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87 articles for “attack detection”
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The Prognostic Efficacy of Inflammatory Indicators in Determining the Cause of Multiple Sclerosis Exacerbation
Abstract: Multiple sclerosis (MS) is the most prevalent immune-mediated inflammatory disease affecting the central nervous system, presenting with diverse clinical symptoms and manifestations. This study investigates the diagnostic potential of the monocyte-to-lymphocyte ratio (MLR), red cell distribution width-to-lymphocyte ratio (RLR), and systemic immune-inflammation index (SII) in detecting MS attacks among relapsing-remitting MS (RRMS) patients seeking care in the emergency department (ED). The research focused on RRMS patients who presented to the …
Published in Research and Reviews : A Journal of Immunology · Vol. 15, Issue 1, 2025 · pp. 1–8 Read article
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Phisherman: A Phishing Email Detection Browser Extension
Abstract: Phishing attacks continue to pose significant security risks, exploiting email as a primary vector to deceive users and compromise sensitive information. To counter these threats, Phisherman presents a sophisticated, real-time phishing detection system that integrates both rule-based methods and deep learning for heightened accuracy. Built as a cross-browser extension, compatible with Chrome, Firefox, and Edge through the WebExtension API, Phisherman combines traditional verification checks, such as DNS blacklisting, SPF, DKIM, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 99–105 Read article
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IoT-based Heart Attack Prediction System Using Machine Learning
Abstract: Heart disease, particularly heart attacks, is one of the leading causes of mortality worldwide. Timely detection and prompt intervention play a vital role in significantly improving the survival rates of individuals at risk of cardiac events. Unfortunately, most traditional healthcare systems are not equipped with mechanisms for continuous, real-time monitoring of patients' cardiovascular health. This limitation makes it extremely difficult for healthcare providers to identify warning signs early enough to …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 2, 2025 · pp. 1–5 Read article
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Intelligent Polymer-Integrated Wearable Platforms for Sustainable IoT and Predictive Health Monitoring for Migraine Detection
Abstract: Migraine is a neurological disorder, and its effect on the global workforce is resultantly significant. However, the fact of the matter is the absence of notable technological breakthroughs and the fact that the technology presently available is reactive, meaning it tackles the symptoms of the attack after the attack has occurred. The requirement for this paper is, therefore, the provision of an innovative approach, and this paper will describe the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 946–960 Read article
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Detection of Phishing Website Using URL
Abstract: Phishing attacks are one of the greatest threats to online security, where fraud websites deceive users into giving out sensitive information. Traditional methods of detection, such as blacklists and heuristic-based systems, often fail in identifying newly created or sophisticated phishing websites. This study proposes an intelligent phishing website detection system using Convolutional Neural Networks (CNNs) in analyzing URLs and associated features. Using labeled URLs, the system employs such attributes such …
Published in Journal Of Network security · Vol. 13, Issue 1, 2025 · pp. 10–15 Read article
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Detection of Phished URLs Using Machine Learning
Abstract: Phishing attacks remain a significant cybersecurity challenge, requiring innovative detection strategies. This study investigates the use of machine learning to detect phishing URLs, to improve the accuracy and reliability of detection systems. Utilizing a diverse dataset of legitimate and phishing URLs we extracted the features such as lexical properties, domain-specific details, and HTML content to train various machine learning models. Algorithms including Random Forest, support vector machine (SVM), and gradient …
Published in Journal of Web Engineering & Technology · Vol. 11, Issue 3, 2024 · pp. 1–7 Read article
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Cybersecurity Innovations in Industrial Control Systems
Abstract: Industrial control systems (ICS) are essential for automating and managing industrial processes across a broad spectrum of sectors, including energy, manufacturing, transportation, and water treatment. Securing these systems is essential to avoid disruptions that could lead to significant economic losses and safety risks. Recent advancements in ICS cybersecurity encompass several key areas that collectively aim to bolster the security and reliability of these critical infrastructures, thereby enhancing industrial safety. Enhanced …
Published in Journal of Industrial Safety Engineering · Vol. 11, Issue 2, 2024 · pp. 15–19 Read article
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AI-Based Cybersecurity Framework for Protecting Smart Surveillance Infrastructure in Mumbai
Abstract: Smart city infrastructures increasingly rely on interconnected surveillance systems to ensure safety, operational efficiency, and public trust. However, the rapid expansion of IoT-based monitoring technologies has introduced new cyber risks, especially in high-density metropolitan areas. This paper proposes an AI-driven cyber resilience framework targeting smart surveillance infrastructure as a critical smart-living domain, focusing on Mumbai as a case study. Using the CIC-IDS2017 dataset, a machine learning-based intrusion detection model is …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 Read article
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Leveraging Standards and Deep Learning Approaches to Secure Internet of Things (IoT) Devices from Cyber Attack
Abstract: The widespread adoption of Internet of Things (IoT) devices between 2019 and 2024 has significantly grows in various sectors in Japan, including healthcare, manufacturing, and the development of smart cities. Although this growth offers many advantages, it also makes these devices more vulnerable to cyber threats. High-profile security breaches in Japan have sparked discussions about the requirement for enhanced security measures to protect the rapidly evolving IoT technologies. This study …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 Read article
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Exploring the Role of Advanced Shell Scripts for Malware Threat Detection
Abstract: This study investigates the application of advanced shell scripts in detecting malware threats within computer systems. As cyber-attacks become more sophisticated, traditional detection methods frequently prove inadequate, highlighting the need for innovative approaches. The research highlights the effectiveness of shell scripting in automating the monitoring and analysis of system behavior, file integrity, and network traffic. By leveraging patterns and signatures of known malware, the scripts can identify anomalies indicative of …
Published in Journal of Advances in Shell Programming · Vol. 11, Issue 3, 2024 · pp. 6–16 Read article
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A Review of AI-Based Intrusion Detection Systems for Mobile Ad Hoc Networks (MANETs)
Abstract: Mobile Ad Hoc Networks (MANETs) comprise wireless networks that lack any conventional infrastructure . Their chief features include highly changing network topologies, lack of centralized administration, and open nature of communication, which collectively result in making MANETs of the wireless kind very susceptible to a diverse range of cyber-attacks like blackhole, greyhole, wormhole, flooding, Sybil and denial-of-service (DoS) among others. Conventionally, Intrusion Detection Systems (IDS) relying on static rule-based methods …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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IT Security and Intrusion Detection Systems: An Introduction
Abstract: This article deals with the current status of IT security in an industrialized country and one of the many approaches. The emphasis is on what are known as intrusion detection systems. These enable users to detect suspicious behavior and attacks in daily IT operations by analyzing data, resources, and network flows. Based on previous research, the different variants, available detection types, and their working methods are briefly explained and presented. …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 10–17 Read article
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Gatividhi Guard: The Activity Guardian—Revolutionizing Security Information and Event Management (SIEM) Technology
Abstract: In the dynamic landscape of cybersecurity, organizations confront increasingly intricate cyber threats that necessitate sophisticated security measures. Conventional systems such as Security Information and Event Management (SIEM) systems face ongoing challenges, they often struggle to effectively detect and mitigate sophisticated attacks within extensive data sets. To address these limitations, the introduction of Gatividhi Guard signifies a paradigm shift in SIEM technology. Gatividhi Guard is an innovative SIEM platform leveraging advanced …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 1, 2024 · pp. 29–44 Read article
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A Security Investigation Survey of Ransomware Detection and Avoidance Strategies for IoT Networks
Abstract: The internet of things (IoT) refers to the interconnection of a large number of distinct physical objects, which in turn makes possible a variety of services and applications. Because the IoT sector is developing at such a rapid rate, ensuring its safety ought to be a high concern. At this time, ransomware attacks constitute the biggest danger to IoT posed by cyberattacks. Ransomware is software that blocks access to or …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 2, 2023 · pp. 14–23 Read article
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Detection of Phishing Website URLs and Email/SMS Using Random Forest and Multinomial Naive Bayes
Abstract: Currently, phishing attacks via SMS/email and URL have become significant threat to cybersecurity, posing risks to both individuals and organizations alike. Phishing attacks typically involve the creation of fraudulent websites or the dissemination of deceptive emails and SMS messages to trick users into disclosing sensitive information such as passwords, credit card numbers or personal details. To respond to these attacks, we develop a robust system for the detection of phishing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 22–30 Read article
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Artificial Intelligence in Cybersecurity: Emerging Trends, Technological Advancements, and Future Directions for Cyber Defense
Abstract: Artificial Intelligence (AI) is revolutionizing the field of cybersecurity by automating complex security tasks, improving threat detection capabilities, and enhancing the precision of threat response mechanisms. With the rapid evolution of cyber threats such as malware, ransomware, phishing, and data breaches, conventional security systems are often insufficient to provide timely and accurate protection. AI, powered by machine learning algorithms and neural networks, enables the analysis of vast datasets to detect …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 103–112 Read article
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Threat Detection on Linux Systems Using OSquery
Abstract: We have made an EDR tool for Linux Systems using Facebook open-source project OSquery. Making our own EDR tool rather than using a commercial EDR tool helps us gain knowledge about the platform and the security aspect of the platform and gives us the capabilities to detect and investigate security events. In our method, we are collecting the logs on the central server and then we are using these logs …
Published in Journal of Advances in Shell Programming Read article
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The Evolution of Bio Crypt Keys: From Concept to Implementation
Abstract: With the rapid increase in data exfiltration due to cyber-attacks, Covert Timing Channels (CTCs) have emerged as a significant and sophisticated network security threat. These channels exploit inter-arrival times of data packets to exfiltrate sensitive information from targeted networks. Detecting CTCs increasingly relies on machine learning techniques, which use statistical metrics to differentiate between malicious (covert) and legitimate (overt) traffic flows. However, as cyber-attacks become more adept at evading detection …
Published in Journal of Control & Instrumentation · Vol. 15, Issue 2, 2024 · pp. 38–45 Read article
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Comparative Study of Facial Spoofing Detection using CNN Architecture
Abstract: Facial recognition systems face a high risk of security breach due to various facial spoofing attacks. This challenge was addressed by the study of several deep learning models. This study proposes an idea to detect facial spoofing using deep learning architecture to differentiate live faces form various types of spoofed images/videos using different CNN models. In addition, the study seeks to strengthen security measured in facial recognition system demonstrating that …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 3, 2024 · pp. 9–17 Read article
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Deep Learning based Solution for Leaf disease Detection in Crops and Fertilizer Recommendation
Abstract: The field of agriculture faces significant threats, including diseases that attack plant leaves. To address this issue, our system assists farmers in promptly detecting plant diseases using advanced technology. The user, typically a farmer, only needs to capture an image of the affected leaf and input it into our system. Our system then analyzes the uploaded image to accurately identify the specific disease afflicting the leaf. This analytical process is …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 31–40 Read article