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42 articles for “Network intrusion detection system”
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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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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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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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Unified Ensemble Techniques for Enhanced DDoS Attack Prevention and Detection
Abstract: Today’s world is entirely reliant on the internet. The internet is a worldwide information source that all users rely on, hence its accessibility is critical. There have been reports in recent years, particularly in the information and technology division of significant organizations worldwide, of data breaches where the terms denial-of-service (DoS) and DDoS are consistently present in the stolen material. Network security is seriously threatened by DoS attacks. They have …
Published in International Journal of Wireless Security and Networks · Vol. 2, Issue 2, 2024 · pp. 20–27 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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Securing The Internet of Things: Threats, Safeguards, and Future Directions
Abstract: The Internet of Things (IoT) brings immense value while also presenting cybersecurity challenges due to its scale, distribution, and heterogeneity. This study conducts an in-depth analysis of IoT security issues, threats, vulnerabilities, and mitigation strategies through an extensive review of scholarly literature and real-world case studies. A multilayered security approach is proposed, encompassing device hardening, network monitoring, encryption, access controls, governance frameworks, and emerging technologies. The analysis underscores systemic IoT …
Published in Journal Of Network security · Vol. 11, Issue 2, 2023 · pp. 26–31 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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A Survey of Several Machine Learning (ML) Algorithms for Security Solution in Internet of Things (IoT) Networks
Abstract: The Internet of Things (IoT) refers to the integration of physical objects with the Internet, allowing for connectivity and monitoring. This idea has garnered immense attention from researchers and users alike, driven by the widespread accessibility of the Internet. It spans a wide range of devices, including smart versions of conventional appliances, innovative tools tailored for Internet-enabled ecosystems, and sensors that leverage connectivity to revolutionize industries such as manufacturing, healthcare, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 1–11 Read article
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Entropy of Network Analysis and Cluster Detection Using Markov Theory
Abstract: Networks square measure an important part of nature and society; nonetheless several aspects of networks operate square measure still mostly unknown. from understanding the networks play a task; however even a small number of the foremost basic questions about networks will be troublesome to answer. Nevertheless, square measure two networks alike or different? However, do networks within networks type and the way will clusters be detected? As networks have amendment …
Published in Journal Of Network security · Vol. 6, Issue 3, 2018 · pp. 1–4 Read article
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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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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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Emerging Threats in Wireless Network Security: A Contemporary Analysis
Abstract: A crucial component of the architecture of contemporary information technology is wireless network security, as wireless communications .Given the continued importance of wireless communication in today's information technology architecture, wireless network security Since wireless communication is becoming more and more essential to our everyday lives, wireless network security is an essential component of today's information technology infrastructure. An overview of the main ideas, problems, and solutions for protecting wireless networks …
Published in International Journal of Satellite Remote Sensing · Vol. 1, Issue 2, 2023 · pp. 1–9 Read article
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Intrusion Detection Using ANN Machine Learning for MIM, DOS, BO
Abstract: Intrusion detection system is a software program developed to use on computer systems so that it can identify intrusion attack with help of different techniques like the machine learning algorithms. The variety of assaults over the internet has multiplied through the years because of the development and smooth availability of computing technologies. Attackers develop new attack types, so in order to save you from those assaults, intrusion detection systems must …
Published in Journal Of Network security · Vol. 10, Issue 1, 2022 · pp. 46–53 Read article
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Intrusion Detection Using ANN Machine Learning for MIM, DOS, BO
Abstract: Intrusion detection system is a software program developed to use on computer systems so that it can identify intrusion attack with help of different techniques like the machine learning algorithms. The variety of assaults over the internet has multiplied through the years because of the development and smooth availability of computing technologies. Attackers develop new attack types, so in order to save you from those assaults, intrusion detection systems must …
Published in Journal Of Network security Read article
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Assessing the Robustness of Machine Learning Models for Wireless Intrusion Detection Under Adversarial Traffic Perturbations
Abstract: As the Internet of Things (IoT) devices and wireless communication networks continue to grow rapidly, protecting systems from cyber threats has become increasingly important. Machine learning–based intrusion detection systems (IDS) have shown strong potential in detecting abnormal and malicious network activities, yet their effectiveness and resilience when facing adversarial attacks are still not sufficiently explored. This research evaluates Machine Learning (ML) models–XGBoost, random forest, and multi-layer perceptron (MLP)—in detecting attacks …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
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An Advance Model for Network Security System Using NIDS and HIDS
Abstract: important role. As use of internet is increasing fear of losing the data is also increased. In this paper a mechanism to secure the data is discussed which is known as intrusion detection system (IDS). This system’s major task is to detect the abnormal activities or attacks done by intrusion over network or host. With the help of this security system, we can maintain the security of data over the …
Published in Journal of Electronic Design Technology · Vol. 10, Issue 3, 2019 · pp. 42–52 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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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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A Suite of Security Mechanisms for Security and Privacy in MANET
Abstract: AbstractReputation of mobile strategies and wireless networks has significantly increased; wireless mobile networks have become popular and vigorous fields of message and link ages from many the years. MANET is the novel advance invention which allows clients to connect without any bodily infrastructure, irrespective of their location, that is why it is quantified as an “infrastructure-less” network. In the past few years, we have seen huge amount of wireless infrastructures …
Published in Journal of Communication Engineering & Systems · Vol. 9, Issue 1, 2019 · pp. 1–6 Read article
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Convolution Neural Network Model for Intrusion Detection in Network
Abstract: The evolution of the internet has made protecting information a necessity. Network intrusion and prevention plays an integral role in network-based security. The Intrusion technologies primarily used in today’s world deploy various machine learning algorithms and train models based on them resulting in effectively low detection rates. A technical advancement from machine learning, Deep Learning employs complex mechanisms to extract features from samples. As observed that conventional intrusion detection systems …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 8, Issue 1, 2021 · pp. 7–13 Read article