EAGER: Collaborative: Algorithmic Framework for Anomaly Detection in Interdependent Networks
EAGER: Collaborative: Algorithmic Framework for Anomaly Detection in Interdependent Networks
批准号:
1646890
负责人:
Nina Fefferman
金额:
$9.99万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-09-01 至 2019-08-31
中文摘要
现代关键基础设施依赖于许多不同类型网络之间成功的相互依赖功能。例如,互联网依赖于接入电网,而电网又依赖于电网通信网络和能源生产网络。出于这个原因,网络科学研究人员已经开始研究关键基础设施作为网络的网络或多层网络的稳健性。网络异常检测系统的研究主要集中在单一网络结构(特别是作为单一网络的Internet)上。在这些方法中,一些有前途的检测算法依赖于许多参与者之间的分散和分布式协调,比独立的并行和集中式算法的结果有了显着改善。该项目涉及对多层网络相对于单层网络结构所带来的异常检测的不同挑战和机遇的严格分析,特别关注如何有效地利用跨层信息来提高效率和检测,以及跨层威胁如何产生漏洞。该项目开发了一个通用框架,可用于多种应用程序,以检测对信息流的大规模威胁,以增强安全性。通过提高国家网络基础设施和其他相互依存的关键基础设施(如电网)的弹性,这有可能为社会带来重大利益。网络安全社区与网络科学社区的概念和思想的结合将有助于两个领域的研究人员更好地理解现实问题,并了解彼此的问题、结果和技术。
英文摘要
Modern critical infrastructure relies on successful interdependent function among many different types of networks. For example, the Internet depends on access to the power grid, which in turn depends on the power-grid communication network and the energy production network. For this reason, network science researchers have begun examining the robustness of critical infrastructure as a network of networks, or a multilayer network. Research in network anomaly detection systems has focused on single network structures (specifically, the Internet as a single network). Among these methods, some promising detection algorithms rely on decentralized and distributed coordination among many participants, improving meaningfully over results from independent parallel and centralized algorithms. The project involves rigorous analysis of the different challenges and opportunities for anomaly detection posed by multilayer networks relative to single network structures, with a particular focus on how cross-layer information can be effectively used to improve both efficiency and detection as well as how cross-layer threats can create vulnerabilities. The project develops a general framework that can be used in multiple applications to detect large-scale threats to information flow for enhanced security. This has the potential for significant benefit to society through its contribution to enhanced resiliency in the nation's cyber infrastructure and other interdependent critical infrastructure such as the power grid. The combination of concepts and ideas from the cybersecurity community with the network science community will help researchers in both fields to better understand the realistic problems and be aware of each other's problems, results, and techniques.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
Anomaly detection through information sharing under different topologies
通过不同拓扑下的信息共享进行异常检测
DOI:
10.1186/s13635-017-0056-5
发表时间:
2017
期刊:
EURASIP Journal on Information Security
影响因子:
3.6
作者:
[Gallos, Lazaros K., Korczyński, Maciej, Fefferman, Nina H.]
通讯作者:
Fefferman, Nina H.
DOI:
10.1073/pnas.1900219116
发表时间:
2019-09
期刊:
Proceedings of the National Academy of Sciences
影响因子:
--
作者:
[L. Gallos;S. Havlin;H. Stanley;N. Fefferman]
通讯作者:
L. Gallos;S. Havlin;H. Stanley;N. Fefferman
PIPP Phase I: Predicting Emergence in Multidisciplinary Pandemic Tipping-points (PREEMPT)
-
批准号:2200140
-
项目类别:Standard Grant
-
资助金额:$99.98万
-
财政年份:2022
-
负责人:Nina Fefferman
-
依托单位:
Collaborative Research: A Workshop on Pre-emergence and the Predictions of Rare Events in Multiscale, Complex, Dynamical Systems
-
批准号:2114651
-
项目类别:Standard Grant
-
资助金额:$8.18万
-
财政年份:2021
-
负责人:Nina Fefferman
-
依托单位:
RAPID: Modeling the Coupled Social and Epidemiological Networks that Determine the Success of Behavioral Interventions on Limiting Spread of COVID-19
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批准号:2028710
-
项目类别:Standard Grant
-
资助金额:$19.89万
-
财政年份:2020
-
负责人:Nina Fefferman
-
依托单位:
RAPID: Modeling Zika Control Effectiveness with Feedback in Risk Perception and Associated Demand across Scales of Intervention
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批准号:1640951
-
项目类别:Standard Grant
-
资助金额:$19.0万
-
财政年份:2016
-
负责人:Nina Fefferman
-
依托单位:
RAPID: Collaborative Research: Learning about Infectious Diseases through Online Participation in a Virtual Epidemic
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批准号:1508981
-
项目类别:Standard Grant
-
资助金额:$2.08万
-
财政年份:2015
-
负责人:Nina Fefferman
-
依托单位:
海外基金