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.
Model-Driven Performance Analysis Methodology for Distributed Software Systems
