Ahmad Alzu’bi^1,*, Amjad Albashayreh², Abdelrahman Abuarqoub³, Mai A. M. Alfawair⁴

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3785-3802, 2024, DOI:10.32604/cmc.2024.052599

Abstract In the era of the Internet of Things (IoT), the proliferation of connected devices has raised security concerns, increasing the risk of intrusions into diverse systems. Despite the convenience and efficiency offered by IoT technology, the growing number of IoT devices escalates the likelihood of attacks, emphasizing the need for robust security tools to automatically detect and explain threats. This paper introduces a deep learning methodology for detecting and classifying distributed denial of service (DDoS) attacks, addressing a significant security concern within IoT environments. An effective procedure of deep transfer learning is applied to utilize More >

Jieren Cheng^1,3, Xiulai Li^1,2,3,4,*, Xinbing Xu^2,3, Xiangyan Tang^1,3, Victor S. Sheng⁵

Computer Systems Science and Engineering, Vol.47, No.1, pp. 975-992, 2023, DOI:10.32604/csse.2023.039280

Abstract With the rapid development of blockchain technology, the number of distributed applications continues to increase, so ensuring the security of the network has become particularly important. However, due to its decentralized, decentralized nature, blockchain networks are vulnerable to distributed denial-of-service (DDoS) attacks, which can lead to service stops, causing serious economic losses and social impacts. The research questions in this paper mainly include two aspects: first, the classification of DDoS, which refers to detecting whether blockchain nodes are suffering DDoS attacks, that is, detecting the data of nodes in parallel; The second is the problem… More >

Olga Ussatova^1,2, Aidana Zhumabekova^1,*, Yenlik Begimbayeva^2,3, Eric T. Matson⁴, Nikita Ussatov⁵

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 577-594, 2022, DOI:10.32604/cmc.2022.026552

Abstract The fast development of Internet technologies ignited the growth of techniques for information security that protect data, networks, systems, and applications from various threats. There are many types of threats. The dedicated denial of service attack (DDoS) is one of the most serious and widespread attacks on Internet resources. This attack is intended to paralyze the victim's system and cause the service to fail. This work is devoted to the classification of DDoS attacks in the special network environment called Software-Defined Networking (SDN) using machine learning algorithms. The analyzed dataset included instances of two classes:… More >