A Direct Anonymous Attestation Scheme Based on Mimic Defense Mechanism
Title | A Direct Anonymous Attestation Scheme Based on Mimic Defense Mechanism |
Publication Type | Conference Paper |
Year of Publication | 2020 |
Authors | Yu, Chen, Chen, Liquan, Lu, Tianyu |
Conference Name | 2020 International Conference on Internet of Things and Intelligent Applications (ITIA) |
Date Published | Nov. 2020 |
Publisher | IEEE |
ISBN Number | 978-1-7281-9301-4 |
Keywords | active defense, anonymous attestation, attestation, composability, Hash functions, Human Behavior, Internet of Things, M2M, machine-to-machine communications, mimic defense, privacy, Protocols, pubcrawl, Public key, resilience, Resiliency, Servers |
Abstract | Machine-to-Machine (M2M) communication is a essential subset of the Internet of Things (IoT). Secure access to communication network systems by M2M devices requires the support of a secure and efficient anonymous authentication protocol. The Direct Anonymous Attestation (DAA) scheme in Trustworthy Computing is a verified security protocol. However, the existing defense system uses a static architecture. The "mimic defense" strategy is characterized by active defense, which is not effective against continuous detection and attack by the attacker. Therefore, in this paper, we propose a Mimic-DAA scheme that incorporates mimic defense to establish an active defense scheme. Multiple heterogeneous and redundant actuators are used to form a DAA verifier and optimization is scheduled so that the behavior of the DAA verifier unpredictable by analysis. The Mimic-DAA proposed in this paper is capable of forming a security mechanism for active defense. The Mimic-DAA scheme effectively safeguard the unpredictability, anonymity, security and system-wide security of M2M communication networks. In comparison with existing DAA schemes, the scheme proposed in this paper improves the safety while maintaining the computational complexity. |
URL | https://ieeexplore.ieee.org/document/9312307 |
DOI | 10.1109/ITIA50152.2020.9312307 |
Citation Key | yu_direct_2020 |