Inicio  /  Applied Sciences  /  Vol: 11 Par: 12 (2021)  /  Artículo
ARTÍCULO
TITULO

Standalone Behaviour-Based Attack Detection Techniques for Distributed Software Systems via Blockchain

Hosam Aljihani    
Fathy Eassa    
Khalid Almarhabi    
Abdullah Algarni and Abdulaziz Attaallah    

Resumen

With the rapid increase of cyberattacks that presently affect distributed software systems, cyberattacks and their consequences have become critical issues and have attracted the interest of research communities and companies to address them. Therefore, developing and improving attack detection techniques are prominent methods to defend against cyberattacks. One of the promising attack detection methods is behaviour-based attack detection methods. Practically, attack detection techniques are widely applied in distributed software systems that utilise network environments. However, there are some other challenges facing attack detection techniques, such as the immutability and reliability of the detection systems. These challenges can be overcome with promising technologies such as blockchain. Blockchain offers a concrete solution for ensuring data integrity against unauthorised modification. Hence, it improves the immutability for detection systems? data and thus the reliability for the target systems. In this paper, we propose a design for standalone behaviour-based attack detection techniques that utilise blockchain?s functionalities to overcome the above-mentioned challenges. Additionally, we provide a validation experiment to prove our proposal in term of achieving its objectives. We argue that our proposal introduces a novel approach to develop and improve behaviour-based attack detection techniques to become more reliable for distributed software systems.

 Artículos similares

       
 
Xie He, Arash Habibi Lashkari, Nikhill Vombatkere and Dilli Prasad Sharma    
Over the past few decades, researchers have put their effort and paid significant attention to the authorship attribution field, as it plays an important role in software forensics analysis, plagiarism detection, security attack detection, and protection... ver más
Revista: Information

 
Mazen Gazzan and Frederick T. Sheldon    
Ransomware attacks have emerged as a significant threat to critical data and systems, extending beyond traditional computers to mobile and IoT/Cyber?Physical Systems. This study addresses the need to detect early ransomware behavior when only limited dat... ver más
Revista: Information

 
Kexiang Qian, Hongyu Yang, Ruyu Li, Weizhe Chen, Xi Luo and Lihua Yin    
With the rapid growth of IoT devices, the threat of botnets is becoming increasingly worrying. There are more and more intelligent detection solutions for botnets that have been proposed with the development of artificial intelligence. However, due to th... ver más
Revista: Applied Sciences

 
Mohamed Shenify, Fokrul Alom Mazarbhuiya and A. S. Wungreiphi    
There are many applications of anomaly detection in the Internet of Things domain. IoT technology consists of a large number of interconnecting digital devices not only generating huge data continuously but also making real-time computations. Since IoT d... ver más
Revista: Applied Sciences

 
Sharoug Alzaidy and Hamad Binsalleeh    
In the field of behavioral detection, deep learning has been extensively utilized. For example, deep learning models have been utilized to detect and classify malware. Deep learning, however, has vulnerabilities that can be exploited with crafted inputs,... ver más
Revista: Applied Sciences