CIF:Medium:Collaborative Research:Maximal Leakage and Active Receivers for Side- and Covert Channel Analysis

CIF：中：协作研究：用于旁路和隐蔽信道分析的最大泄漏和有源接收器

• 批准号: 1704443
• 负责人: Aaron Wagner
• 金额: $ 80万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-06-01 至 2023-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1704443&HistoricalAwards=false
• 关键词: CIF; Medium; Collaborative; Research; Maximal

A side-channel is any process that inevitably and unintentionally leaks information to an unauthorized user in a computer or communication system. A covert channel is any mechanism through which two parties simultaneously accessing the same computer intentionally communicate, despite this mechanism being disallowed for communication. Examples of both channels abound, and their presence makes our computation and communication infrastructure less secure: side channels allow attackers to glean sensitive information that they would not otherwise be able to access, and covert channels enable unauthorized disclosure between users. This project enables engineers to attenuate side- and convert channels, thereby making our electronic infrastructure less vulnerable to external attack and internal leaks. In the process, the project enables a new collaboration between researchers in information theory, computer architecture, and communication networks. The project broadens participation of under-represented groups, especially women, through research opportunities and an improved mentoring program for a professional society.This project approaches the study of side- and covert channels information theoretically. Historically, information theory has provided relatively little assistance toward mitigating side- and covert channels. This is partly because it is unclear how to quantify the amount of information leaked through a side channel and partly because many side- and covert channels involve a receiver that can actively control the channel. Such receivers are not well understood.To address these two impediments, the project develops a recently-proposed metric for measuring leakage in side-channels that is operationally justified and easily computed. The project also develops results that enable one to predict how active receivers will act. The project culminates in the application of these results to three specific scenarios spanning communication networks and multi-core processors.

侧信道是指在计算机或通信系统中不可避免地和无意地将信息泄露给未经授权的用户的任何进程。 隐蔽通道（英语：covert channel）是一种机制，通过这种机制，同时访问同一台计算机的两方可以有意地进行通信，尽管这种机制不允许进行通信。 这两种通道的例子比比皆是，它们的存在使我们的计算和通信基础设施不那么安全：侧通道允许攻击者收集他们无法访问的敏感信息，而隐蔽通道允许用户之间未经授权的泄露。该项目使工程师能够衰减侧通道和转换通道，从而使我们的电子基础设施不那么容易受到外部攻击和内部泄漏。在这个过程中，该项目使信息理论，计算机体系结构和通信网络的研究人员之间的新合作成为可能。该项目通过研究机会和改进专业协会的指导方案，扩大了代表性不足的群体，特别是妇女的参与。 从历史上看，信息理论提供了相对较少的援助，以减轻侧和隐蔽渠道。这部分是因为不清楚如何量化通过侧信道泄露的信息量，部分是因为许多侧信道和隐蔽信道涉及可以主动控制信道的接收器。为了解决这两个障碍，该项目开发了一个最近提出的用于测量侧通道泄漏的度量标准，该度量标准在操作上是合理的，并且易于计算。该项目还开发了一些结果，使人们能够预测主动接收器将如何行动。该项目最终将这些结果应用于跨越通信网络和多核处理器的三个特定场景。

项目成果

Optimal Mechanisms Under Maximal Leakage

• DOI: 10.1109/cns48642.2020.9162276
• 发表时间: 2020-06
• 期刊: 2020 IEEE Conference on Communications and Network Security (CNS)
• 作者: Benjamin Wu;Aaron B. Wagner;G. E. Suh

Strong Asymptotic Composition Theorems for Sibson Mutual Information

Sibson互信息的强渐近复合定理

• DOI: 10.1109/isit44484.2020.9174456
• 发表时间: 2020
• 期刊: 2020 IEEE International Symposium on Information Theory (ISIT
• 作者: Wu, Benjamin;Wagner, Aaron B.;Suh, G. Edward;Issa, Ibrahim
• 通讯作者: Issa, Ibrahim

An Operational Approach to Information Leakage

• DOI: 10.1109/tit.2019.2962804
• 发表时间: 2020-03-01
• 期刊: IEEE TRANSACTIONS ON INFORMATION THEORY
• 影响因子: 2.5
• 作者: Issa, Ibrahim;Wagner, Aaron B.;Kamath, Sudeep
• 通讯作者: Kamath, Sudeep

Estimating Quantum Entropy

估计量子熵

• DOI: 10.1109/jsait.2020.3015235
• 发表时间: 2020
• 期刊: IEEE Journal on Selected Areas in Information Theory
• 作者: Acharya, Jayadev;Issa, Ibrahim;Shende, Nirmal V.;Wagner, Aaron B.
• 通讯作者: Wagner, Aaron B.

Guessing Outputs of Dynamically Pruned CNNs Using Memory Access Patterns

使用内存访问模式猜测动态修剪的 CNN 的输出

• DOI: 10.1109/lca.2021.3101505
• 发表时间: 2021
• 期刊: IEEE Computer Architecture Letters
• 影响因子: 2.3
• 作者: Wu, Benjamin;Tiwari, Trishita;Suh, G. Edward;Wagner, Aaron B.
• 通讯作者: Wagner, Aaron B.