Volume 13, Issue 3 (2025)
Table of contents
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AI-Based Threat Detection in Cloud Platforms
Abstract: This research work delves into the transformative role AI has come to assume for enhanced threat detection in the cloud ecosystem. The conventional security frameworks, which form the basis for many architectures, are several steps behind actualizing the rapidly evolving cyber threat landscape, exposing critical weaknesses in the areas of accuracy, adaptability, and speed of response. Initially, the study sets forth the problems with the old-school approaches to threat detection …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 01–10 Read article
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Blockchain Enabled Security Framework: Smart Healthcare
Abstract: To explores the transformative potential of blockchain technology in managing, securing, and ensuring the integrity of Electronic Health Records (EHRs). EHRs, which store vital patient information such as medical histories, diagnoses, prescriptions, and imaging results, are essential for enhancing healthcare delivery. Conventional centralized Electronic Health Record (EHR) systems encounter issues such as susceptibility to single points of failure, security risks, and constraints in maintaining data integrity. By leveraging blockchain’s inherent …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 11–17 Read article
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Hybrid DL-ML Approach for Android Malware Detection
Abstract: The widespread growth of Android malware has become a significant mobile security threat during the past few years thus requiring the development of strong detection solutions. The primary tool applied in this research for Android malware detection consists of app permissions. The main indicator in the dataset for identifying malicious and benign applications functions through displaying application permission information. The evaluation of particular permission relationships with malware behavior leads to …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 18–25 Read article
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Network Security and Risk Technologies
Abstract: This research work delves into the dynamic domain of network security risk, providing a comprehensive analysis of corruption of data. The study explores strategic models aimed at strengthening network defenses in response to the continually changing threat environment. In the past, network security has relied on various technologies to mitigate risks, which include Firewalls, Virtual Private Networks (VPNs) and Encryption Protocols. The research scrutinizes the role of technologies such as …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 26–34 Read article
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The Evolution of Ransomware: In-Depth Analysis of Threat Development and Modern Defense Mechanisms
Abstract: Ransomware is the most severe of all cybersecurity threats the contemporary digital world is confronted with. It is a form of malware that encrypts a victim's information and requests ransom, usually in cryptocurrency, for its decryption. From its first appearance in the late 1980s, ransomware grew from simple malware into very advanced and targeted attacks that can be used to bring down entire organizations, businesses and critical infrastructure. This study …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 35–43 Read article
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Cybersecurity in a Digital World: Risks and Future Perspectives
Abstract: The field of information security offers a wide range of guidance in academic and practitioner literature. While various strategies such as deterrence, deception, detection, and reaction are explored, most research focuses on technological countermeasures to prevent security threats. This study presents the findings of a qualitative study conducted in Korea, examining how businesses utilize security techniques to safeguard their information systems. The results highlight a strong emphasis on preventive measures, …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 44–49 Read article
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A Survey on Ensemble Technique for Enhanced Cyberattack Detection
Abstract: It is now more difficult than ever to safeguard enterprises against cyberattacks due to their fast growth and growing sophistication. Stronger cyberattack detection systems are becoming more and more necessary as hostile strategies continue to evolve in order to safeguard information, preserve corporate trust, and protect sensitive data. An overview of contemporary detection techniques is given in this study, with a focus on integrating machine learning (ML) to increase efficacy. …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 50–54 Read article