse security breach simulations. The objective is to discern the method's effectiveness in safeguarding sensitive information and maintaining system integrity.The research methodology involves the selection of representative security breach scenarios, each emulating distinct attack vectors and potential vulnerabilitie

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Yuan, Hao. "A Network Security Risk Assessment Method Based on Immunity Algorithm." Advanced Materials Research 108-111 (May 2010): 948–53. http://dx.doi.org/10.4028/www.scientific.net/amr.108-111.948.

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Based on the research of domestic and foreign vulnerability assessment systems, in this paper, we propose an improved network security assessment method based on Immunity algorithm. It integrates the advantages of both host based and network based scan system. Our goal is to explore the known security vulnerabilities, and to check hosts’ security effectively as well. It has the features of self-adaptive, distributed, and real time. Therefore, it provides a good solution to risk assessment for network security.

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Rajalakshmi, N. R., Sathishkumar V. E., C. Kannika Parameshwari, Maheshwari V., and Prasanna M. "Cyber-security attack prediction using cognitive spectral clustering technique based on simulated annealing search." Applied and Computational Engineering 6, no. 1 (2023): 1368–73. http://dx.doi.org/10.54254/2755-2721/6/20230791.

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Data protection and security is a big challenging portion in a modern technical world against the cyber-attacks like; ransomware, man-in-the-middle, DDoS, etc. In order to overcome this scenario, there are lot of artificial intelligence framework have been introduced to detect and classify the cyber-attacks. In particular, neural networks, with their solid speculation execution ability, are capable to address an extensive variety of cyber-attacks. This article frames the training and testing of a neural network group such a way to deal with detection of cyber-attack using cognitive spectral cl

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Asaad, Maha Salah, and Muayad Sadik Croock. "Adaptive security approach for wireless sensor network using RSA algorithm." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 1 (2021): 361. http://dx.doi.org/10.11591/ijeecs.v22.i1.pp361-368.

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A type of distributed and self-regulating network is the wireless sensor network (WSN). The sensor nodes have limited computing capabilities, memory, battery power are needed to ensure a strong security design. In this paper, an adaptive cryptographic scheme for WSN that is operating on routing ad hoc on-demand vector routing (AODV) protocol. The adaptive term refers to the adopted mechanism between heavy and light asymmetric cryptography techniques of RSA. The heavy technique adopts the complete version of RSA algorithm, while the light one considers a reduced complexity version. This is to c

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