BibTeX:

@article{IJIRSTV3I4147,
     title={Design and Development of Enhanced Optimization Techniques Based on Ant Colony Systems},
     author={Annu K Simon, Dr. S. Subasree and Mr. Girish R},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={3},
     number={4},
     pages={414--419},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV3I4147.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

Many cyber defense techniques require time critical decisions and deployments. These decisions cannot be taken by a human alone; rather it requires a mixed initiative of human as well as some other digital agents. This project will make use of biologically inspired swarming agents called digital ants which make use of Ant Colony Optimization algorithm (ACO) for cyber defense. The system is rapidly and automatically adapts to new cyber-attacks while enabling humans to supervise the system at an appropriate level. Ant colony systems can provide approximate solutions for so many dynamic problems, but the performance of ant colony systems is reduced due to its slow convergence rate. This project will incorporate a physarum based matrix optimization strategy in Ant Colony Optimization algorithm, so as to enhance the convergence rate and leads to better performance in cyber defense techniques.

Digital Agents, Ant Colony, Ant Colony Optimization (ACO), Physarum based Matrix Optimization