Using swarming agents for scalable security in large network environments

The difficulty of securing computer infrastructures increases as they grow in size and complexity. Network-based security solutions such as IDS and firewalls cannot scale because of exponentially increasing computational costs inherent in detecting the rapidly growing number of threat signatures. Host-based solutions like virus scanners and IDS suffer similar issues that are compounded when enterprises try to monitor them in a centralized manner. Swarm-based autonomous agent systems like digital ants and artificial immune systems can provide a scalable security solution for large network environments. The digital ants approach offers a biologically inspired design where each ant in the virtual colony can detect atoms of evidence that may help identify a possible threat. By assembling the atomic evidences from different ant types the colony may detect the threat. This decentralized approach can require, on average, fewer computational resources than traditional centralized solutions; however there are limits to its scalability. This paper describes how dividing a large infrastructure into smaller, managed enclaves allows the digital ant framework to effectively operate in larger environments. Experimental results will show that using smaller enclaves allows for more consistent distribution of agents and results in faster response times.