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This is the '''Forensics Wiki''', a [http://creativecommons.org/licenses/by-sa/2.5/ Creative Commons]-licensed [http://en.wikipedia.org/wiki/Wiki wiki] devoted to information about [[digital forensics]] (also known as computer forensics). We currently list a total of [[Special:Allpages|{{NUMBEROFARTICLES}}]] pages.
 
This is the '''Forensics Wiki''', a [http://creativecommons.org/licenses/by-sa/2.5/ Creative Commons]-licensed [http://en.wikipedia.org/wiki/Wiki wiki] devoted to information about [[digital forensics]] (also known as computer forensics). We currently list a total of [[Special:Allpages|{{NUMBEROFARTICLES}}]] pages.
 
    
 
    
Much of [[computer forensics]] is focused on the [[tools]] and [[techniques]] used by [[investigator]]s, but there are also a number of important [[papers]], [[people]], and [[organizations]] involved. Many of those organizations sponsor [[conferences]] throughout the year and around the world. You may also wish to examine the popular [[journals]] and some special [[reports]].
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Much of [[computer forensics]] is focused on the [[tools]] and [[techniques]] used by [[investigator]]s, but there are also a number of important [[papers]], [[people]], and [[organizations]] involved. Many of those organizations sponsor [[Upcoming_events|conferences]] throughout the year and around the world. You may also wish to examine the popular [[journals]] and some special [[reports]].
 
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==WIKI NEWS==
 
==WIKI NEWS==
2012-feb-25: We continue to have problems with our hosting provider and are in the process of identifying a new one. Thank you for your patience.
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2013-05-15: You can now subscribe to Forensics Wiki Recent Changes with the [[ForensicsWiki FeedBurner Feed]]
  
 
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<h2 style="margin:0; background-color:#ffff33; font-size:120%; font-weight:bold; border:1px solid #afa3bf; text-align:left; color:#000; padding-left:0.4em; padding-top:0.2em; padding-bottom:0.2em;"> Featured Forensic Research </h2>
 
<h2 style="margin:0; background-color:#ffff33; font-size:120%; font-weight:bold; border:1px solid #afa3bf; text-align:left; color:#000; padding-left:0.4em; padding-top:0.2em; padding-bottom:0.2em;"> Featured Forensic Research </h2>
  
<small>Mar 2012</small>
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<small>June 2013</small>
 
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<bibtex>
 
<bibtex>
@inproceedings{Balasubramaniyan:2010:PUS:1866307.1866320,
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@INPROCEEDINGS{6503202,  
author = {Balasubramaniyan, Vijay A. and Poonawalla, Aamir and Ahamad, Mustaque and Hunter, Michael T. and Traynor, Patrick},
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author={Gessiou, E. and Volanis, S. and Athanasopoulos, E. and Markatos, E.P. and Ioannidis, S.},  
title = {PinDr0p: using single-ended audio features to determine call provenance},
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booktitle={Global Communications Conference (GLOBECOM), 2012 IEEE},  
booktitle = {Proceedings of the 17th ACM conference on Computer and communications security},
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title={Digging up social structures from documents on the web},  
series = {CCS '10},
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year={2012},  
year = {2010},
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pages={744-750},  
isbn = {978-1-4503-0245-6},
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abstract={We collected more than ten million Microsoft Office documents from public websites, analyzed the metadata stored in each document and extracted information related to social activities. Our analysis revealed the existence of exactly identified cliques of users that edit, revise and collaborate on industrial and military content. We also examined cliques in documents downloaded from Fortune-500 company websites. We constructed their graphs and measured their properties. The graphs contained many connected components and presented social properties. The a priori knowledge of a company's social graph may significantly assist an adversary to launch targeted attacks, such as targeted advertisements and phishing emails. Our study demonstrates the privacy risks associated with metadata by cross-correlating all members identified in a clique with users of Twitter. We show that it is possible to match authors collaborating in the creation of a document with Twitter accounts. To the best of our knowledge, this study is the first to identify individuals and create social cliques solely based on information derived from document metadata. Our study raises major concerns about the risks involved in privacy leakage due to document metadata.},  
location = {Chicago, Illinois, USA},
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keywords={data privacy;document handling;graph theory;meta data;social networking (online);Fortune-500 company Websites;Microsoft Office documents;Twitter accounts;company social graph;document metadata;information extraction;metadata analysis;phishing emails;privacy leakage;privacy risks;public Websites;social activities;social cliques;social properties;social structures;targeted advertisements},  
pages = {109--120},
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doi={10.1109/GLOCOM.2012.6503202},  
numpages = {12},
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ISSN={1930-529X},}
url = {http://doi.acm.org/10.1145/1866307.1866320},
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doi = {http://doi.acm.org/10.1145/1866307.1866320},
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acmid = {1866320},
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publisher = {ACM},
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address = {New York, NY, USA},
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keywords = {VoIP, call fingerprinting, provenance, telephony},
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}
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</bibtex>
 
</bibtex>
The recent diversification of telephony infrastructure allows users to communicate through landlines, mobile phones and VoIP phones. However, call metadata such as Caller-ID is either not transferred or transferred without verification across these networks, allowing attackers to maliciously alter it. In this paper, we develop PinDr0p, a mechanism to assist users in determining call provenance — the source and the path taken by a call. Our techniques detect and mea- sure single-ended audio features to identify all of the applied voice codecs, calculate packet loss and noise profiles, while remaining agnostic to characteristics of the speaker’s voice (as this may le- gitimately change when interacting with a large organization). In the absence of verifiable call metadata, these features in combina- tion with machine learning allow us to determine the traversal of a call through as many as three different providers (e.g., cellular, then VoIP, then PSTN and all combinations and subsets thereof) with 91.6% accuracy. Moreover, we show that once we identify and characterize the networks traversed, we can create detailed fin- gerprints for a call source. Using these fingerprints we show that we are able to distinguish between calls made using specific PSTN, cellular, Vonage, Skype and other hard and soft phones from loca- tions across the world with over 90% accuracy. In so doing, we provide a first step in accurately determining the provenance of a call.
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We collected more than ten million Microsoft Office documents from public websites, analyzed the metadata stored in each document and extracted information related to social activities. Our analysis revealed the existence of exactly identified cliques of users that edit, revise and collaborate on industrial and military content. We also examined cliques in documents downloaded from Fortune-500 company websites. We constructed their graphs and measured their properties. The graphs contained many connected components and presented social properties. The a priori knowledge of a company's social graph may significantly assist an adversary to launch targeted attacks, such as targeted advertisements and phishing emails. Our study demonstrates the privacy risks associated with metadata by cross-correlating all members identified in a clique with users of Twitter. We show that it is possible to match authors collaborating in the creation of a document with Twitter accounts. To the best of our knowledge, this study is the first to identify individuals and create social cliques solely based on information derived from document metadata. Our study raises major concerns about the risks involved in privacy leakage due to document metadata.
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http://cis.poly.edu/~gessiou/reports/metadata.pdf
  
 
(See also [[Past Selected Articles]])
 
(See also [[Past Selected Articles]])

Revision as of 15:59, 30 June 2013

This is the Forensics Wiki, a Creative Commons-licensed wiki devoted to information about digital forensics (also known as computer forensics). We currently list a total of 741 pages.

Much of computer forensics is focused on the tools and techniques used by investigators, but there are also a number of important papers, people, and organizations involved. Many of those organizations sponsor conferences throughout the year and around the world. You may also wish to examine the popular journals and some special reports.


WIKI NEWS

2013-05-15: You can now subscribe to Forensics Wiki Recent Changes with the ForensicsWiki FeedBurner Feed

Featured Forensic Research

June 2013

Gessiou, E., Volanis, S., Athanasopoulos, E., Markatos, E.P., Ioannidis, S. - Digging up social structures from documents on the web
Global Communications Conference (GLOBECOM), 2012 IEEE pp. 744-750,2012
Bibtex
Author : Gessiou, E., Volanis, S., Athanasopoulos, E., Markatos, E.P., Ioannidis, S.
Title : Digging up social structures from documents on the web
In : Global Communications Conference (GLOBECOM), 2012 IEEE -
Address :
Date : 2012

We collected more than ten million Microsoft Office documents from public websites, analyzed the metadata stored in each document and extracted information related to social activities. Our analysis revealed the existence of exactly identified cliques of users that edit, revise and collaborate on industrial and military content. We also examined cliques in documents downloaded from Fortune-500 company websites. We constructed their graphs and measured their properties. The graphs contained many connected components and presented social properties. The a priori knowledge of a company's social graph may significantly assist an adversary to launch targeted attacks, such as targeted advertisements and phishing emails. Our study demonstrates the privacy risks associated with metadata by cross-correlating all members identified in a clique with users of Twitter. We show that it is possible to match authors collaborating in the creation of a document with Twitter accounts. To the best of our knowledge, this study is the first to identify individuals and create social cliques solely based on information derived from document metadata. Our study raises major concerns about the risks involved in privacy leakage due to document metadata. http://cis.poly.edu/~gessiou/reports/metadata.pdf

(See also Past Selected Articles)

Featured Article

Forensic Linux Live CD issues
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