CRII: SaTC: Transparent Capture and Aggregation of Secure Data Provenance for Smart Devices

CRII：SaTC：智能设备安全数据来源的透明捕获和聚合

• 批准号: 1657534
• 负责人: Adam Bates
• 金额: $ 17.47万
• 依托单位: University of Illinois at Urbana-Champaign
• 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
• 起止时间: 2017-03-01 至 2020-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1657534&HistoricalAwards=false
• 关键词: CRII; SaTC; Transparent; Capture; Aggregation

Computers are increasingly pervasive and diverse, embedded in devices ranging from smart phones and wearable computers to home automation devices and automotive systems. This explosive growth has far outpaced the speed with which device behaviors can be analyzed and understood, creating unprecedented opportunities for "Internet of Things" devices to engage in nefarious activities such as violating users' privacy or spreading malware. This project is designing and implementing new frameworks that track the provenance (i.e., history) of data processing and communications in systems of smart devices. To facilitate the identification of malicious behaviors, the project is developing non-invasive techniques for extracting device provenance, and presenting a public accountability infrastructure through which the history of interactions between smart devices can be analyzed.In light of the great diversity of computing platforms in this environment, the efficient extraction of fine-grained data provenance is difficult. To overcome these challenges, the researchers are designing and implementing minimally-invasive mechanisms and associated algorithms for the observation of smart device activity at multiple system layers. The expected results include the development of a retrofit mechanism that leverages program instrumentation to enable complete provenance mediation for commodity-off-the-shelf smart devices, and a network mediation point that monitors inter-device communication in order to extract network provenance from systems of devices. Finally, the project is developing algorithms and protocols to securely extract and aggregate device provenance to a centralized repository, enabling provenance-based crowd-sourced monitoring of the Internet of Things. This work will not only establish foundations for trust in the functionality of smart devices, but also enable further research in provenance-based analytics.

计算机越来越普遍和多样化，嵌入到从智能手机和可穿戴计算机到家庭自动化设备和汽车系统等设备中。这种爆炸性增长远远超过了设备行为分析和理解的速度，为“物联网”设备从事侵犯用户隐私或传播恶意软件等邪恶活动创造了前所未有的机会。该项目正在设计和实施新的框架，用于跟踪智能设备系统中数据处理和通信的来源（即历史）。为了促进识别恶意行为，该项目正在开发用于提取设备来源的非侵入性技术，并提出一个公共问责基础设施，通过该基础设施可以分析智能设备之间的交互历史。在这种环境下，高效提取细粒度数据来源是很困难的。为了克服这些挑战，研究人员正在设计和实施微创机制和相关算法，以观察多个系统层的智能设备活动。预期结果包括开发一种改造机制，该机制利用程序检测来实现对现成商品智能设备的完整来源中介，以及一个网络中介点，用于监视设备间通信，以便从系统中提取网络来源。设备。最后，该项目正在开发算法和协议，以安全地提取设备来源并将其聚合到集中存储库，从而实现基于来源的物联网众包监控。这项工作不仅将为人们对智能设备功能的信任奠定基础，而且还有助于对基于来源的分析进行进一步的研究。

项目成果

AliDrone: Enabling Trustworthy Proof-of-Alibi for Commercial Drone Compliance

AliDrone：为商业无人机合规性提供可靠的不在场证明

• DOI: 10.1109/icdcs.2018.00086
• 发表时间: 2018-07-01
• 期刊: 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS)
• 作者: Tianyuan Liu;Avesta Hojjati;Adam Bates;K. Nahrstedt
• 通讯作者: K. Nahrstedt

Valve: Securing Function Workfows on Serverless Computing Platforms

Valve：保护无服务器计算平台上的功能工作流

• DOI: 3366423.3380173
• 发表时间: 2020-01
• 期刊: The Web Conference
• 作者: Datta, Pubali;Kumar, Prabuddha;Morris, Tristan;Grace, Michael;Rahmati, Amir;Bates, Adam
• 通讯作者: Bates, Adam

Provenance for Intent-Based Networking

基于意图的网络的起源

• 发表时间: 2020-01
• 期刊: Proceedings of the IEEE Conference on Network Softwarization
• 作者: Ujcich, Benjamin E.;Bates, Adam;Sanders, William H.
• 通讯作者: Sanders, William H.

Runtime Analysis of Whole-System Provenance

整个系统来源的运行时分析

• DOI: 10.1145/3243734.3243776
• 发表时间: 2018-01-15
• 期刊: Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security
• 作者: Thomas Pasquier;Xueyuan Han;Thomas Moyer;Adam Bates;O. Hermant;D. Eyers;J. Bacon;M. Seltzer
• 通讯作者: M. Seltzer

A Provenance Model for the European Union General Data Protection Regulation

欧盟通用数据保护法规的来源模型

• DOI: 10.1007/978-3-319-98379
• 发表时间: 2019-07
• 期刊: Provenance and Annotation of Data and Processes
• 作者: Ujcich, Benjamin E.;Bates, Adam;Sanders, William H.
• 通讯作者: Sanders, William H.