With the growing cyber-security threats to governmental and organizational infrastructures, the need to develop high resilient systems that preserve the security and privacy of data is becoming increasingly important. Although there is a large body of work on security and privacy countermeasures, cyber-attacks still persist. A prominent type of such attacks is intrusion attack that aims at data tampering, which can impair the availability and the integrity of data.
In this talk, I will address the challenges of designing and developing an adaptive intrusion management system. In particular, I will present PIMS, a Partitioning-based Intrusion Management System that can endure intense malicious intrusion attacks on Database Management Systems (DBMSs). The novelty of PIMS is a data partitioning scheme that provides the ability to contain the potential damage of the attacks. The partitioning problem is formulated as a dual-objective optimization problem. We propose two polynomial-time heuristic solutions for the problem. Furthermore, PIMS incorporates a novel partition-based response and recovery mechanisms, which execute compensating transactions to automatically repair the damage caused by the intrusion attacks.
Then, I will discuss the challenges of integrating PIMS in several database-backed Cyber-Based Systems, including Cloud computing and IoT. Moreover, I will present a novel Malicious Transaction Benchmark (MTB) to evaluate the performance of PIMS. The novelty of MTB is the ability to generate transactional workload and to orchestrate various attacking scenarios.
Muhamad Felemban is currently an Assistant Professor in the Computer Engineering Department, at KFUPM, Saudi Arabia. He earned his BSc in Computer Engineering from the KFUPM, in 2008; his MSc in Computer Science form KAUST in 2011; and his Ph.D. from the Department of Electrical and Computer Engineering at Purdue University, USA, in 2018. His research interest includes IoT security, Cloud and Edge security, and data privacy. He has several published papers in referred journals including TOIT, ToN, TDSC, and TCSV, IEEE Network, and IEEE Computer.