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.

侧渠道是任何不可避免地且无意间将信息泄露给计算机或通信系统中未经授权的用户的过程。 秘密渠道是任何机制，尽管这种机制被禁止进行通信，但两方同时访问相同计算机的同时访问相同的计算机。 两个渠道的示例及其存在的示例使我们的计算和通信基础架构的安全降低：侧渠道使攻击者能够收集他们无法访问的敏感信息，并且掩盖通道可以在用户之间进行未经授权的披露。该项目使工程师能够衰减侧面和转换通道，从而使我们的电子基础设施较少容易受到外部攻击和内部泄漏的影响。在此过程中，该项目可以在信息理论，计算机体系结构和通信网络中研究人员之间进行新的合作。该项目通过研究机会和改进的专业社会的指导计划扩大了代表性不足的群体的参与。该项目从理论上讲是对侧面和秘密渠道信息的研究。 从历史上看，信息理论为减轻侧面和秘密渠道提供了相对较少的帮助。这部分是因为目前尚不清楚如何量化通过侧通道泄漏的信息量，部分原因是许多侧面和掩护通道涉及可以主动控制通道的接收器。此类接收器尚不清楚。要解决这两种障碍，该项目开发了一个最近提供的指标，用于测量侧通道中的泄漏，这在操作上是合理的且易于计算的。该项目还开发了结果，使人们能够预测主动接收者的行为。该项目最终将这些结果应用于涵盖通信网络和多核处理器的三个特定方案。

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

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.

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