Thesis topic:
Detecting and Defending against Data Integrity Attacks in IoT systems
- Supervisor: Abasi-Amefon Obot Affia
- contact: amefon.affia@ut.ee
- Data integrity attacks have a large negative impact on IoT systems. The requirement for data integrity ensures system integrity and availability and can serve essential benefits in system monitoring and other data-dependent functions. Resolving data integrity attacks benefit trust-based information fusion to ensure that before relying on fused information from the IoT layers, data integrity is ensured.
The goal of the study is to analyze different attack types that affect data integrity within the IoT perception, network, and application layers and their impact on the IoT systems. Additionally, countermeasures and remediation paths should be evaluated. The paper can also highlight the interactions between each IoT layer when analyzing data integrity attacks or proposing countermeasures.
- Note: This topic can be adapted specifically for autonomous/connected vehicle systems and can be tested with the help of the Autonomous Vehicle Lab.
- References
- 1. Affia, A. O., Matulevičius, R., & Nolte, A. (2019, October). Security risk management in cooperative intelligent transportation systems: a systematic literature review. In OTM Confederated International Conferences" On the Move to Meaningful Internet Systems" (pp. 282-300). Springer, Cham.
- 2. Affia, A. O., Matulevičius, R., & Tõnisson, R. (2021, June). Security Risk Estimation and Management in Autonomous Driving Vehicles. In International Conference on Advanced Information Systems Engineering (pp. 11-19). Springer, Cham.