Research ArticleOpen accessIn the abstractDesign and Implementation of a Smart File Cabinet System With Enhanced Security and Remote AccessAdebayo Afeez Oluwagbenga, Mustapha Favour, Adebiyi Temidayo Daniel et al.In an era increasingly defined by digital interconnectivity, the physical security of sensitive hard-copy documents remains a persistent vulnerability in organizational infrastructure. Traditional filing cabinets, relying on passive mechanical locks, lack the capability for real-time monitoring, remote access control, or active intrusion detection. This research presents the design and validation of a Smart File Cabinet (SFC) system that bridges this … …Journal of Mechatronics and Robotics, Vol. 10, Issue 1 · 25 May 2026 · 1,696 accessesView PDFCite
Research ArticleOpen accessIn the abstractSmart and Secure Anomaly Detection in IoT Using Quantum Inspired Kernel Ensemble LearningAbrar M. AlajlanThe exponential growth of the Internet of Things networks has greatly increased the attack surface for cyber threats, necessitating the use of strong and perceptive anomaly detection systems. Traditional intrusion detection systems often struggle with high false alarm rates, limited generalization, and inefficiency in processing high-dimensional heterogeneous IoT data. To address this issue, a novel Hybrid Quantum-Enhanced Kernel Ensemble Learning … …Journal of Computer Science, Vol. 22, Issue 3 · 12 Mar 2026 · 1,762 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Distillation GAN Model for Network Intrusion DetectionChandrakala C B, Sai Sreevall, Raghudathesh G PThis study presents a distillation-based Generative Adversarial Network (GAN) model designed for intrusion detection in network systems. A Teacher-Student architecture is proposed, in which a single teacher generator is utilized to train both the teacher discriminator and the student discriminator. The model was trained to identify anomalies present in network traffic intrusions by tuning the min-max loss function in GANs. … …Journal of Computer Science, Vol. 22, Issue 2 · 5 Mar 2026 · 1,549 accessesView PDFCite
Research ArticleOpen accessIn the abstractMulti-Source Cyber Intrusion Detection Using Ensemble Machine LearningTaskeen Ali Khan, Sara Abbas, Biswaranjan Senapati et al.The increased usage of digital technologies across businesses has led to an increase in cybercrime. It is difficult for existing intrusion detection systems to detect highly skilled hacking attempts; however, machine learning has been suggested as a way around these drawbacks. The purpose of this study is to evaluate how well various machine learning algorithms identify and stop cyberattacks in … …Journal of Computer Science, Vol. 21, Issue 1 · 14 Dec 2024 · 5,696 accessesView PDFCite
Research ArticleOpen accessIn the abstractCyber Security Threats and Countermeasures using Machine and Deep Learning Approaches: A SurveyManjula M, Venkatesh, Venugopal K. R.Recent advancements in e-business, e-healthcare, e-governance, and online digital transactions have brought valuable benefits. Unfortunately, it raises severe cyber-attacks. Cyberattacks disrupt normal operations, try to retrieve confidential information and defense secrets, and subvert the nation’s defense systems and Internet-connected devices. Cyber security solutions are required to detect, analyze, defend against threats and protect sensitive data from unauthorized access. This study … …Journal of Computer Science, Vol. 19, Issue 1 · 4 Jan 2023 · 9,370 accessesView PDFCite
Research ArticleOpen accessIn the abstractData Analytics for the Cyber Security of an Information System Based on a Markov Decision Process ModelLidong Wang, Randy Jones, Terril C. FallsIntrusion detection is an important research topic in information systems and cyber security. Both a defender and an attacker detect and learn about each other during an intrusion process. The defender can expel the attacker as soon as the attacker is detected or wait and observe to know more about the attacker for the detection and prevention of other attacks … …American Journal of Engineering and Applied Sciences, Vol. 15, Issue 4 · 7 Dec 2022 · 5,431 accessesView PDFCite
Literature ReviewOpen accessIn the abstractObject Tracking in Wireless Sensor Networks: Challenges and SolutionsShereen Ismail, Eman Alkhader, Said ElnaffarWireless Sensor Networks (WSNs) are small, inexpensive and battery-operated sensor nodes that are deployed over a geographical area. WSNs are used in many applications such border patrolling, military intrusion detection, wildlife animal monitoring, surveillance of natural disasters and healthcare systems. Mobile object tracking is a vital task in all these applications. The goal of this work is to highlight the … …Journal of Computer Science, Vol. 12, Issue 4 · 1 May 2016 · 7,777 accessesView PDFCite
Research ArticleOpen accessIn the abstractMULTI SCALE TIME SERIES PREDICTION FOR INTRUSION DETECTIONG. Palanivel, K. DuraiswamyWe propose an anomaly-based network intrusion detection system, which analyzes traffic features to detect anomalies. The proposed system can be used both in online as well as off-line mode for detecting deviations from the expected behavior. Although our approach uses network packet or flow data, it is general enough to be adaptable for use with any other network variable, which … …American Journal of Applied Sciences, Vol. 11, Issue 8 · 27 Jun 2014 · 6,776 accessesView PDFCite
Research ArticleOpen accessIn the abstractREVIEW CLUSTERING MECHANISMS OF DISTRIBUTED DENIAL OF SERVICE ATTACKSWesam Bhaya, Mehdi Ebady ManaaDistributed Denial of Service attacks (DDoS) overwhelm network resources with useless or harmful packets and prevent normal users from accessing these network resources. These attacks jeopardize the confidentiality, privacy and integrity of information on the internet. Since it is very difficult to set any predefined rules to correctly identify genuine network traffic, an anomaly-based Intrusion Detection System (IDS) for network … …Journal of Computer Science, Vol. 10, Issue 10 · 26 Jun 2014 · 7,635 accessesView PDFCite