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386 results for “Attack”
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Review ArticleOpen accessEvery word in the titleA Systematic Review of Adversarial Attacks: ML Techniques, Classification and CountermeasuresBhavesh Kumar Sharma, Sanatan Ratna, Rajiv KumarMachine Learning (ML) and Deep Learning (DL)-based technologies have made significant strides in areas such as computer vision, natural language processing, and autonomous systems. Yet they have been applied in high-stake applications, and have been found to be fragile through adversarial attacks-, maliciously crafted small distortions that fool models into making mistakes. From the pioneering work by Szegedy et al. … …Journal of Computer Science, Vol. 22, Issue 5 · 19 May 2026 · 1,497 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleLSTM-Based AI Model for Sinkhole Attack Detection With Legal Basis in an Ecuadorian Public InstitutionEstefanía Alejandra Mora Parra, Rubén Nogales Portero, Moisés Toapanta T. et al.Wireless Sensor Networks (WSN) are an essential component of the Internet of Things (IoT). However, their decentralized nature, data transmission over unencrypted channels, and the physical exposure of nodes make them especially vulnerable to attacks, among which the sinkhole attack stands out. This research aims to develop a machine learning–based model to detect sinkhole‐type attacks in wireless sensor networks, with … …Journal of Computer Science, Vol. 22, Issue 3 · 4 Mar 2026 · 1,648 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleRobust Adversarial Attack Detection via Generative Adversarial Network With Residual Multi-Layer Aggregation Based Contrastive Loss FunctionAmudha Gopalakrishnan, Nalini JosephAdversarial attacks in medical imaging refer to subtle modifications to images that mislead diagnostic systems, resulting in inaccurate diagnoses and assessments. These attacks exploit vulnerabilities in image processing, leading to misclassification or altered visual features that often go unnoticed. This raises serious concerns about the security and reliability of medical diagnosis, directly impacting clinical decision-making and patient safety. This research … …Journal of Computer Science, Vol. 22, Issue 1 · 10 Feb 2026 · 1,742 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSecuring IoT Networks: Multi-Attack Detection of RPL Routing Threats Using Deep LearningAyoub Krari, Abdelmajid Hajami, Ayoub Toubi, Marouane Ait SaidThe growing frequency of cyber threats in Internet of Things (IoT) networks, including attacks on RPL routing, requires the creation of strong detection systems to safeguard network integrity and provide dependable communication. This study is driven by the pressing necessity to tackle the security weaknesses in IoT networks, where threats such as black holes, version number alteration, DIS flooding, and … …Journal of Computer Science, Vol. 21, Issue 4 · 6 Mar 2025 · 5,397 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleThe Optimized Extreme Learning Machine (GA-OELM) for DDoS Attack Detection in Cloud EnvironmentMeryem Ec-Sabery, Adil Ben Abbou, Abdelali Boushaba et al.The widespread adoption of cloud computing has increased the attack surface and raised significant security concerns. A Distributed Denial of Service (DDoS) is a serious attack that depletes the network and server resources in cloud computing, causing service downtime or reduced performance. Therefore, defending against DDoS attacks becomes an urgent need. In this present paper, we propose an Optimized Extreme … …Journal of Computer Science, Vol. 21, Issue 1 · 19 Dec 2024 · 5,033 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDeep Learning Approach to Mitigate DDoS Attacks in SDNHema Surendrakumar Dhadhal, Paresh Kotak, Parvez Faruki, Atul GonsaiThe rise of Distributed Denial of Service (DDoS) attacks remains a significant obstacle to network security and availability. This abstract presents a new hybrid model for DDoS mitigation in Software-Defined Networking (SDN) environments, combining a Semi-supervised Deep Extreme Learning Machine (Semi-Deep ELM) with a hybrid architecture. SDN's centralized control and programmability create an ideal platform for implementing advanced mitigation strategies. … …Journal of Computer Science, Vol. 20, Issue 9 · 5 Jul 2024 · 5,338 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleImproved Intrusion Detection System to Alleviate Attacks on DNS ServiceHani Mahmoud Al-Mimi, Nesreen Adnan Hamad, Mosleh Mohammad Abualhaj et al.Cybercriminals continuously devise new and more sophisticated ways to attack their targets’ security and cyberattacks are on the rise. One of the earliest and most vulnerable network services is the Domain Name System (DNS), which has had several security issues that have been repeatedly exploited over time. Building a strong Intrusion Detection System (IDS) that guards against unwanted access to … …Journal of Computer Science, Vol. 19, Issue 12 · 9 Nov 2023 · 5,786 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDEACT: Hardware Solution to Rowhammer AttacksTesfamichael Gebregziabher Gebrehiwot, Fitsum Assamnew Andargie, Mohammed IsmailDynamic Random Access Memory (DRAM) is a crucial component in modern computing devices. Improvements in process technology have significantly increased the speed and storage capacity of memory devices. However, as memory cells become smaller and closer to one another, annoying circuit disturbance errors such as the Row-hammer problem have become significant. Studies show that attackers can systematically exploit such errors … …Journal of Computer Science, Vol. 19, Issue 7 · 22 Jun 2023 · 6,483 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleOrganizing Classification of Application Logic Attacks in Component-based E-Commerce SystemsFaisal Nabi, Jianming Yong, Xiaohui Tao et al.This research paper addresses the topic of application logic attack taxonomy that is due to unclear and incorrect implementation in component-based applications. The issue addresses the detection and classification of two separate types of vulnerabilities in component-based applications. The paper completes this aim through organising the classification of each attack and then proposes the classification of logical vulnerabilities and discusses … …Journal of Computer Science, Vol. 17, Issue 11 · 14 Nov 2021 · 6,611 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSoft Marking Scheme of SVM Hierarchical Classifiers for Attack ClassificationAzizi Abdullah, Warhamni Jani@MokhtarClassification is a predictive modelling problem that involves assigning a class label to an instance correctly. There exist several strategies in machine learning to deal with the multi-class classification problems for attack detection. One of the popular strategies is the one-vs-one that decomposes the multi-class problem into multiple binary ones. The approach has been applied in many popular supervised learning … …Journal of Computer Science, Vol. 17, Issue 9 · 27 Sep 2021 · 6,000 accessesView PDFCite