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22 results for “Cyber-Attacks”
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Research ArticleOpen accessIn the keywordsAn Intrusion Detection System Using Optimized Deep Learning for IoT NetworksChempavathy B., Mouleeswaran S. K.In the rapidly evolving landscape of Internet of Things (IoT) networks, assuring security is paramount. Cyber-attacks on IoT networks are evolving in complexity and scale. Intruders employ diverse tactics, including malware, Denial of Service (DoS) attacks, along with unauthorized access. This research aims to propose an optimized Deep Learning (DL) based Intrusion Detection System (IDS) to bolster security within IoT … …Journal of Computer Science, Vol. 21, Issue 8 · 9 Oct 2025 · 3,001 accessesView PDFCite
Review ArticleOpen accessIn the keywordsDDoS Mitigation Using Machine Learning in Software-Defined NetworksAhmed Gaber Abu Abd-Allah, Noureldin Omar Mohamed, Mohamed Samir Mohamed et al.With the escalating frequency and sophistication of Distributed Denial of Service (DDoS) attacks, the realm of cyber security has witnessed a paradigm shift towards innovative solutions. This review explores the potential of machine learning as a powerful defense mechanism in the field of DDoS mitigation within Software-Defined Networks (SDNs). The study methodically examines a variety of machine learning algorithms used … …Journal of Computer Science, Vol. 21, Issue 4 · 23 Mar 2025 · 6,782 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSecuring 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 · 5,413 accessesView PDFCite
Research ArticleOpen accessIn the keywordsCyber Security Threats and Countermeasures using Machine and Deep Learning Approaches: A SurveyManjula M, Venkatesh, Venugopal K. R.Recent advancements in e-business, e-healthcare, e-governance, and online digital transactions have brought valuable benefits. Unfortunately, it raises severe cyber-attacks. Cyberattacks disrupt normal operations, try to retrieve confidential information and defense secrets, and subvert the nation’s defense systems and Internet-connected devices. Cyber security solutions are required to detect, analyze, defend against threats and protect sensitive data from unauthorized access. This study … …Journal of Computer Science, Vol. 19, Issue 1 · 4 Jan 2023 · 9,379 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Data Security Approach Based on GAN Teganographyand AES-RSA Encryption in a Distributed SystemDerrick Méthode Bagaza, Abraham Walake, Mamoudou Kourouma, Blaise Omer YenkeData security in distributed environments has become a major challenge due to the dispersion of resources, the expansion of the attack surface, and the increasing sophistication of cyber threats. Although traditional mechanisms such as data encryption, multi-factor authentication, and access control systems help to strengthen information protection, these approaches still have certain limitations when faced with advanced attacks and human … …Journal of Computer Science, Vol. 22, Issue 8 · 28 Jul 2026 · 1,068 accessesView PDFCite
Research ArticleOpen accessIn the abstractRisk Assessment of Healthcare Information Systems in Indonesian Regional Government Hospitals Using ISO 27001:2022Deo Alif Alfitrah, Nilo LeegowoThe growing number of cyber-attacks targeting the healthcare sector, particularly Indonesian regional government hospitals, reflects the absence of a structured information security management system. Issues such as shared account usage, lack of staff security training, and undocumented incident reporting present serious risks to patient data. This study aims to assess the current state of information security in a government hospital … …Journal of Computer Science, Vol. 22, Issue 3 · 13 Mar 2026 · 2,424 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelligent Intrusion Detection System Using RF, SVM, and DT: A Comparison-Based KDD Data SetWalaa Hassan Elashmawi, Alaa Sheta, Ahmad Al-QeremThe rapid growth of technology has brought about many advantages, but has also made networks more susceptible to security threats. Intrusion Detection Systems (IDS) play a vital role in protecting computer networks against malicious activities. Given the dynamic and constantly evolving nature of cyber threats, these systems must continuously adapt to maintain their effectiveness. Machine Learning (ML) methods have gained … …Journal of Computer Science, Vol. 21, Issue 8 · 28 Aug 2025 · 5,821 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing the CIC IoT Dataset 2023 for Improved Attack Detection through GANs Augmentation and Federated LearningShahad Alahmari, Noura AleisaThe escalating frequency and sophistication of cyber-attacks on Internet of Things (IoT) devices present a pressing challenge to cybersecurity. With IoT device connections projected to exceed 42 billion by 2025, the vulnerability of these devices to cyber-attacks has never been more evident. This paper investigates the integration of Machine Learning (ML) and data augmentation, specifically Generative Adversarial Networks (GAN) and … …Journal of Computer Science, Vol. 21, Issue 7 · 18 Jul 2025 · 9,122 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Succinct Review on Identification of Network Anomalies and Protection in Cyber-Physical SystemsShalini Kumari, Chander Prabha, Prakash Srivastava et al.Advanced cyberattacks outperform traditional threat detection methods in the rapidly expanding cybersecurity field. Advanced Machine Learning (ML) algorithms can detect network traffic and system problems using AI-based Anomaly Detection (AD) for cybersecurity in real-time. Signature-based systems may overlook new and subtle threats. This paper examines Artificial Intelligence (AI) driven AD systems' design, methodology, and efficacy. The process includes data preprocessing … …Journal of Computer Science, Vol. 21, Issue 6 · 29 May 2025 · 5,247 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing IoT RPL Protocol Security Against Black Hole Attacks with Deep Learning TechniquesKrari Ayoub, Hajami Abdelmajid, Toubi Ayoub, Mihi SoukainaAs the Internet of Things (IoT) extends its reach into critical infrastructures, it encounters escalating security threats, particularly black hole attacks that jeopardize network communication. The growing use of IoT in essential services underscores the need for robust network integrity. Driven by this urgency, our research has developed a sophisticated detection framework that effectively identifies black hole attacks within IoT … …Journal of Computer Science, Vol. 20, Issue 11 · 18 Oct 2024 · 5,004 accessesView PDFCite