Abdullah M. Alnajim^1,*, Faisal Mohammed Alotaibi^2,#, Sheroz Khan^3,#

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4515-4535, 2025, DOI:10.32604/cmc.2025.063139 - 19 May 2025

Abstract Distributed denial of service (DDoS) attacks are common network attacks that primarily target Internet of Things (IoT) devices. They are critical for emerging wireless services, especially for applications with limited latency. DDoS attacks pose significant risks to entrepreneurial businesses, preventing legitimate customers from accessing their websites. These attacks require intelligent analytics before processing service requests. Distributed denial of service (DDoS) attacks exploit vulnerabilities in IoT devices by launching multi-point distributed attacks. These attacks generate massive traffic that overwhelms the victim’s network, disrupting normal operations. The consequences of distributed denial of service (DDoS) attacks are typically… More >

Chunhui Li^1,2, Xiaoying Wang^1,2,*, Qingjie Zhang^1,2, Jiaye Liang¹, Aijing Zhang¹

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 645-674, 2025, DOI:10.32604/cmc.2024.058081 - 03 January 2025

Abstract Previous studies have shown that deep learning is very effective in detecting known attacks. However, when facing unknown attacks, models such as Deep Neural Networks (DNN) combined with Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN) combined with LSTM, and so on are built by simple stacking, which has the problems of feature loss, low efficiency, and low accuracy. Therefore, this paper proposes an autonomous detection model for Distributed Denial of Service attacks, Multi-Scale Convolutional Neural Network-Bidirectional Gated Recurrent Units-Single Headed Attention (MSCNN-BiGRU-SHA), which is based on a Multi-strategy Integrated Zebra Optimization Algorithm (MI-ZOA). The… More >

Kithmini Godewatte Arachchige¹, Mohsin Murtaza², Chi-Tsun Cheng², Bader M. Albahlal^3,*, Cheng-Chi Lee^4,5,*

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 3679-3705, 2024, DOI:10.32604/cmc.2024.059378 - 19 December 2024

Abstract Information security has emerged as a crucial consideration over the past decade due to escalating cyber security threats, with Internet of Things (IoT) security gaining particular attention due to its role in data communication across various industries. However, IoT devices, typically low-powered, are susceptible to cyber threats. Conversely, blockchain has emerged as a robust solution to secure these devices due to its decentralised nature. Nevertheless, the fusion of blockchain and IoT technologies is challenging due to performance bottlenecks, network scalability limitations, and blockchain-specific security vulnerabilities. Blockchain, on the other hand, is a recently emerged information… More >

Ouail Mjahed^1,*, Salah El Hadaj¹, El Mahdi El Guarmah^1,2, Soukaina Mjahed¹

Computer Systems Science and Engineering, Vol.47, No.1, pp. 757-775, 2023, DOI:10.32604/csse.2023.039111 - 26 May 2023

Abstract Denial of Service (DoS/DDoS) intrusions are damaging cyber-attacks, and their identification is of great interest to the Intrusion Detection System (IDS). Existing IDS are mainly based on Machine Learning (ML) methods including Deep Neural Networks (DNN), but which are rarely hybridized with other techniques. The intrusion data used are generally imbalanced and contain multiple features. Thus, the proposed approach aims to use a DNN-based method to detect DoS/DDoS attacks using CICIDS2017, CSE-CICIDS2018 and CICDDoS 2019 datasets, according to the following key points. a) Three imbalanced CICIDS2017-2018-2019 datasets, including Benign and DoS/DDoS attack classes, are used.… More >

Sajjad Ahmad¹, Imran Raza¹, M. Hasan Jamal¹, Sirojiddin Djuraev², Soojung Hur³, Imran Ashraf^3,*

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2363-2377, 2023, DOI:10.32604/cmc.2023.032694 - 31 October 2022

Abstract Vehicle-to-grid technology is an emerging field that allows unused power from Electric Vehicles (EVs) to be used by the smart grid through the central aggregator. Since the central aggregator is connected to the smart grid through a wireless network, it is prone to cyber-attacks that can be detected and mitigated using an intrusion detection system. However, existing intrusion detection systems cannot be used in the vehicle-to-grid network because of the special requirements and characteristics of the vehicle-to-grid network. In this paper, the effect of denial-of-service attacks of malicious electric vehicles on the central aggregator of… More >

Magdy M. Fadel^1,*, Sally M. El-Ghamrawy², Amr M. T. Ali-Eldin¹, Mohammed K. Hassan³, Ali I. El-Desoky¹

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2293-2312, 2022, DOI:10.32604/cmc.2022.028287 - 16 June 2022

Abstract Distributed denial-of-service (DDoS) attacks are designed to interrupt network services such as email servers and webpages in traditional computer networks. Furthermore, the enormous number of connected devices makes it difficult to operate such a network effectively. Software defined networks (SDN) are networks that are managed through a centralized control system, according to researchers. This controller is the brain of any SDN, composing the forwarding table of all data plane network switches. Despite the advantages of SDN controllers, DDoS attacks are easier to perpetrate than on traditional networks. Because the controller is a single point of More >

Noman Mazhar^1,2, Rosli Saleh^1,*, Reza Zaba^1,3, Muhammad Zeeshan⁴, M. Muzaffar Hameed¹, Nauman Khan¹

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3099-3118, 2022, DOI:10.32604/cmc.2022.028285 - 16 June 2022

Abstract The advent of the latest technologies like the Internet of things (IoT) transforms the world from a manual to an automated way of lifestyle. Meanwhile, IoT sector open numerous security challenges. In traditional networks, intrusion detection and prevention systems (IDPS) have been the key player in the market to ensure security. The challenges to the conventional IDPS are implementation cost, computing power, processing delay, and scalability. Further, online machine learning model training has been an issue. All these challenges still question the IoT network security. There has been a lot of research for IoT based… More >