Complex Attack Linkage Decision-Making in Edge Computing Networks

• Main Authors: Qianmu Li, Shunmei Meng, Sainan Zhang, Jun Hou, Lianyong Qi
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Access
• Subjects: Edge computing network; complex attack detection; attribute attack graph; linkage defense
• Online Access: https://ieeexplore.ieee.org/document/8607977/

The edge computing network refers to a new paradigm of edge-side big data computing networks, which integrates networks, computing, storage, and business core capabilities. It is close to users, the Internet of Things (IoT), or data source side. The edge computing network is generated by the common development of cloud computing and the IoT. The core is the massive uplink monitoring collection and downlink decision-making control big data generated by intelligent sensing devices, solving the problem of low data computing efficiency and performance under the centralized cloud computing model. Compared with traditional cloud computing networks, the edge computing network has more abundant terminal types, more frequent data real-time interaction, more complex transmission network technology systems, and more intelligent and interconnected business systems. Moreover, this situation is aggravated with the mobile edge computing, e.g., model proximity service increasingly prevalent in daily life. However, the ubiquitous and open features of edge computing networks expose network security risks to all parts of the system, facing severe security protection challenges. To solve the linkage disposal and minimum cost response of complex attacks, we propose an attack linkage disposal decision-making method for edge computing network systems based on attribute attack graphs. A simplified attribute attack graph is constructed through the network security alarm association and false-alarm determination, and formal correlation analysis is performed on the causal relationship of the alarm information. On this basis, the linkage defense strategy decision computing is transformed into the minimum dominance set solution of the attribute attack graph. Finally, a linkage disposal strategy execution point decision algorithm based on the greedy algorithm is designed, which constructs a set of attack linkage disposal decision-making technologies with optimal defense cost. It provides a powerful guarantee for timely and effectively active defense.