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Zhu Z, Geng J, Zhou M, Fang B. Module Against Power Consumption Attacks for Trustworthiness of Vehicular AI Chips in Wide Temperature Range. INT J PATTERN RECOGN 2022. [DOI: 10.1142/s0218001422500124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Power consumption attacks monitoring on artificial intelligence (AI) chips play a critical role in the vehicular AI systems. However, most of the current monitoring and management methods focus on the trustworthiness of industrial equipment instead of resource-constrained edge devices. To address the above problem, a closed-loop module for monitoring and management of vehicular AI chips based on fitting and filtering to resist power consumption attacks is proposed in this paper. First, considering the characteristics of power, we propose a raw data correction approach for power monitoring to monitor abnormal power consumption. Second, we address the challenging problem of precision temperature monitoring to monitor the abnormal temperature of the chip, especially in a wide temperature range. Finally, the established method is applied to attack surveillance and transformed into a power consumption management problem solved by dynamic voltage and frequency scaling (DVFS) technology. As the experimental results reveal, compared with existing methods of power and temperature monitoring and power consumption control in wide temperature, our method can achieve significantly improved monitoring and managing performance.
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Affiliation(s)
- Zongwei Zhu
- School of Software Engineering, Suzhou Research Institute for Advanced Study, University of Science and Technology of China, Suzhou 215000, P. R. China
| | - Jiawei Geng
- School of Software Engineering, Suzhou Research Institute for Advanced Study, University of Science and Technology of China, Suzhou 215000, P. R. China
| | - Mingliang Zhou
- The School of Computer Science, Chongqing University, Chongqing 400044, P. R. China
| | - Bin Fang
- The School of Computer Science, Chongqing University, Chongqing 400044, P. R. China
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