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31 articles for “Intrusion”
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Network Intrusion Detection Using Wireshark and Machine Learning
Abstract: The growth of networked devices has highlighted the desire for advanced intrusion detection (IDS) tools to protect digital systems from evolving cyber threats. Traditional IDS systems are often difficult to adapt to the threat environment because they rely on predefined signature lists. This study presents a new approach that combines Wireshark, a widely used network packet analysis tool, with advanced machine learning for intrusion detection. Our system leverages Wireshark's data …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 10, Issue 1, 2024 · pp. 23–31 Read article
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Decision Trees in Intrusion Detection: A Comparative Analysis of Machine Learning Techniques
Abstract: Recent malware sophistication poses immense challenges in intrusion detection systems, making it imperative to develop highly sophisticated methodologies for detection of fast-evolving cyber threats. Traditional IDS typically employs a signature-based detection approach and has limitations in identifying unknown and obfuscated attacks, particularly zero-day vulnerabilities. This paper discusses the existing limitations of IDS based on ML techniques to further improve the detection capability of such systems. Machine learning algorithms, particularly decision …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 11, Issue 1, 2025 Read article
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Review of Anomaly Detection Techniques in MANETs: AMachine Learning Approach to Intrusion Detection, Attack Prediction, and Routing Security
Abstract: Mobile Ad hoc Networks (MANETs) are decentralized, self-organizing networks that offer flexibility and scalability for a variety of applications. However, their dynamic topology and limited resources make them highly susceptible to security threats. Traditional security measures often struggle to address the complexities of evolving and sophisticated attacks within such networks. This paper reviews the role of machine learning (ML) techniques in enhancing anomaly detection capabilities in MANETs, focusing on their …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 2, 2026 · pp. 1–5 Read article
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Decision Trees in Intrusion Detection: A Comparative Analysis of Machine Learning Techniques
Abstract: Recent malware sophistication poses immense challenges in intrusion detection systems, making it imperative to develop highly sophisticated methodologies for detection of fast-evolving cyber threats. Traditional IDS typically employs a signature-based detection approach and has limitations in identifying unknown and obfuscated attacks, particularly zero-day vulnerabilities. This paper discusses the existing limitations of IDS based on ML techniques to further improve the detection capability of such systems. Machine learning algorithms, particularly decision …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 11, Issue 1, 2025 Read article
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Intrusion Detection System Using Gated Recurrent Neural Network
Abstract: In the realm of cybersecurity, the constant evolution of threats demands sophisticated intrusion detection systems (IDSs) capable of discerning intricate patterns in network traffic. This study proposes an IDS leveraging the capabilities of gated recurrent neural networks (GRNNs) to enhance the detection of anomalies and potential security breaches. The GRNN architecture, employing mechanisms like long short-term memory (LSTM) and gated recurrent unit (GRU), demonstrates efficacy in capturing long-range dependencies within …
Published in International Journal of Software Computing and Testing · Vol. 10, Issue 1, 2024 · pp. 1–8 Read article
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Bot Defender: A Collaborative Defense Framework for Botnet Intrusion Mitigation
Abstract: Botnet attacks represent a significant threat to cybersecurity, compromising vast numbers of devices and causing extensive harm. BOT DEFENDER is a novel collaborative defense framework designed to mitigate botnet intrusions effectively. This framework leverages the power of collective intelligence, integrating data from multiple sources to detect and respond to botnet threats in real-time. By utilizing advanced machine learning algorithms, BOT DEFENDER can identify anomalous network behavior indicative of botnet activities, …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 2, 2026 · pp. 6–11 Read article
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A LITERATURE REVIEW OF INTELLIGENCE INTRUSION DETECTION PREVENTION TECHNIQUES FOR UNKNOWN MALWARE FINDING
Abstract: Intrusion detection system (IDS) has played a vital role as a device to guard our networks from unknown malware attacks. However, since it still suffers from detecting an unknown attack, the ultimate challenge in intrusion detection field is how we can precisely identify such an attack. For identifying known malware various tools are available but that does not detect Unknown malware exactly. It will vary according to connectivity and using …
Published in International Journal of Digital Communication and Analog Signals · Vol. 1, Issue 2, 2015 · pp. 1–8 Read article
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Evaluation with Wave Propagation Launch Vehicles besides Non-Intrusive Transmission Lines Failure Detection.
Abstract: The whole paper presents a principle of non-intrusive real-time network failure tracking utilizing wireless sensor networks. The core components of the detector are known as energy harvesters, waveforms and algorithms, circuits and components, and surface wave launchers. In this we have discussed a compact energy harvesting system that is capable of non-intrusively extracting power from a power cable. In terms of waveforms and algorithms, we suggest the usage of TDR …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 6, Issue 2, 2020 · pp. 12–21 Read article
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Functioning of Intelligent Intrusion Detection and Prevention System (IIDPS)
Abstract: In this paper, the architecture of Intelligent Intrusion Detection and Prevention System is proposed. The intelligence element was introduced using Artificial intelligence techniques. The development of IIDPS was done as a protection from cyber-attacks. The TSAM is decision maker agent and PMM is the main controller agent. Although, the proposed system is a combination of different types of intelligent agents, hybrid architecture under real time constraints.
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 1, Issue 1, 2016 · pp. 27–38 Read article
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SUSTAINABLE ENERGY METER FOR NON- ESSENTIAL LOADS
Abstract: The growing demand for accurate, cost-effective, and sustainable energy monitoring solutions has accelerated advancements in smart metering, non-intrusive load monitoring (NILM), and real-time consumption analysis. This research paper consolidates and extends insights from recent developments in energy metering technologies, focusing on battery-free sensing, IoT- enabled monitoring, life-cycle sustainability, and meter performance under distorted grid conditions. Building upon prior work on non-intrusive and adaptive load monitoring, this study proposes an integrated …
Published in International Journal of Digital Communication and Analog Signals · Vol. 12, Issue 1, 2026 · pp. 21–30 Read article
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Cost-Effective Smart Surveillance Using ESP32 and Cloud Connectivity
Abstract: The world is expanding quickly, which has led to an increase in attacks and burglaries. As a result, having a trustworthy and efficient surveillance security system is now essential to meeting all security requirements and improving the quality of human life. Computers and CCTV cameras are used in the current security systems. Along with requiring a lot of memory due to continuous recording and the labor-intensive nature of detecting unauthorized …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 10, Issue 1, 2024 · pp. 1–9 Read article
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The Use of Factor and Cluster Analysis to Interpret Groundwater Chemistry in Ga East Municipality, Ghana, West Africa.
Abstract: Groundwater chemistry was interpreted in this studies to ascertain the groundwater controlling parameters within the vicinity of Ga East Municipality, Ghana. 37 data points from various Boreholes were analyzed using factor and cluster analysis. The studies have revealed that groundwater in areas of Ga East is controlled by seawater intrusions, anthropogenic activities and carbonate mineral dissociation according to the results obtained from factor analysis. Three cluster groups were developed which …
Published in International Journal of Analytical and Applied Chemistry · Vol. 5, Issue 2, 2019 · pp. 34–43 Read article
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The Foundations and Principles of Computational Intelligence
Abstract: Artificial intelligence (AI) assumes a driving part in security administrations. A dynamic model Intelligent Intrusion Detection System (IIDS), in view of particular AI approach for intrusion detection. The strategies that are being explored incorporate neural networks and fuzzy logic with network profiling that uses basic data mining procedures to handle the network data. Suspicious interruptions can be followed back to its unique source way and any traffic from that specific …
Published in International Journal of Analog Integrated Circuits · Vol. 1, Issue 2, 2015 · pp. 17–33 Read article
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OODA Principles for Finding Unknown Malware
Abstract: This paper is planned to give a model to "OODA Principles for Finding Unknown Malware", it portrays the state's general necessities with respect to the securing and execution of intrusion prevention and detection systems with intelligence (IIPS/IIDS). This is intended to give a more profound comprehension of interruption aversion and recognition standards with knowledge may be in charge of getting, actualizing or checking such frameworks in comprehension the innovation and …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 1, Issue 2, 2015 · pp. 1–12 Read article
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CyberSentinel: A Proposed Hybrid AI Framework for Real-Time Cyber Threat Intelligence
Abstract: Modern cyberattacks have grown far more sophisticated, frequent, and fast-moving than the signature-based intrusion detection systems many organizations still rely on. This paper proposes CyberSentinel, a hybrid artificial intelligence framework for real-time cyber threat intelligence (CTI) that combines three complementary techniques into a single detection pipeline: a Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) module for network traffic anomaly detection, a Random Forest ensemble for structured log classification, and a transformer-based …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 2, 2026 Read article
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Integrated Telecommunication Systems: Networking,Security, and Emerging Technologies inNext-Generation Communication Networks
Abstract: Integrated telecommunication systems play a crucial role in enabling reliable, high-speed, and scalablecommunication across modern digital infrastructures. This paper presents a comprehensive review ofintegrated telecommunication systems with a focus on networking architectures, security mechanisms,and emerging technologies in next-generation communication networks. It examines the fundamentalcomponents of communication systems, including transmission media, communication channels, andstandardized networking protocols, highlighting their contribution to efficient data exchange andsystem interoperability. The study explores both wired and …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 1, 2026 · pp. 36–45 Read article
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A Study on Securing the Local Area Network with the Immutable Trust of Blockchain
Abstract: The contemporary Local Area Network (LAN) is the digital circulatory system of the modern enterprise, a vital yet perilously vulnerable ecosystem. Traditional security paradigms, built upon centralized authority models – firewalls, intrusion detection systems, and privileged administrators – increasingly resemble medieval castles in an age of artillery. They present a brittle single point of failure: compromise the center, and the entire kingdom falls. This paper proposes a radical architectural shift, …
Published in International Journal of Distributed Computing and Technology · Vol. 12, Issue 1, 2026 · pp. 24–35 Read article
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A Study on Sensors in Metallurgy Applications
Abstract: The relentless pursuit of efficiency, quality, and sustainability within the metallurgical industry hinges on unprecedented control over its often extreme and dynamic processes. This control is progressively realized through the strategic deployment of advanced sensor technologies. This paper explores the pivotal role of sensors in modern metallurgy, spanning from the raw material stage to the final product. It highlights how sensors, by providing real-time, accurate, and often non-intrusive data, are …
Published in International Journal of Metallurgy and Alloys · Vol. 11, Issue 2, 2025 · pp. 14–26 Read article
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Cloud Security Using Machine Learning: A Study
Abstract: The rapid adoption of cloud computing has revolutionized IT infrastructure, offering unprecedented scalability, flexibility, and cost efficiency. However, this paradigm shift introduces a new spectrum of sophisticated security challenges that traditional, signature-based security mechanisms often struggle to address effectively given the dynamic, multi-tenant, and distributed nature of cloud environments. This paper explores the critical role of Machine Learning (ML) as a potent paradigm for strengthening cloud infrastructure. ML emerges as …
Published in International Journal of Distributed Computing and Technology · Vol. 11, Issue 2, 2025 · pp. 21–30 Read article
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Fog Computing Architecture and Deployment in IoT
Abstract: The relentless proliferation of Internet of Things maneuvers generates colossal volumes of data at the network edge, straining traditional cloud-centric paradigms with inherent limitations in latency, bandwidth, resilience, and privacy. This necessitates a paradigm shift towards distributed intelligence. Fog Computing arises as a pivotal architectural paradigm, extending computational, storage, and networking capabilities closer to the data source, thereby mitigating latency, reducing bandwidth consumption, and enhancing real-time processing capabilities for critical …
Published in International Journal of Distributed Computing and Technology · Vol. 11, Issue 2, 2025 · pp. 31–39 Read article