Of Bees and Botnets
Abstract
Botnets ability to grow to large sizes combined with our inability to exhaustively incapacitate them has forced us to look for more effective methods to model their growth and seek ways to curtail it. Particle swarm optimization is a stochastic computation technique based on the movement and intelligence of swarms. This study uses a simulated bee colony to model the growth of a botnet. Botnets are like swarms of bees in several ways. For both, a successful hive grows while withstanding losses. A swarm of honeybees also uses distributed decision making [1] similarly to a botnet. This study uses swarm optimization to model the growth a botnet and estimate the optimal number of scout bees required to make a botnet hive successful. The technique is applied to the Mirai botnet to simulate its growth, find ways to reduce that growth, and minimize distributed denial-of-service attacks launched from these botnets.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2018
- Accession Number
- AD1087757
Entities
People
- Vijay Sarvepalli
Organizations
- Carnegie Mellon University