Side-Channel Analysis-Based Model Extraction on Intelligent CPS: An Information Theory Perspective

Qianqian Pan, Jun Wu*, Xi Lin, Jianhua Li

*この研究の対応する著者

研究成果: Conference contribution

抄録

The intelligent cyber-physical system (CPS) has been applied in various fields, covering multiple critical infras-tructures and human daily life support areas. CPS Security is a major concern and of critical importance, especially the security of the intelligent control component. Side-channel analysis (SCA) is the common threat exploiting the weaknesses in system operation to extract information of the intelligent CPS. However, existing literature lacks the systematic theo-retical analysis of the side-channel attacks on the intelligent CPS, without the ability to quantify and measure the leaked information. To address these issues, we propose the SCA-based model extraction attack on intelligent CPS. First, we design an efficient and novel SCA-based model extraction framework, including the threat model, hierarchical attack process, and the multiple micro-space parallel search enabled weight extraction algorithm. Secondly, an information theory-empowered analy-sis model for side-channel attacks on intelligent CPS is built. We propose a mutual information-based quantification method and derive the capacity of side-channel attacks on intelligent CPS, formulating the amount of information leakage through side channels. Thirdly, we develop the theoretical bounds of the leaked information over multiple attack queries based on the data processing inequality and properties of entropy. These convergence bounds provide theoretical means to estimate the amount of information leaked. Finally, experimental evaluation, including real-world experiments, demonstrates the effective-ness of the proposed SCA-based model extraction algorithm and the information theory-based analysis method in intelligent CPS.

本文言語English
ホスト出版物のタイトルProceedings - IEEE Congress on Cybermatics
ホスト出版物のサブタイトル2021 IEEE International Conferences on Internet of Things, iThings 2021, IEEE Green Computing and Communications, GreenCom 2021, IEEE Cyber, Physical and Social Computing, CPSCom 2021 and IEEE Smart Data, SmartData 2021
編集者James Zheng, Xiao Liu, Tom Hao Luan, Prem Prakash Jayaraman, Haipeng Dai, Karan Mitra, Kai Qin, Rajiv Ranjan, Sheng Wen
出版社Institute of Electrical and Electronics Engineers Inc.
ページ254-261
ページ数8
ISBN(電子版)9781665417624
DOI
出版ステータスPublished - 2021
イベント2021 IEEE Congress on Cybermatics: 14th IEEE International Conferences on Internet of Things, iThings 2021, 17th IEEE International Conference on Green Computing and Communications, GreenCom 2021, 2021 IEEE International Conference on Cyber Physical and Social Computing, CPSCom 2021 and 7th IEEE International Conference on Smart Data, SmartData 2021 - Virtual, Melbourne, Australia
継続期間: 2021 12月 62021 12月 8

出版物シリーズ

名前Proceedings - IEEE Congress on Cybermatics: 2021 IEEE International Conferences on Internet of Things, iThings 2021, IEEE Green Computing and Communications, GreenCom 2021, IEEE Cyber, Physical and Social Computing, CPSCom 2021 and IEEE Smart Data, SmartData 2021

Conference

Conference2021 IEEE Congress on Cybermatics: 14th IEEE International Conferences on Internet of Things, iThings 2021, 17th IEEE International Conference on Green Computing and Communications, GreenCom 2021, 2021 IEEE International Conference on Cyber Physical and Social Computing, CPSCom 2021 and 7th IEEE International Conference on Smart Data, SmartData 2021
国/地域Australia
CityVirtual, Melbourne
Period21/12/621/12/8

ASJC Scopus subject areas

  • 人工知能
  • コンピュータ ネットワークおよび通信
  • コンピュータ サイエンスの応用
  • 情報システムおよび情報管理
  • 再生可能エネルギー、持続可能性、環境
  • 安全性、リスク、信頼性、品質管理
  • 通信

フィンガープリント

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