A Privacy-Aware Design for the Vehicle-to-Grid Framework

被引:19
|
作者
Ghosh, Dipayan P. [1 ]
Thomas, Robert J. [1 ]
Wicker, Stephen B. [1 ]
机构
[1] Cornell Univ, Sch Elect & Comp Engn, Ithaca, NY 14853 USA
关键词
D O I
10.1109/HICSS.2013.54
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The vehicle-to-grid (V2G) framework proposes integration of battery-powered electric drive vehicles into the grid, enabling them to be recharged as necessary and to act as suppliers in the ancillary service electricity markets. This is expected to create incentives for the production and adoption of electric vehicles in the automotive industry. V2G frameworks require that the utility company or a third party aggregator has access to each vehicle's charging status via a two-way communication network for billing and planning purposes. We establish that there exist consumer privacy risks associated with current concepts for V2G implementation and argue that consumer preferences and behaviors can be inferred from charging information if privacy is not a primary concern from the outset of V2G design. Finally, we outline a privacy-aware architecture for V2G systems.
引用
收藏
页码:2283 / 2291
页数:9
相关论文
共 50 条
  • [41] CampER: An Effective Framework for Privacy-Aware Deep Entity Resolution
    Guo, Yuxiang
    Chen, Lu
    Zhou, Zhengjie
    Zheng, Baihua
    Fang, Ziquan
    Zhang, Zhikun
    Mao, Yuren
    Gao, Yunjun
    PROCEEDINGS OF THE 29TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, KDD 2023, 2023, : 626 - 637
  • [42] An Efficient Privacy-Aware Split Learning Framework for Satellite Communications
    Sun, Jianfei
    Wu, Cong
    Mumtaz, Shahid
    Tao, Junyi
    Cao, Mingsheng
    Wang, Mei
    Frascolla, Valerio
    IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2024, 42 (12) : 3355 - 3365
  • [43] Privacy-Aware Process Performance Indicators: Framework and Release Mechanisms
    Kabierski, Martin
    Fahrenkrog-Petersen, Stephan A.
    Weidlich, Matthias
    ADVANCED INFORMATION SYSTEMS ENGINEERING (CAISE 2021), 2021, 12751 : 19 - 36
  • [44] Design Framework for Privacy-Aware Demand-Side Management With Realistic Energy Storage Model
    Avula, Ramana R.
    Chin, Jun-Xing
    Oechtering, Tobias J.
    Hug, Gabriela
    Mansson, Daniel
    IEEE TRANSACTIONS ON SMART GRID, 2021, 12 (04) : 3503 - 3513
  • [45] Design of an Anomaly Detection Framework for Delay and Privacy-Aware Blockchain-Based Cloud Deployments
    Nagarjun, A. Venkata
    Rajkumar, Sujatha
    IEEE ACCESS, 2024, 12 : 84843 - 84862
  • [46] Privacy-Aware Kalman Filtering
    Song, Yang
    Wang, Chong Xiao
    Tay, Wee Peng
    2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2018, : 4434 - 4438
  • [47] An automated consistency management approach for a privacy-aware electric vehicle architecture
    Stancke, Jonathan
    Plappert, Christian
    Jaeger, Lukas
    MICROPROCESSORS AND MICROSYSTEMS, 2024, 109
  • [48] Privacy-Aware QoE Evaluation
    Zhou, Liang
    Wei, Xin
    Cui, Jingwu
    Zheng, Baoyu
    2017 IEEE 85TH VEHICULAR TECHNOLOGY CONFERENCE (VTC SPRING), 2017,
  • [49] Towards Privacy-Aware Keyboards
    Buza, Krisztian
    Kis, Piroska B.
    PROCEEDINGS OF THE 10TH INTERNATIONAL CONFERENCE ON COMPUTER RECOGNITION SYSTEMS CORES 2017, 2018, 578 : 140 - 147
  • [50] On privacy-aware eScience workflows
    Belhajjame, Khalid
    Faci, Noura
    Maamar, Zakaria
    Buregio, Vanilson
    Soares, Edvan
    Barhamgi, Mahmoud
    COMPUTING, 2020, 102 (05) : 1171 - 1185