Androidâ—¢ App Forensic Evidence Database (AndroidAED) · Forensic Evidence 2-17-2020...
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CSAFE Presentations and Proceedings Center for Statistics and Applications in Forensic Evidence 2-17-2020 Android™ App Forensic Evidence Database (AndroidAED) Android™ App Forensic Evidence Database (AndroidAED) Chen Shi Iowa State University, [email protected] Chao-Chun Cheng Iowa State University, [email protected] Connor Kocolowski Iowa State University Emmett Kozlowski Iowa State University Justin Kuennen Iowa State University See next page for additional authors Follow this and additional works at: https://lib.dr.iastate.edu/csafe_conf Part of the Electrical and Computer Engineering Commons, and the Forensic Science and Technology Commons Recommended Citation Recommended Citation Shi, Chen; Cheng, Chao-Chun; Kocolowski, Connor; Kozlowski, Emmett; Kuennen, Justin; Lawlor, Matthew; Kerr, Mitchell; Stair, Jacob; Liao, Zhonghao; Gong, Zhenqiang; and Guan, Yong, "Android™ App Forensic Evidence Database (AndroidAED)" (2020). CSAFE Presentations and Proceedings. 63. https://lib.dr.iastate.edu/csafe_conf/63 This Presentation is brought to you for free and open access by the Center for Statistics and Applications in Forensic Evidence at Iowa State University Digital Repository. It has been accepted for inclusion in CSAFE Presentations and Proceedings by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected].
Transcript of Androidâ—¢ App Forensic Evidence Database (AndroidAED) · Forensic Evidence 2-17-2020...
CSAFE Presentations and Proceedings Center for Statistics and Applications in Forensic Evidence
2-17-2020
Android™ App Forensic Evidence Database (AndroidAED) Android™ App Forensic Evidence Database (AndroidAED)
Chen Shi Iowa State University, [email protected]
Chao-Chun Cheng Iowa State University, [email protected]
Connor Kocolowski Iowa State University
Emmett Kozlowski Iowa State University
Justin Kuennen Iowa State University
See next page for additional authors
Follow this and additional works at: https://lib.dr.iastate.edu/csafe_conf
Part of the Electrical and Computer Engineering Commons, and the Forensic Science and Technology
Commons
Recommended Citation Recommended Citation Shi, Chen; Cheng, Chao-Chun; Kocolowski, Connor; Kozlowski, Emmett; Kuennen, Justin; Lawlor, Matthew; Kerr, Mitchell; Stair, Jacob; Liao, Zhonghao; Gong, Zhenqiang; and Guan, Yong, "Android™ App Forensic Evidence Database (AndroidAED)" (2020). CSAFE Presentations and Proceedings. 63. https://lib.dr.iastate.edu/csafe_conf/63
This Presentation is brought to you for free and open access by the Center for Statistics and Applications in Forensic Evidence at Iowa State University Digital Repository. It has been accepted for inclusion in CSAFE Presentations and Proceedings by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected].
Android™ App Forensic Evidence Database (AndroidAED) Android™ App Forensic Evidence Database (AndroidAED)
Abstract Abstract Learning Overview: After attending this presentation, attendees will better understand how AndroidAED will be beneficial for academic researchers whose studies relate to mobile applications that grant them the ability to search through many of the available applications across various third-party app stores.
Disciplines Disciplines Electrical and Computer Engineering | Forensic Science and Technology
Comments Comments Shi, C., Cheng, C.C., Kocoloski, C., Kozlowski, E., Kuennen, J., Lawlor, M., Kerr, M., Stair, J., Liao, Z., Gong, Z., Guan, Y., Android app Forensic Evidence Database (AndroidAED), 2020 AAFS, Anaheim, CA. Posted with permission from CSAFE.
Authors Authors Chen Shi, Chao-Chun Cheng, Connor Kocolowski, Emmett Kozlowski, Justin Kuennen, Matthew Lawlor, Mitchell Kerr, Jacob Stair, Zhonghao Liao, Zhenqiang Gong, and Yong Guan
This presentation is available at Iowa State University Digital Repository: https://lib.dr.iastate.edu/csafe_conf/63
Android™ App Forensic Evidence Database(AndroidAED)
Chen Shi, Chris Chao-Chun Cheng, Brody Concannon, Neil Zhenqiang Gong, and Yong Guan
Acknowledgement: Barbara Guttman, Michael Ogata, and James Lyle (NIST)
Presenter
Presentation Notes
I would like to talk about my research of building Mobile devices become increasingly popular nowadays, more and more criminal cases involved the use of mobile devices, so the evidence generated or stored in mobile devices become important for the investigators.
UIUC Chinese Scholar Kidnapping
Research funded by the Center for Statistics and Applications in Forensic Evidence (CSAFE) - forensicstats.org
Presenter
Presentation Notes
on June 2017 was abducted by Brendt Christensen, a former physics graduate student at the university. Christensen lured Zhang into his car at a bus stop took her to his apartment where he raped and murdered her
Mobile App’s Evidence: UIUC Kidnapping
Obtain the suspect’s mobile device
Extract the file system image
Identify evidence in the image
Web browsing historyabduction 101
Perfect abduction fantasy
decomposition
Research funded by the Center for Statistics and Applications in Forensic Evidence (CSAFE) - forensicstats.org
Presenter
Presentation Notes
Downloaded a research paper on decomposition Posts on message board Fetlife.com Keyword searches
Rape and Murder in Germany
Research funded by the Center for Statistics and Applications in Forensic Evidence (CSAFE) - forensicstats.org
Presenter
Presentation Notes
October 2016, 19-year-old medical student Maria was murdered raped and drowned in the River.
Mobile App’s Evidence: Rape and Murder
Research funded by the Center for Statistics and Applications in Forensic Evidence (CSAFE) - forensicstats.org
Presenter
Presentation Notes
The health data activity - including how many steps are taken, sleep patterns as well as various body measurements such as heart rate. suggested periods of activity, two peaks, which the app indicates 'climbing stairs.’ could correlate to him dragging his victim down a riverbank and climbing back up, digital forensics has begun to play an important role in proving the innocence or guilt of suspects.
Mobile Forensics Problems
1. Given an app, what kinds of information will be collected and where will it be stored?
2. After the app is updated, what are the changes of the evidentiary data?
3. What kinds of evidence stored in the suspect’s device? Where they are?
Research funded by the Center for Statistics and Applications in Forensic Evidence (CSAFE) - forensicstats.org
App Evidence Database
Research funded by the Center for Statistics and Applications in Forensic Evidence (CSAFE) - forensicstats.org
Presenter
Presentation Notes
how forensic investigator deal with Obtain phone retrieve file system UIUC scholar case find browsing history
Design and Implementation
System Diagram Website UIResearch funded by the Center for Statistics and Applications in Forensic Evidence (CSAFE) - forensicstats.org
Presenter
Presentation Notes
The Node.js backend uses the Express framework and is responsible for handling all the requests from the front end. The backend processes the request against the database and returns the desired information. It is also responsible for updating new forensic reports to the database. The frontend is a React app website. This website is the portal for users to interact with our database. Scalability, system support the vast amount of applications we need to download and analyze.
App Crawlers Development
• 54 App Markets: Google Play Store, ApkPure, ApkMirror
• Versions, MD5 hash, Permission list, Release date …
App Crawlers ServersResearch funded by the Center for Statistics and Applications in Forensic Evidence (CSAFE) - forensicstats.org
Presenter
Presentation Notes
The web crawlers are used to collect the information and apk files for each application. Since each site has different html and functions, we created a crawler tailored to each store to collect data. The crawlers utilize Beautifulsoup to scrape each webpage and the Selenium driver for webpage interactions.
Design and Implementation
System Diagram Website UIResearch funded by the Center for Statistics and Applications in Forensic Evidence (CSAFE) - forensicstats.org
Presenter
Presentation Notes
The Node.js backend uses the Express framework and is responsible for handling all the requests from the front end. The backend processes the request against the database and returns the desired information. It is also responsible for updating new forensic reports to the database. The frontend is a React app website. This website is the portal for users to interact with our database. Scalability, system support the vast amount of applications we need to download and analyze.
enter keyword to search
various sources
ApkMirror
Research funded by the Center for Statistics and Applications in Forensic Evidence (CSAFE) - forensicstats.org
Presenter
Presentation Notes
investigator gather the list of apps installed on the device, database provide analysis results for the same app
evidentiary datametadata
Research funded by the Center for Statistics and Applications in Forensic Evidence (CSAFE) - forensicstats.org
EviHunter - Static Program Analysis
1. Obtain Android Package file2. Extract app’s code3. Perform forward analysis
and apply propagation rules4. Output when reaching a
sink method
Chris Chao-Chun Cheng, Chen Shi, Neil Zhenqiang Gong, and Yong Guan, "EviHunter: Identifying Digital Evidence in the Permanent Storage of Android Devices via Static Analysis," in ACM CCS 2018
Research funded by the Center for Statistics and Applications in Forensic Evidence (CSAFE) - forensicstats.org
Presenter
Presentation Notes
The tool we designed for examine the app and generate forensic report
EviHunter - Dynamic Program Analysis
Preprocessing:Install customized Android OS on device
For each app:1. Install and run it on device
carried modified OS2. Output when reaching a
sink method
Zhen Xu, Chen Shi, Chris Cheng, Neil Gong and Yong Guan, "A Dynamic Taint Analysis Tool for Android App Forensics," in SADFE 2018
Research funded by the Center for Statistics and Applications in Forensic Evidence (CSAFE) - forensicstats.org
Presenter
Presentation Notes
track the information flow at runtime. The difference static has better coverage since it examine all the app code directly, contain false position cuz some paths trigger in real time. Dynamic can lessen false positions, but it really hard for dynamic analysis all the possible events at runtime, false negative. Most accurate and completed forensic report.
450 Million Users > 300K Apps
Source:https://airpush.com/about/Research funded by the Center for Statistics and Applications in Forensic Evidence (CSAFE) - forensicstats.org
Hourly Tracking
133 apps:Path: /data/data/<package name>/databases/ldata.dbEvidence Type: Location and Time
Research funded by the Center for Statistics and Applications in Forensic Evidence (CSAFE) - forensicstats.org
Step1. Crawl Apps from markets
Step2. Apply EviHunter to generate result
Step3. Upload apps, metadata, forensic
analysis result
Research funded by the Center for Statistics and Applications in Forensic Evidence (CSAFE) - forensicstats.org
Summary and Future Directions
• Save time and move fast in real-world cases.
• Up-to-date forensic analysis result of real-world apps.
Research funded by the Center for Statistics and Applications in Forensic Evidence (CSAFE) - forensicstats.org
