We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
Enhancing Cybersecurity by relying on a Botnet Attack Tracking Model using Harris Hawks Optimization.
- Authors
Ahmed, Ali Ibrahim; Khidhir, AbdulSattar M.; Baker, Shatha A.; Alsaif, Omar I.; Saleh, Ibrahim Ahmed
- Abstract
A botnet attack is a major cybersecurity threat that involves coordinated control of a network of infected computers, enabling large-scale distributed denial of service (DDoS) attacks, malware spreading, and other cybercrime activities. Proactive security measures and advanced threat intelligence systems are essential to detect and mitigate these assaults. This paper proposes the Harris Hawks Optimization (HHO) algorithm, which employs exploration and exploitation techniques to find optimal solutions for analyzing botnet attack pathways. The proposed approach involves HHO as a feature selector for extracting features from anomalous network traffic. The algorithm’s impact on botnet IP positioning performance is analyzed, considering different optimization modes and control center accuracy. The paper is organized into sections covering attack path establishment and analysis, system testing and verification, and a central leadership entity controls it [1]. Botnets are created based on the use of malicious software packages to infect important and sensitive devices in the network, thus making servers, computers, and Internet of Things devices vulnerable [2]. To detect these attacks and limit their impact requires many proactive security measures such as strong network security settings, regular software upgrades, etc. [3]. HHO is a powerful method that has the potential to solve many functional optimization problems and provides a suitable environment for engineering applications, as it mimics the exploration and exploitation phases during the foraging process of Harris Hawks [4]. A model based on HHO algorithm is proposed in this paper that has the ability to track and analyze bot attack paths by extracting a set of features during abnormal network traffic. The results were analyzed and their impact on the performance of robot networks was discussed, based on the use of different experimental results. After configuring the network topology and determining the attack path based on HHO, the performance of the algorithm and its effectiveness in preventing IP addresses from being spoofed are verified. The results showed convergence in being able to correct attack paths and effective performance in repelling the interference of fake IP addresses.
- Subjects
BOTNETS; COMPUTER network traffic; COMPUTER networks; COMPUTER network security; MALWARE; INTERNET protocol address
- Publication
International Journal for Computers & Their Applications, 2024, Vol 31, Issue 2, p103
- ISSN
1076-5204
- Publication type
Article