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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-19: The forensicswiki.org has been changed from Apache to nginx and upgraded from MediaWiki 1.16 to 1.18. We hope that this will address some of the downtime we have been having. Please email Simson if you see any weird problems. Thanks!
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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>JAN 2012</small>
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<small>June 2013</small>
 
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<bibtex>
 
<bibtex>
@article{10.1109/CIS.2011.180,
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@INPROCEEDINGS{6503202,  
author = {Vrizlynn L.L. Thing and Tong-Wei Chua and Ming-Lee Cheong},
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author={Gessiou, E. and Volanis, S. and Athanasopoulos, E. and Markatos, E.P. and Ioannidis, S.},  
title = {Design of a Digital Forensics Evidence Reconstruction System for Complex and Obscure Fragmented File Carving},
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booktitle={Global Communications Conference (GLOBECOM), 2012 IEEE},  
journal ={Computational Intelligence and Security, International Conference on},
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title={Digging up social structures from documents on the web},  
volume = {0},
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year={2012},  
isbn = {978-0-7695-4584-4},
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pages={744-750},  
year = {2011},
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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.},  
pages = {793-797},
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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},  
doi = {http://doi.ieeecomputersociety.org/10.1109/CIS.2011.180},
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doi={10.1109/GLOCOM.2012.6503202},  
publisher = {IEEE Computer Society},
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ISSN={1930-529X},}
address = {Los Alamitos, CA, USA},
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}
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</bibtex>
 
</bibtex>
Fragmented file carving is an important technique in Digital Forensics to recover files from their fragments in the absence of the file system allocation information. In this paper, we proposed a system design for solving the fragmented file carving problem taking into consideration, conditions of real-life fragmentation scenarios. We developed our evidence reconstruction and recovery system, and carried out experiments, to evaluate the capability in detecting and recovering obscured evidence. The results showed that our system is able to achieve a higher efficiency and accuracy (e.g. 1.5 minutes for the reconstruction of each highly fragmented and deleted (obscured) image in its entirety or 100% recovery), when compared with the commercial recovery system, Adroit Photo Forensics (e.g. 2.8 minutes and 6.3 minutes for a partial image recovery or failure in recovery, respectively).
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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
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(See also [[Past Selected Articles]])
 
(See also [[Past Selected Articles]])
  
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* '''[[Tools#Disk_Analysis_Tools|Disk Analysis]]''': [[EnCase]], [[SMART]], [[Sleuthkit]], [[foremost]], [[Scalpel]], [[frag_find]]...
 
* '''[[Tools#Disk_Analysis_Tools|Disk Analysis]]''': [[EnCase]], [[SMART]], [[Sleuthkit]], [[foremost]], [[Scalpel]], [[frag_find]]...
 
* '''[[Tools#Forensics_Live_CDs|Live CDs]]''': [[DEFT Linux]], [[Helix]] ([[Helix3 Pro|Pro]]), [[FCCU Gnu/Linux Boot CD]], [[Knoppix STD]], ...
 
* '''[[Tools#Forensics_Live_CDs|Live CDs]]''': [[DEFT Linux]], [[Helix]] ([[Helix3 Pro|Pro]]), [[FCCU Gnu/Linux Boot CD]], [[Knoppix STD]], ...
* '''[[Tools:Document Metadata Extraction|Metadata Extraction]]''': [[wvWare]], [[jhead]], [[Hachoir | hachoir-metadata]], ...
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* '''[[Tools:Document Metadata Extraction|Metadata Extraction]]''': [[wvWare]], [[jhead]], [[Hachoir | hachoir-metadata]], [[Photo Investigator]]...
 
* '''[[Tools:File Analysis|File Analysis]]''': [[file]], [[ldd]], [[ltrace]], [[strace]], [[strings]], ...
 
* '''[[Tools:File Analysis|File Analysis]]''': [[file]], [[ldd]], [[ltrace]], [[strace]], [[strings]], ...
 
* '''[[Tools:Network_Forensics|Network Forensics]]''': [[Snort]],  [[Wireshark]], [[Kismet]],  [[NetworkMiner]]...
 
* '''[[Tools:Network_Forensics|Network Forensics]]''': [[Snort]],  [[Wireshark]], [[Kismet]],  [[NetworkMiner]]...

Revision as of 13:38, 9 October 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 686 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
Forensic Linux Live CD distributions are widely used during computer forensic investigations. Currently, many vendors of such Live CD distributions state that their Linux do not modify the contents of hard drives or employ "write protection." Testing indicates that this may not always be the case. Read More...


Topics



You can help! We have a list of articles that need to be expanded. If you know anything about any of these topics, please feel free to chip in.