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NeTS: JUNO2: Collaborative Research: STEAM: Secure and Trustworthy Framework for Integrated Energy and Mobility in Smart Connected Communities

NeTS: JUNO2: Collaborative Research: STEAM: Secure and Trustworthy Framework for Integrated Energy and Mobility in Smart Connected Communities
NetS:JUNO2:协作研究:STEAM:智能互联社区中集成能源和移动性的安全可信框架
批准号:
1818942
负责人:
Sajal Das
金额:
$24.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-09-01 至 2023-08-31

项目摘要

项目成果

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中文摘要
翻译
数据驱动分析、物联网(IoT)和网络物理系统(CPS)的快速发展正在推动越来越多的智能互联社区(SCC)应用,包括智能交通和智能能源。 然而,在没有适当安全机制的情况下部署这种技术解决方案,使它们容易受到数据完整性和隐私攻击,最近发生的大量事件就是如此。如果处理不当,这种攻击不仅会削弱SCC的运营,还会影响客户愿意共享数据的程度。这反过来将使SCC应用程序的可信度非常具有挑战性。为了解决这个问题,来自美国和日本的研究人员在JUNO2计划下的协同团队将在这个名为STEAM(集成能源和移动性的安全和可信框架)的项目上进行合作,以开发一个框架,以确保智能和互联社区中的数据隐私,数据完整性和可信度。此次合作为该项目提供了大量来自日本的汽车(运输)数据,并可以访问日本的测试平台。虽然目标应用是智能移动和智能能源(选择是故意利用日本和美国在这两个领域的互补优势),但所提出的技术和解决方案对其他领域具有广泛的适用性,例如智能医疗。STEAM项目的新奇在于其在SCC应用程序中处理安全性和可信性的集成方法。具体而言,研究团队将开发创新的隐私保护算法和模型,用于异常检测,应用程序提供商用于数据完整性和信息保证的信任和声誉评分。为了实现这一目标,他们将研究安全,隐私,信任级别,资源和性能之间的权衡,使用两个示例应用程序在社区中的智能移动和智能能源交换。最后,他们将设计一个模块化,安全和值得信赖的中间件架构,实现隐私保护算法,资源约束,数据源或内容和决策方案的可信度。该项目可以访问来自德克萨斯州、加州和爱尔兰的智能仪表数据以及来自日本的大量汽车数据。 该评估计划包括将该项目的异常检测和可信决策算法集成到智能车辆路线规划应用程序中,并在日本的插电式电动汽车试验台上使用交互式能源系统。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
The rapid evolution of data-driven analytics, Internet of things (IoT) and cyber-physical systems (CPS) are fueling a growing set of Smart and Connected Communities (SCC) applications, including for smart transportation and smart energy. However, the deployment of such technological solutions without proper security mechanisms makes them susceptible to data integrity and privacy attacks, as observed in a large number of recent incidents. If not addressed properly, such attacks will not only cripple SCC operations but also influence the extent to which customers are willing to share data. This in turn will make trustworthiness in SCC applications very challenging. To address this, a synergistic team of researchers from the US and Japan, under the JUNO2 program, will collaborate on this project, called STEAM (Secure and Trustworthy framework for integrated Energy and Mobility) to develop a framework to ensure data privacy, data integrity, and trustworthiness in smart and connected communities. The collaboration provides the project with a significant amount of automotive (transportation) data from Japan, and also access to a testbed in Japan. Although the target applications are smart mobility and smart energy (the choice is deliberate to exploit the complementary strengths of Japan and US in these two domains), the proposed techniques and solutions have wide applicability to other domains, such as smart healthcare. The novelty of the STEAM project lies in its integrated approach to handling security and trustworthiness in SCC applications. Specifically, the research team will develop innovative privacy-preserving algorithms and models for anomaly detection, trust and reputation scoring used by application providers for data integrity and information assurance. Towards that goal, they will study trade-offs between security, privacy, trust levels, resources, and performance using two exemplar applications in smart mobility and smart energy exchange in communities. Finally, they will design a modular, secure and trustworthy middleware architecture that implements privacy-preserving algorithms, resource constraints, and trustworthiness of data sources or content and decision-making schemes. The project has access to smart meter data from Texas, California, and Ireland and a large volume of automobile data from Japan. The evaluation plan includes integration of the project's anomaly detection and trustworthy decision-making algorithms into a smart vehicle route planning application and a transactive energy system in a plug-in electric vehicle testbed in Japan.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(19)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1109/tnsm.2020.2969086
发表时间: 2020-01
期刊: IEEE Transactions on Network and Service Management
影响因子: 5.3
作者: [V. Shah;Brian Luciano;S. Silvestri;Shameek Bhattacharjee;Sajal K. Das]
通讯作者: V. Shah;Brian Luciano;S. Silvestri;Shameek Bhattacharjee;Sajal K. Das
Resilience Against Bad Mouthing Attacks in Mobile Crowdsensing Systems via Cyber Deception
移动群体感知系统中通过网络欺骗抵御恶意攻击的能力
DOI: 10.1109/wowmom51794.2021.00030
发表时间: 2021
期刊: IEEE International Symposium on World of Wireless Mobile and Multimedia Networks (WoWMoM
影响因子: --
作者: [Roy, Prithwiraj, Bhattacharjee, Shameek, Alsheakh, Hussein, Das, Sajal K.]
通讯作者: Das, Sajal K.
A Diversity Index based Scoring Framework for Identifying Smart Meters Launching Stealthy Data Falsification Attacks
基于多样性指数的评分框架,用于识别发起隐形数据伪造攻击的智能电表
DOI: --
发表时间: 2021
期刊: ACM Asia Conference on Computer and Communications Security
影响因子: --
作者: [S. Bhattacharjee, V. P.]
通讯作者: S. Bhattacharjee, V. P.
DOI: 10.1109/smartcomp.2019.00063
发表时间: 2019
期刊: 2019 IEEE International Conference on Smart Computing (SMARTCOMP
影响因子: --
作者: [Wilbur, Michael, Dubey, Abhishek, Bruno, Leao, Bhattacharjee, Shameek.]
通讯作者: Bhattacharjee, Shameek.
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