Adil Fahad

TL;DR: Concepts and algorithms related to clustering, a concise survey of existing (clustering) algorithms as well as a comparison, both from a theoretical and an empirical perspective are introduced.

TL;DR: Two novel techniques are proposed: an automatic identification of consistent and inconsistent states of SCADA data for any given system, and an automatic extraction of proximity detection rules from identified states.

TL;DR: A novel way is proposed to identify efficiently and accurately the ''best'' features by first combining the results of some well-known FS techniques to find consistent features, and then using the proposed concept of support to select a smallest set of features and cover data optimality.

TL;DR: An innovative intrusion detection approach to detect SCADA tailored attacks is presented based on a data-driven clustering technique of process parameters, which automatically identifies the normal and critical states of a given system and extracts proximity-based detection rules from the identified states for monitoring purposes.

TL;DR: A SCADA security testbed based on virtualization technology is proposed, and a server is introduced which is used as a surrogate for water distribution systems and a case study of two malicious attacks is presented to demonstrate how the testbed can easily monitor and control any automatised processes.