DFRWS 2018 Challenge Page
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README.md

IoT Forensic Challenge, 2017-2018

Internet of Things (IoT) are, very generally, network and Internet connected devices usually for the purpose of monitoring and automation tasks. Consumer-grade "Smart" devices are increasing in popularity and scope. These devices and the data they collect are potentially interesting for digital investigations, but also come with a number of new investigation challenges.

This challenge seeks to advance the state-of-the-art in IoT forensics by focusing the community's attention on this emerging domain.

This challenge is made possible by a grant from the Korea Institute for Advancement of Technology (KIAT), N0002260.

Scenario

A woman (Betty) has been murdered. The murder was called in by Betty's husband (Simon), who claims to have been at home at the time. Additional case details can be found here. Your job is to analyze these artifacts for forensically interesting information.

Time Zone: UTC+9

Responders acquired the following data:

  • Smart TV Rasberry Pi
    • SHA1: 9ac0de76eca7958bfed1bd5909bbf766409af180
  • Samsung Note 2 (Betty)
    • SHA1: cd494cf3097d8482100ce26dc8e35f0d87b67198
  • Samsung Note 2 (Simon)
    • SHA1: fc28e415ee740531df86a2b227c4f514e9ed40ba
  • Google OnHub Diagnostic report
    • SHA1: 20eb4825eaf6c303beadd090868110fb2de37066
  • Amazon Echo Cloud Data
    • SHA1: d1d126f47b565926dcc80fe6a4e7094f0281cb47
  • MDS (Acme, Inc.) Smarthome Network Dump
    • SHA1: 6ab6c522b070cde292a18645a19929998e009293

All acquired data can be downloaded from here. We recommend using a download manager like uGet since the compressed mobile images are 3GB.

Challenge

This DFRWS Forensic Challenge aspires to motivate new approaches to forensic analysis and has four levels of participation:

  1. Evaluating and Expressing Conclusions: Formally evaluating and expressing the probability or likelihood ratio that the husband killed his wife versus some other unknown person.
  2. Device Level Analysis: Developing methods and tools to forensically process digital traces generated by IoT devices, including on mobile devices.
  3. Network and Cloud Level Analysis: Developing methods and tools to forensically process digital traces generated by IoT devices on networks and cloud systems.
  4. Correlation and Analysis: Developing methods and supporting tools that combine information from various data sources and automatically compute, visualize, or otherwise expose patterns of potential interest.

Submissions

  • Submission deadline: Feb. 21, 2018
  • Please see complete rules
  • All participants must send an email to challenge@dfrws.org with the subject line "Solution submission".
  • The actual solution (code and relevant documentation) can be submitted via email tarball (5MB max), posted on a public VCS, or posted for HTTP/FTP download.
  • Submissions will be judged on: 1) completeness; 2) accuracy; and 3) tool/code quality.

Good luck!