Thesis Defense - Cem Ata Baykara (MSCS)

Cem Ata Baykara– M.Sc. Computer Science

Asst. Prof. Kübra Kalkan– Advisor

Dr. Ilgın Şafak – Co-Advisor

Date: 25.05.2022

Time: 14:00

Locatin: AB1 511

“A Security Protocol for IoT Networks using Blacklisting and Trust Scoring”

Thesis Committee

Asst. Prof. Kübra Kalkan, Özyeğin University

Assoc. Prof. Hasan Sözer, Özyeğin University

Prof. Fatih Alagöz, Boğaziçi University

Abstract:

There have been a number of high-profile incidents to compromise and attacking larger networks of IoT devices, drawing attention to the need for IoT security. The purpose of IoT security is to ensure the availability, confidentiality, and integrity of IoT networks. However, due to the heterogeneity of IoT devices and the possibility of attacks from both inside and outside the network, securing an IoT network is a difficult task. Handshake protocols are useful for achieving mutual authentication which allows secure inclusion of devices into the network. However, they cannot prevent malicious network-based attacks once attackers enter the network. The use of autonomous anomaly detection and blacklisting prevent nodes with anomalous behavior from joining, re-joining, or remaining in the network. This is useful for securing an IoT network from insider network-based attacks. Similarly, trust scoring is another popular method that can be used to increase the resilience of the network against behavioral attacks.

The contributions of this thesis are threefold. First, we propose a new handshake protocol that can be used in device discovery and mutual authentication to ensure the security of the IoT network from outsider attacks. In the proposed handshake protocol, a Physical Unclonable Function (PUF) is utilized for the session key generation to reduce computational complexity. The proposed protocol is resilient to Man-in-the-middle, replay, and reforge attacks as proven in our security analysis. Secondly, we propose a machine learning (ML) based intrusion and anomaly detection to prevent network-based attacks from the insiders. Finally, we propose a trust system that utilizes blockchain for managing the trust of a dynamic IoT network to increase resilience against behavioral attacks. Simulation results show that the proposed comprehensive security framework is capable of ensuring the security of an IoT network from both inside and outside attackers.

Bio:

Cem Ata Baykara is a graduate of Istek Science High School. He received his bachelor’s degree in computer science from Özyeğin University in 2020 and started his master’s degree in computer science, specializing in network security, the same year.

He is currently working as a researcher and developer on a joint project of Fibabanka and Özyeğin University.