EAGER: Collaborative Research: E-Witness: Preserve and Prove Forensic Soundness of Digital Evidence

EAGER:协作研究:电子证人:保存并证明数字证据的法证可靠性

基本信息

  • 批准号:
    1742919
  • 负责人:
  • 金额:
    $ 12.5万
  • 依托单位:
  • 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:
    2017-10-01 至 2020-09-30
  • 项目状态:
    已结题

项目摘要

This project seeks to explore the challenges of developing E-Witness - a system that allows civilians to use their smart devices to collect forensically sound multimedia evidence. In order to be considered authentic and forensically sound, a digital evidence needs to have a proof of being untampered and the time and location of the event needs to be attested in a way that it is immutable. Such research on forensically sound and anonymous evidence gathering is hard due to various challenging requirements: user friendly application interface, unbiased, collusion-resistant and privacy-preserving time-stamping service as well as accurate location attestation. The effectiveness of each aspect needs to be proved to build a robust system. The overarching reward of this project is its ability to record and validate facts in real-time while bringing forensic accountability to such collected evidence. The building blocks of E-Witness consist of: (a) a secure smart phone application, (b) a time-stamping service implemented as a public blockchain maintained by individual miners, and (c) a location-attestation service that provides confidence on the truthfulness of the location reported by the evidence device. A prototype will be developed and performance analysis will be performed over a testbed deployment to ensure correctness of all components of the system. A pilot study involving University users will be performed to identify the challenges of a large-scale deployment.
该项目旨在探索开发E-Witness的挑战--这是一个允许平民使用智能设备收集具有取证效力的多媒体证据的系统。为了被认为是真实的和取证合理的,数字证据需要有未被篡改的证明,并且事件的时间和地点需要以不可改变的方式证明。由于各种具有挑战性的要求:用户友好的应用界面、无偏见、抗共谋和隐私保护的时间戳服务以及准确的位置证明,对取证可靠和匿名证据收集的研究是困难的。需要证明每个方面的有效性才能构建一个健壮的系统。这个项目最重要的回报是它能够实时记录和验证事实,同时对收集的证据进行法医问责。E-Witness的组成部分包括:(A)安全的智能手机应用程序;(B)作为公共区块链由个人矿工维护的时间戳服务;以及(C)提供对证据装置所报告位置的真实性的信心的位置证明服务。将开发一个原型,并在试验台部署上进行性能分析,以确保系统所有组件的正确性。将进行一项涉及大学用户的试点研究,以确定大规模部署的挑战。

项目成果

期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
E-Witness: Preserve and Prove Forensic Soundness of Digital Evidence
电子证人:保存并证明数字证据的法证可靠性
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Shweta Jain其他文献

A Multiarmed Bandit Based Incentive Mechanism for a Subset Selection of Customers for Demand Response in Smart Grids
智能电网需求响应中基于多臂强盗的客户子集选择激励机制
IMPLEMENTATION OF PROBABILITY-BASED PRIORITY-DRIVEN STRIDE SCHEDULING IN DISTRIBUTED SYSTEM
分布式系统中基于概率的优先级驱动步长调度的实现
  • DOI:
    10.26483/ijarcs.v8i8.4776
  • 发表时间:
    2017
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Shweta Jain
  • 通讯作者:
    Shweta Jain
MAIRE - A Model-Agnostic Interpretable Rule Extraction Procedure for Explaining Classifiers
MAIRE - 用于解释分类器的与模型无关的可解释规则提取过程
A Comparative Study of Intrathecal Fentanyl and Dexmedetomidine as Adjuvants to Hyperbaric Levobupivacaine 0.5% and Hyperbaric Levobupivacaine 0.5% Alone in Infraumbilical Surgeries
A%20比较%20研究%20of%20鞘内%20芬太尼%20和%20右美托咪定%20as%20佐剂%20至%20高压%20左布比卡因%200.5%%20和%20高压%20左布比卡因%200.5%%20单独%20in %20脐下%20手术
  • DOI:
  • 发表时间:
    2016
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Shweta Jain;G. Sharma;U. Bafna;Dilip Jain;S. Meena;Pranav Jetley;G. Das
  • 通讯作者:
    G. Das
Analysis of Multi Level Feedback Queue Scheduling Using Markov Chain Model with Data Model Approach
基于数据模型方法的马尔可夫链模型多级反馈队列调度分析
  • DOI:
  • 发表时间:
    2016
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Shweta Jain;Dr. Saurabh Jain
  • 通讯作者:
    Dr. Saurabh Jain

Shweta Jain的其他文献

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{{ truncateString('Shweta Jain', 18)}}的其他基金

PFI-TT: A system to secure and verify location, time, metadata, and authenticity of digital images and videos
PFI-TT:保护和验证数字图像和视频的位置、时间、元数据和真实性的系统
  • 批准号:
    2122682
  • 财政年份:
    2021
  • 资助金额:
    $ 12.5万
  • 项目类别:
    Standard Grant
CISE-MSI:RCBP-ED:SaTC: Cultivating and Developing Research Talent to Support Research in Cyber-Security
CISE-MSI:RCBP-ED:SaTC:培养和发展研究人才以支持网络安全研究
  • 批准号:
    2131182
  • 财政年份:
    2021
  • 资助金额:
    $ 12.5万
  • 项目类别:
    Standard Grant
I-Corps: Blockchain-backed system that establishes the provenance of digital images and videos
I-Corps:区块链支持的系统,可确定数字图像和视频的来源
  • 批准号:
    2011744
  • 财政年份:
    2020
  • 资助金额:
    $ 12.5万
  • 项目类别:
    Standard Grant

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