CPS: Medium: Distorting the adversary's view: a CPS approach to privacy and security
CPS: Medium: Distorting the adversary's view: a CPS approach to privacy and security
批准号:
1740047
负责人:
Christina Fragouli
金额:
$97.76万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-01 至 2021-08-31
中文摘要
点击翻译按钮获取中文摘要
英文摘要
This project develops a novel Cyber Physical System (CPS) centric approach to privacy and security for wireless networked CPS systems, by reconciling the low-delay and low-jitter requirements of CPS applications with the requirements imposed by security and privacy. Our starting observation is that, in CPS, an adversary's primary goal is not to learn all the raw data, but instead core attributes, such as the state or control actions that are derived from data. Building on this observation, we propose to use a distortion measure for security that maximizes the difference between the eavesdropper's estimate and the true value of the function computing the attributes of interest, reducing the adversary's ability to disrupt normal operation of CPS. We posit that we can protect these core attributes with fewer resources than needed to protect all the raw data. Ensuring secure and private information exchange over networked CPS systems is essential to building a thriving ecosystem of applications that range from autonomous cars and drones, to the Internet-of-Things (IoT), to immersive environments such as augmented reality for health, education, and collaboration. Our educational plan engages not only graduate students and postdocs but also high school and undergraduate students. It also reaches out to engineers and the lay public, by providing open source implementations of our algorithms making them available both to industry and hobbyists. The project considers both passive and active attacks. We will quantify novel privacy and security measures for CPS systems that are based on distortion measurements in a metric space; we will develop fundamental bounds as well as low complexity and low overhead coding schemes; we will quantify the disruptive power of active adversaries and design pro-active and retro-active defense mechanisms; and we will illustrate our approach over a flagship application, drone localization. Our approach will offer an alternative to wireless network encryption methods, by designing for low-delay, low-jitter requirements of CPS.
期刊论文(40)
专著(0)
科研奖励(0)
会议论文
登录
查看更多内容
Privacy Against Adversarial Classification in Cyber-Physical Systems
网络物理系统中针对对抗性分类的隐私
DOI:
10.1109/cdc42340.2020.9303960
发表时间:
2020
期刊:
2020 59th IEEE Conference on Decision and Control (CDC
影响因子:
--
作者:
[Murguia, Carlos, Tabuada, Paulo]
通讯作者:
Tabuada, Paulo
Privacy in Index Coding: $k$ -Limited-Access Schemes
索引编码中的隐私:$k$ - 有限访问方案
DOI:
10.1109/tit.2019.2957577
发表时间:
2020
期刊:
IEEE Transactions on Information Theory
影响因子:
2.5
作者:
[Karmoose, Mohammed, Song, Linqi, Cardone, Martina, Fragouli, Christina]
通讯作者:
Fragouli, Christina
Symmetries and privacy in control over the cloud: uncertainty sets and side knowledge *
云控制中的对称性和隐私:不确定性集和辅助知识*
DOI:
10.1109/cdc40024.2019.9029609
发表时间:
2019
期刊:
Conference on Decision and Control (CDC
影响因子:
--
作者:
[Sultangazin, Alimzhan, Tabuada, Paulo]
通讯作者:
Tabuada, Paulo
Shuffled model of differential privacy in federated learnin
联邦学习中差分隐私的洗牌模型
DOI:
--
发表时间:
2021
期刊:
AISTATS
影响因子:
--
作者:
[Girgis, Antonious M, Data, Deepesh, Diggavi, Suhas, Kairouz, Peter, and Suresh, Theerta.]
通讯作者:
and Suresh, Theerta.
Hiding Identities: Estimation Under Local Differential Privacy
隐藏身份:本地差分隐私下的估计
DOI:
10.1109/isit44484.2020.9174332
发表时间:
2020
期刊:
IEEE International Symposium on Information Theory (ISIT
影响因子:
--
作者:
[Girgis, Antonious M., Data, Deepesh, Diggavi, Suhas]
通讯作者:
Diggavi, Suhas
共 34 条
RINGS: Ensuring Reliability in mmWave Networks
-
批准号:2146838
-
项目类别:Continuing Grant
-
资助金额:$100.0万
-
财政年份:2022
-
负责人:Christina Fragouli
-
依托单位:
CIF: Small: Group Testing for Epidemics Control
-
批准号:2146828
-
项目类别:Standard Grant
-
资助金额:$50.0万
-
财政年份:2022
-
负责人:Christina Fragouli
-
依托单位:
CIF: Small: Compression for Learning over networks
-
批准号:2007714
-
项目类别:Standard Grant
-
资助金额:$52.39万
-
财政年份:2020
-
负责人:Christina Fragouli
-
依托单位:
CIF: Small: Collaborative Research: From Pliable to Content-Type Coding
-
批准号:1527550
-
项目类别:Standard Grant
-
资助金额:$20.0万
-
财政年份:2015
-
负责人:Christina Fragouli
-
依托单位:
CIF: Small: Wireless Network Security: Building on Erasures
-
批准号:1321120
-
项目类别:Standard Grant
-
资助金额:$49.74万
-
财政年份:2013
-
负责人:Christina Fragouli
-
依托单位:
海外基金