Articles

Enhancing Network Security through Advanced Authentication and Key Management Mechanisms

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This paper introduces the SEAKS-PKMv2 protocol, a robust security mechanism aimed at addressing vulnerabilities within the PKMv2 framework, particularly focusing on mutual authentication, key management, and encryption in mobile WiMAX networks. By integrating RSA-based and EAP-based authentication methods, SEAKS-PKMv2 establishes a secure environment that mitigates risks such as replay, man-in-the-middle and interleaving attacks. The protocol adopts a distributed authentication and localized key management approach, facilitating efficient and secure network access and data transmission. Through simulation, we evaluate the SEAKS-PKMv2 protocol’s performance in terms of packet delivery ratio, overhead, processing time, and resilience against rogue relay station attacks. The findings demonstrate significant improvements in network security and efficiency, confirming the effectiveness of SEAKS-PKMv2 in enhancing the integrity and confidentiality of communications in distributed network settings.

Challenges and Solutions in Network Security for Serverless Computing

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This research study explores the challenges and solutions related to serverless computing so that the computer systems connected to the network can be protected. Serverless computing can be defined as a method of managing computer services without the need to have fixed servers. The qualitative research method is used by this research study, which does not include any numerical data and involves the examination of non-number data so that the network security challenges can be identified in detail. In the literature review, the past studies from 2019 to 2023 are reviewed to identify study gaps so that the foundation for investigating serverless network security. The literature review is based on thematic analysis, so all the data can be organized into meaningful themes. The findings of this research study include the solutions to the challenges like data privacy, insecure dependencies and limited control. The strategies to overcome these challenges include encryption, strong monitoring and other relevant strategies. This research study also suggests the use of blockchain technology and Artificial Intelligence. In short, this research study provides insights to improve serverless computing security and also guides future researchers to innovate creative solutions for developing security challenges.

A Literary Review of Pattern Matching Techniques in Network Intrusion Detection

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With the exponential growth in devices and services being added to networks, we are also witnessing an increase in the volume and complexity of threats, urging an increased efficiency in network intrusion detection systems which primarily rely on pattern matching to identify malicious activity on the network. In this literary review of pattern matching techniques in network intrusion detection, we explore the limitations and the research carried out in both signature-based and anomaly-based intrusion detection systems to overcome them. It focuses on the performance improvements in signature-based intrusion detection systems achieved through methodologies and technologies like regular expressions, Hyperscan, RE2, Flashtext, a generalized Aho-Corasick algorithm, usage of Bloom filters and payload sampling. It also covers the usage of machine learning techniques, including genetic algorithms, Support Vector Machines (SVM) and Improved Self-Adaptive Bayesian Algorithm (ISABA), which are used to detect anomalous behavior and identify potential threats in a network in anomaly-based network intrusion detection to assist the security analysts carry out their job functions. Additionally, this review explores the integration of the MITRE ATT&CK framework and Security Information and Event Management (SIEM) systems in network intrusion detection as this framework provides a structured and standardized approach for analyzing the tactics and techniques used by attackers to classify them, while SIEM systems enable the correlation of threat activity across multiple sources, allowing for a more comprehensive and accurate view of the network security. Overall, this literary review provides insights into the state-of-the-art techniques and frameworks used in Network Intrusion Detection based on Pattern Matching, highlighting the significant improvements in performance and detection capabilities.