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49 articles for “intrusion detection systems”
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Advancements in Intrusion Detection: Tackling Imbalanced Network Traffic with Machine Learning and Deep Learning Techniques
Abstract: Malicious cyberattacks can frequently hide enormous amounts of typical data in unbalanced network traffic. It is very stealthy and obfuscating in cyberspace, which makes it challenging for Network Intrusion Detection Systems (NIDS) to guarantee the precision and promptness of detection. This essay investigates. Machine learning and deep learning are utilized for intrusion detection in imbalanced network traffic. It offers a novel method for addressing the problem of class imbalance termed …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 18–24 Read article
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Cybersecurity Early Detection Algorithms for Threats
Abstract: Cybersecurity plays a vital role in protecting digital systems, networks, and data from unauthorized access, misuse, and cyberattacks in an increasingly interconnected world. As reliance on internet-based technologies continues to grow, the frequency and sophistication of cyber threats have also increased, making effective cybersecurity strategies essential. Cybersecurity encompasses a comprehensive framework that integrates technological solutions, organizational processes, and human awareness to ensure the confidentiality, integrity, and availability of information. Key …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 · pp. 31–37 Read article
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Strategies for Efficient Integration of Distributed Energy Resources into Microgrid Systems
Abstract: With the growing integration of Distributed Energy Resources into modern power systems, the global energy landscape is changing. Some of the DERs are solar photovoltaic (PV), wind turbines, battery storage systems, combined heat and power (CHP) units, and electric vehicles (EVs). Some of the advantages include lower transmission losses, better energy efficiency, and more resilience to grid failures. However, the far-reaching integration of DERs carries with it considerable technical, economic, …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 51–56 Read article
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Intrusion Eye Detector
Abstract: Uncertainty about security risks and illegal access are becoming more prevalent in a variety of settings, such as private homes, business buildings, and critical government buildings. Conventional security systems, which may not offer real-time warnings or prompt reactions, frequently rely on passive monitoring, including CCTV cameras and motion sensors. Artificial intelligence (AI) and computer vision-based intelligent systems are becoming more and more popular as a means of improving security and …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 28–32 Read article
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Cyber Security and International Relations: Navigating the Digital Battlefield
Abstract: In the interconnected world of the 21st century, the sphere of international relations extends into the digital realm, where cybersecurity has become an arena of strategic importance. This intricate interplay of technology and geopolitics has birthed a digital battlefield where state and non-state actors engage in actions ranging from espionage to sabotage, thus influencing global stability and order. The phenomenon of cybersecurity in international relations involves multiple facets, including but …
Published in Journal of Web Engineering & Technology · Vol. 11, Issue 1, 2024 · pp. 12–19 Read article
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Enhancing IoT Network Security with Hybrid Deep Learning Classifiers for DDoS Attack Detection
Abstract: The security and operational dependability of Internet of Things (IoT) networks are seriously threatened by the growing susceptibility to Distributed Denial of Service (DDoS) assaults brought about by their rapid expansion. The intricacy and dynamic character of these advanced attacks can provide a challenge to conventional intrusion detection systems. This study presents a novel method for strengthening IoT network security by combining Convolutional Neural Networks (CNNs) and Long Short-Term Memory …
Published in Journal of Web Engineering & Technology · Vol. 13, Issue 1, 2026 · pp. 23–33 Read article
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A Comparative Study of Routing Protocols and Artificial Intelligence in Manets
Abstract: Decentralized networks called Mobile Ad hoc Networks (MANETs) allow mobile nodes to dynamically connect to one another without the need for fixed infrastructure. An overview of MANETs is given in this work, along with a discussion of their features, uses, and difficulties. It explores how routing protocols, such as proactive, reactive, and hybrid protocols, are categorized in MANETs and provides examples and features for each. It also examines the performance …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 1, Issue 2, 2023 · pp. 31–38 Read article
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Blockchain-Enabled Secure Wireless Communication IoT Networks
Abstract: Cloud-native environments with their distributed environments and transient workloads raise the intrinsic problem of traditional intrusion detection and response systems to unprecedented levels. Modern cloud platforms have rapid elasticity, microservice orientation, and dynamic scaling, which usually exceed the range of centralized security services, contributing to the problem of slower threat detection and a poor ability to contain the threat. The proliferation of the Internet of Things (IoT) gadgets across different …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 10–14 Read article
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Intelligent automated railway crossing gate control system
Abstract: The high incidence of accidents at railway level crossings due to human errors and lack of proactive track monitoring is a challenge for rail safety in high-density networks. This paper proposes the development and validation of an intelligent automated railway crossing system- IARCS that leverages sensor fusion and IoT communication to eliminate human dependency and mitigate intrusion risks. The core system deploys an Arduino Uno for the purpose of primary …
Published in Journal of Microcontroller Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 20–28 Read article
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Deep Learning Meets IoT: Hybrid Approaches for Botnet Detection
Abstract: Rapid advancement in the Internet of Things (IoT) changed everything, making it possible for seamless interconnectivity of devices and altering data-driven decision processes. This study delves into the intersection of IoT with deep learning approaches and hybrid approaches for managing botnet in IoT systems, especially security, efficiency, and performance optimization. Leveraging deep learning models, for example, CNNs and RNNs, will help the network achieve more intrusion detection and data analysis. …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 1, 2025 · pp. 18–27 Read article
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Animal Intrusion Prevent System: Using YoloV8 and Raspberry Pi
Abstract: The Animal Intrusion Prevention System employs advanced YOLOv8 object detection technology to address human-wildlife conflicts, a growing concern due to human encroachment into natural habitats. Featuring a Raspberry Pi mounted on a rotating head for 360-degree surveillance, the system accurately identifies animals such as monkeys, elephants, and wild boars in real time. Upon detection, it activates non-invasive light and sound deterrents to prevent wildlife intrusions, ensuring minimal harm to animals. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 103–112 Read article
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Transforming Hospital Environments: The Role of Sound Detection
Abstract: Hospitals are sanctuaries of healing, yet they are often paradoxically exposed to a pervasive, often underestimated threat: excessive noise. While internal hospital sounds pose their own challenges, the impact of external sounds – traffic, construction, sirens, and urban clamor – can profoundly compromise patient safety, recovery, and overall well-being. This article explores the critical role of advanced sound detection systems in mitigating this external acoustic intrusion, leveraging technology to create …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 4, Issue 1, 2026 · pp. 28–40 Read article
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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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Smart Drive Assist Systems for Modern Vehicles: A Review of Current Advances and Future Directions
Abstract: Smart drive assist systems serve as advanced automotive companions, boasting three pivotal capabilities: blind spot monitoring, collision prevention, and adaptive lighting. Blind spot monitoring acts as a vigilant sentinel, overseeing areas beyond the driver's direct view and issuing alerts for potential blind spot intrusions during lane changes. Collision prevention acts as a protective shield, scanning the road ahead to notify the driver of impending collisions, affording crucial reaction time to …
Published in International Journal of Advanced Control and System Engineering · Vol. 2, Issue 2, 2024 · pp. 19–27 Read article
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Fortifying the Cloud: AI-Driven Security Paradigms and Evolving Threat Defenses in Modern Cloud Computing
Abstract: Organizations worldwide are raising their concerns about security maintenance while cloud computing expands rapidly to serve as a digital transformation foundation. The study explores modern cloud security patterns while also evaluating how artificial intelligence modifies the identification and evaluation of complex cyber threats along with their prevention methods. New security threats such as insider operations and DDoS attacks and data breaches alongside insecure APIs can be detected through machine learning …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 34–40 Read article
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Open Source Software Empowering Artificial Intelligence, Machine Learning, and Cyber Security: A Comprehensive Research Study
Abstract: Open Source Software (OSS) has become a foundational pillar for rapid innovation across Artificial Intelligence (AI), Machine Learning (ML), and Cybersecurity. This paper delivers a comprehensive, journal-length analysis of OSS-driven ecosystems, emphasizing collaborative development, transparency, and accelerated deployment. By providing freely available libraries, tools, and frameworks, OSS makes it easier for developers and researchers to experiment, build models, and deploy solutions quickly. This study examines how OSS can be combined …
Published in Journal of Open Source Developments · Vol. 13, Issue 1, 2026 Read article
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Autonomous Snake Detection and Catching System for Household Safety After Calamities
Abstract: Autonomous Snake Detection and Catching Robot for household Safety after Calamities is a robot to protect house premises from the intrusion of snakes which is a major issue specially after calamities. During floods many incidents of snake encounters and bites were reported in numerous residential areas. According to disaster management experts, the possibility of flood in Kerala still remains and it can cause major impacts in future. Conventional methods for …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 1, 2024 · pp. 1–5 Read article
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Facial Biometrics Driven Attendance Automation Solution Using LBPH Algorithm
Abstract: In today's educational landscape, managing attendance remains a central administrative task, often conducted manually on paper, consuming valuable time for educators. This project proposes a solution utilizing facial recognition technology to streamline the attendance process, thereby saving time and maintaining accurate student records. The objective is to develop an automated attendance system that is minimally intrusive, cost-effective, and highly efficient, leveraging computer vision techniques and algorithms like local binary patterns …
Published in Journal of Open Source Developments · Vol. 11, Issue 1, 2024 · pp. 27–35 Read article
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Attendance System Based on Facial Recognition
Abstract: Attendance management is a fundamental aspect of educational institutions and workplaces, ensuring accountability, discipline, and operational efficiency. Traditional methods, such as manual roll calls, RFID cards, and fingerprint scanners, are often time-consuming, error-prone, and susceptible to fraud. This research presents an automated attendance management system utilizing face recognition technology to address these challenges effectively. The proposed system employs OpenCV for real-time image processing, the face recognition library for accurate facial …
Published in International Journal of Electronics Automation · Vol. 3, Issue 1, 2025 · pp. 28–34 Read article
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Cybersecurity in Web Automation: A Machine Learning Approach to Lightweight Intrusion Detection
Abstract: Launch-Attack is a lightweight and practical threat-detection framework designed specifically for smaller web-automation environments, including setups that rely on tools such as Selenium. Rather than aiming to replace large enterprise-grade security platforms, the framework focuses on offering an accessible option for developers, testers, and researchers who need real-time monitoring without the heavy resource demands of traditional systems. The model relies on machine-learning techniques implemented through Scikit-learn, enabling it to detect …
Published in Journal of Web Engineering & Technology · Vol. 13, Issue 1, 2026 · pp. 34–40 Read article