| Title | Network Security Risk Assessment Using Intelligent Agents |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Mohammadian, M. |
| Conference Name | 2018 International Symposium on Agent, Multi-Agent Systems and Robotics (ISAMSR) |
| Keywords | attack graph, Attack Graphs, automated intelligent systems, Communication networks, compositionality, computer network security, computer networks, data communication, Data security, decision making, decision-making approach, FCMs, Fuzzy cognitive maps, governmental rules, graph theory, Intelligent Data and Security, Intelligent Data Security, interconnected network analysis, large networks analysis, multi-agent systems, multiagent system, network connectivity, network graphical representation, network security engineers, network security risk assessment, organisational rules, pubcrawl, Resiliency, risk analysis, Risk Prevention, robots, Scalability, security, security breaches, security risk analysis, Task Analysis, Tools |
| Abstract | Network security is an important issue in today's world with existence of network systems that communicate data and information about all aspects of our life, work and business. Network security is an important issue with connected networks and data communication between organisations of that specialized in different areas. Network security engineers spend a considerable amount of time to investigate network for security breaches and to enhance the security of their networks and data communications on their networks. They use Attack Graphs (AGs) which are graphical representation of networks to assist them in analysing large networks. With increase size of networks and their complexity, the use of attack graphs alone does not provide the necessary risk analysis and assessment facilities. There is a need for automated intelligent systems such as multiagent systems to assist in analysing, assessing and testing networks. Network systems changes with the increase in the size of organisation and connectivity of network of organisations based on the business needs or organisational or governmental rules and regulations. In this paper a multi-agent system is developed assist in analysing interconnected network to identify security risks. The multi-agent system is capable of security network analysis to identify paths using an attack graph of the network under consideration to protect network systems, as the networks grow and change, against possible attacks. The multiagent system uses a model developed by Mohammadian [3] for converting AGs to Fuzzy Cognitive Maps (FCMs) to identify attack paths from attack graphs and perform security risk analysis. In this paper a novel decision-making approach using FCMs is employed. |
| DOI | 10.1109/ISAMSR.2018.8540557 |
| Citation Key | mohammadian_network_2018 |
Network Security Risk Assessment Using Intelligent Agents