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Exploring Power Network Attributes for Information Forensics

探索信息取证的电力网络属性

基本信息

批准号：
1309623
负责人：
Min Wu
金额：
$ 36万
依托单位：
University of Maryland, College Park
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2013
资助国家：
美国
起止时间：
2013-09-01 至 2017-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1309623&HistoricalAwards=false
关键词：
Exploring Power Network Attributes Information

项目摘要

Objective: The objective of this project is to investigate the scientific and technological foundations on time, location and integrity of sensor recordings, by exploiting novel intrinsic fingerprints in the environment. An example is the small random-like fluctuations of the electricity frequency known as the Electric Network Frequency (ENF). These environmental fingerprints reflect the attributes and conditions of the power grid and become naturally "embedded" into video, audio or other types of sensor signals at the time of recording. They carry time and location information and may facilitate integrity verification of the primary sensing data. Answering questions about the time, location, and integrity of sensor recordings find important applications in crime solving, counter-terrorism, journalism, infrastructure monitoring, smart grid management, and other commercial operations.Intellectual merit: The intellectual merit lies on exploring the nearly unchartered research area of forensic evidences in the environment, by drawing synergy across multiple disciplines including signal processing, machine learning, sensor circuits and systems, power engineering, and information forensics/security. The research exploration and technology development of this project are transformative and interdisciplinary in nature. Broader impacts: The broader impacts are two folds: through engaging students, especially female and under-represented ones, in exploratory research, the project's seamless integration of research with education and outreach will prepare the future generation of engineering workforce with interdisciplinary strength; through new technologies and tools developed to advance information forensics, the project has a high potential to benefit a number of applications of global and societal importance.

目的：本项目的目的是通过利用环境中新的固有指纹，探索传感器记录的时间、位置和完整性的科学和技术基础。一个例子是电力频率的小幅随机波动，称为电网频率(ENF)。这些环境指纹反映了电网的属性和状况，并在记录时自然地被嵌入到视频、音频或其他类型的传感器信号中。它们携带时间和位置信息，并且可以促进初级感测数据的完整性验证。回答有关传感器记录的时间、位置和完整性的问题在解决犯罪、反恐、新闻、基础设施监控、智能电网管理和其他商业运营中具有重要应用。智力优势：智力优势在于探索环境中几乎未知的法医证据研究领域，通过跨信号处理、机器学习、传感器电路和系统、电力工程和信息取证/安全等多个学科的协同作用。该项目的研究、探索和技术开发具有变革性和跨学科的性质。更广泛的影响：更广泛的影响有两个方面：通过吸引学生，特别是女性和代表性不足的学生参与探索性研究，该项目将研究与教育和外联无缝结合，将培养具有跨学科能力的下一代工程劳动力；通过开发新的技术和工具来促进信息取证，该项目很有可能使一些具有全球和社会重要性的应用程序受益。

项目成果

期刊论文数量（3）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Location Signatures That You Don't See: Highlights from the IEEE Signal Processing Cup 2016 Student Competition [SP Education]

你看不到的位置特征：2016 年 IEEE 信号处理杯学生竞赛亮点 [SP Education]

DOI：
10.1109/msp.2016.2581738
发表时间：
2016
期刊：
IEEE Signal Processing Magazine
影响因子：
14.9
作者：
Wu, Min;Hajj-Ahmad, Adi;Kirchner, Matthias;Ren, Yanpin;Zhang, Changshui;Campisi, Patrizio
通讯作者：
Campisi, Patrizio

Factors Affecting ENF Capture in Audio