Joseph DiVita

IoDDoS - The Internet of Distributed Denial of Sevice Attacks - A Case Study of the Mirai Malware and IoT-Based Botnets.

The Internet of Things (IoT), a platform and phenomenon allowing everything to process information and communicate data, is populated by ‘things’ which are introducing a multitude of new security vulnerabilities to the cyber-ecosystem. These vulnerable ‘things’ typically lack the ability to support security technologies due to the required lightweightness and a rush to market. There have recently been several high-profile Distributed Denial of Service (DDoS) attacks which utilized a botnet army of IoT devices. We first discuss challenges to cybersecurity in the IoT environment. We then examine the use of IoT botnets, the characteristics of the IoT cyber ecosystem that make it vulnerable to botnets, and make a deep dive into the recently discovered IoTbased Mirai botnet malware. Finally, we consider options to mitigate the risk of IoT devices being conscripted into a botnet army.

An Approach to Botnet Malware Detection Using Nonparametric Bayesian Methods

Botnet malware, which infects Internet-connected devices and seizes control for a remote botmaster, is a long-standing threat to Internet-connected users and systems. Botnets are used to conduct DDoS attacks, distributed computing (e.g., mining bitcoins), spread electronic spam and malware, conduct cyberwarfare, conduct click-fraud scams, and steal personal user information. Current approaches to the detection and classification of botnet malware include syntactic, or signature-based, and semantic, or context-based, detection techniques. Both methods have shortcomings and botnets remain a persistent threat. In this paper, we propose a method of botnet detection using Nonparametric Bayesian Methods.