Ramesh, Shanmugasundar (2023) Enhancing Secure Communication Protocol in ADAS (Advanced Driving Assistance System) System. Masters thesis, Dublin, National College of Ireland.
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Abstract
The objective of this study is to improve the secure communications protocol in Advanced Driver Assistance Systems (ADAS) by confronting the difficulties caused by the sensitive and constantly changing character of information in autonomous driving scenarios. The suggested method combines blockchain technology to create an encrypted proof of authentication, Advanced Encryption Standard in Galois/Counter Mode (AES-GCM) for reliable information encryption, and Multi Input Data Merging (MIDM) for comprehensive information synthesizing. A key component in integrating various data streams produced by sensors, cameras, and other ADAS components is the Multi Input Data Merging (MIDM) approach. Using the intelligent integration of various information, MIDM provides a comprehensive and instantaneous comprehension of the vehicle's environment. By offering a dynamic and adaptive encryption solution suitable to the various properties of numerous kinds of information inside the ADAS environment, the incorporation of AES-GCM as the encryption mechanism improves the security of data transmission. Moreover, a decentralized and impenetrable structure for authentication evidence is introduced by the use of blockchain technology. The blockchain provides an immutable and transparent ledger by securely recording every transaction or authentication event. This offers a distributed consensus technique for verifying the validity of activities inside the ADAS system in addition to ensuring the integrity of authentication procedures. In order to handle the challenges of data integration, encryption, and authentication, this study suggests an all-encompassing and flexible security architecture for ADAS. The goal of the beneficial combination of blockchain, AES-GCM, and MIDM technology is to substantially improve the secure communications protocol, consequently enhancing the effectiveness and security of autonomous driving systems.
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