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94 articles for “Intrusion Detection System”
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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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Network Intrusion Detection System using Machine Learning and Deep Learning Approach
Abstract: Networks play a significant part in today’s world; fast internet and communication industries result in vast network size and data expansion. Furthermore, attackers aiming to launch various cyberattacks inside the system cannot be neglected. An IDS keeps track of the network’s software and hardware security to preserve its privacy, integrity, and accessibility. Despite the significant efforts of the researchers, current IDS continue to confront challenges in terms of accuracy rate, …
Published in Journal Of Network security · Vol. 10, Issue 1, 2022 · pp. 7–34 Read article
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Intrusion Detection Systems: A Review
Abstract: In this paper, we present an overview of existing intrusion detection techniques. All these algorithms are described more or less on their own. Intrusion detection system is a very popular and computationally expensive task. We also explain the fundamentals of intrusion detection system. We describe today’s approaches for intrusion detection system. From the broad variety of efficient techniques that have been developed we will compare the most important ones. We …
Published in Journal of Advances in Shell Programming · Vol. 2, Issue 1, 2015 · pp. 11–13 Read article
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Intrusion Detection System with Machine Learning Algorithms
Abstract: Machine learning has become increasingly relevant in recent years, including in IT security. Algorithms are used to train intrusion detection systems to be able to react to new attack vectors. In this work, the basics of machine learning are explained and the results of two research projects are presented in order to investigate which algorithms are suitable for training a machine-learning intrusion detection system. In addition, the software library Scikit-Learn …
Published in Journal of Advancements in Robotics · Vol. 10, Issue 3, 2023 · pp. 28–37 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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Smart Electric Fence: A Deep Learning-Based Intrusion Detection System
Abstract: Intrusion of humans and wild animals into protected areas such as forest boundaries and agricultural lands poses significant challenges in terms of safety and resource management. Conventional electric fencing systems operate continuously without distinguishing the type of intrusion, leading to inefficient energy usage and potential harm to wildlife. The design and partial implementation of an intrusion detection system for smart electric fence based on deep learning are presented in this …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 3, 2026 Read article
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Comprehensive Comparative Analysis of Intrusion Detection Systems: Evaluating Signature Based, Anomaly Based, and Hybrid Approaches
Abstract: In the fast-changing world of cybersecurity, Intrusion Detection Systems (IDS) play a vital role in protecting digital resources. This study offers an in-depth comparative analysis to evaluate the efficiency and performance of different IDS solutions. It examines a variety of both commercial and opensource platforms, encompassing signature based, anomaly based, and hybrid models, to assess their effectiveness in identifying and responding to a wide range of cyber threats. Methodologies for …
Published in International Journal of Information Security Engineering · Vol. 3, Issue 2, 2025 · pp. 39–44 Read article
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A Study on Machine Learning and Cryptographic based Intrusion Detection System in Blockchain and Data Science Environment
Abstract: The recent speedy development of Internet of Things, vehicular networks and cloud computing has greatly boosted the need of effective and safe intrusion detection systems. The shortcomings of the traditional IDS-based approaches are centralized architecture, issue of scalability, and inability to analyze the encrypted and distributed data. To address these issues, the recent studies have paid attention to the incorporation of the latest technologies such as machine learning, deep learning, …
Published in International Journal of Wireless Network Security · Vol. 4, Issue 2, 2026 Read article
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A Technical Review on Intrusion Detection System with Various Machine Learning Algorithms in Data Mining
Abstract: With the progression in information & communication technology (ICT), it has become a vital element of human’s life. But this technology has brought a lot of threats in cyber world. These threats increase the chances of network vulnerabilities to attack the system in the network. To evade these attacks there are distinct ways in which one is Intrusion-Detection System (IDS). IDSs are software or hardware products that automate this monitoring …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 5, Issue 1, 2018 · pp. 1–8 Read article
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A Review on Various Approaches of Intrusion Detection System and Random Forest in Data Mining
Abstract: With the development in Information and Communication Technology (ICT), it have become a fundamental factor of human’s life. But this technology has brought lots of threats in cyber world. These threats increase the chances of network vulnerabilities to attack the structure in the network. DM based intrusion area techniques consistently fall into any of the two classes; anomaly detection and mistreat finding. In general course of DM alludes to extricating …
Published in Recent Trends in Programming languages · Vol. 5, Issue 1, 2018 · pp. 6–13 Read article
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An Intelligent Gray Wolf Optimizer: A Nature Inspired Technique in Intrusion Detection System (IDS)
Abstract: AbstractFeature choice algorithmic program investigates the knowledge to get rid of creaking, irrelevant, overabundance information, and everyone the while optimizes the classification performance. In this work, an intelligent grey wolf optimization (GWO) technique is used to select optimal feature subset for classification purposes. Grey wolf optimizer (GWO) is one of the most recent bio-enlivened optimization strategies, which impersonate the authority pecking order and chasing system of gray wolves in nature. …
Published in Journal of Advancements in Robotics · Vol. 6, Issue 1, 2019 · pp. 18–24 Read article
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Network Intrusion Detection System Using Decision Tree
Abstract: This paper presents a novel approach to network intrusion detection systems (NIDS) using advanced decision tree algorithms to address critical limitations in existing IDS solutions. Traditional IDSs often struggle with high false positive and negative rates, lack of scalability, and poor interpretability. Our proposed IDS leverages decision trees to enhance detection accuracy, interpretability, and scalability, thereby improving network security. Decision trees are chosen for their adaptive learning capabilities, transparent decision-making …
Published in Journal Of Network security · Vol. 12, Issue 2, 2024 · pp. 22–33 Read article
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Intrusion Detection System Using Honeyword
Abstract: We proposed a most accurate and best method for improving the security of hashed passwords by providing of additional “honeywords” (false passwords) associated with each user’s account. An adversary who wants to steals a file of hashed passwords and inverts the hash function cannot tell if he has found the password or a honeyword. An auxiliary server (the “Honeychecker”) can distinguish the user password from honeywords for the login routine, …
Published in Journal Of Network security · Vol. 8, Issue 2, 2020 · pp. 24–32 Read article
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Towards a Machine Learning Oriented Expert System for Intrusion Detection Model
Abstract: AbstractIn this paper, we describe the possibility of using machine learning and expert system for constructing a new intrusion detection model. The first main idea is to construct the classifier on the KDD intrusion data using a machine learning algorithm. For constructing the classifier J48 decision tree machine learning algorithm is used. The other key idea is to collect domain expert knowledge, and building an expert system to interpret and …
Published in Journal Of Network security · Vol. 8, Issue 3, 2020 · pp. 24–30 Read article
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AI-Powered Defense: Advancing Cybersecurity Through Artificial Intelligence Innovations
Abstract: In the current landscape of escalating cyber threats and increasingly sophisticated attack vectors, integrating artificial intelligence (AI) within cybersecurity strategies has become a critical step forward. This study explores the role of AI in strengthening cybersecurity by utilizing its strengths in data analysis, pattern recognition, and predictive modeling. Through AI, organizations can greatly enhance their ability to detect and respond to threats. Machine learning algorithms enable ongoing adaptation to new …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 1, 2026 · pp. 35–41 Read article
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Anomaly Based Intrusion Detection Using Machine Learning Techniques
Abstract: Detection of Cyberattacks/anomalies in a network to build an efficient Intrusion Detection System (IDS) is very important. A system called an intrusion detection system (IDS) monitors network traffic in order to find suspicious activity and sends out signals when it is noticed. Monitoring and data analysis are designed with the objective of finding any network or system intrusions. Machine learning methods can anticipate both known and unidentified attacks. This project …
Published in Journal Of Network security · Vol. 10, Issue 2, 2022 · pp. 1–8 Read article
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Navigating Privacy and Security in Cloud Computing
Abstract: Cloud computing has rapidly evolved, serving as a cornerstone for storage, information processing, and various applications. Its adoption has surged across enterprises and small businesses alike, offering them efficient means to store and process data. However, alongside its undeniable benefits, the cloud also presents inherent risks to privacy and security, as data traverses and resides on remote servers. Employing tactics such as data encryption, multifactor authentication, access control, and intrusion …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 1–10 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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Evaluation of Ensemble and Deep Learning Classifiers on CSE-CIC-IDS2018 Dataset for Intelligent NIDS
Abstract: Network Intrusion Detection System (NIDS) plays an active role in preventing cyberattacks by early detection of threats before it really starts affecting targeted information services. Over the years, many intrusion detection system (IDS) have been developed applying signature or rule-based approach to prevent unauthorised access of network or computer devices. However, ever growing landscape of cyberattacks in recent years has motivated present day researchers to design and develop more accurate …
Published in Current Trends in Information Technology · Vol. 13, Issue 1, 2023 · pp. 1–11 Read article
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Random Forrest Based Man-in-the-Middle Attack Detection in Advanced Metering Infrastructure
Abstract: Advanced metering infrastructure (AMI) plays a central role in the operation of modern smart grid (SG) systems by enabling continuous, two-way communication between utility providers and consumers. Through this communication, AMI supports real-time monitoring, dynamic pricing, and efficient energy management. However, the same connectivity that makes AMI effective also increases its exposure to cyber threats. One of the most critical threats is the man-in-the-middle (MITM) attack, in which an attacker …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 · pp. 1–8 Read article