Blockchain-based Smart-IoT Trust Zone Measurement Architecture
This addresses security for IoT systems, but it appears incremental as it combines existing technologies like blockchain, deep learning, and SGX.
The paper tackles the vulnerability of IoT devices to attacks by proposing a behavior monitor in an IoT-Blockchain setup that uses deep auto-encoders and Intel SGX to analyze device activity and provide a secure execution environment, with evaluation on Mirai-infected data showing results in terms of accuracy and detection time.
With a rapid growth in the IT industry, Internet of Things (IoT) has gained a tremendous attention and become a central aspect of our environment. In IoT the things (devices) communicate and exchange the data without the act of human intervention. Such autonomy and proliferation of IoT ecosystem make the devices more vulnerable to attacks. In this paper, we propose a behavior monitor in IoT-Blockchain setup which can provide trust-confidence to outside networks. Behavior monitor extracts the activity of each device and analyzes the behavior using deep auto-encoders. In addition, we also incorporate Trusted Execution Technology (Intel SGX) in order to provide a secure execution environment for applications and data on blockchain. Finally, in evaluation we analyze three IoT devices data that is infected by mirai attack. The evaluation results demonstrate the ability of our proposed method in terms of accuracy and time required for detection.