Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
LEIA: The Live Evidence Information Aggregator: Towards Efficient Cyber-Law Enforcement
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2013 (English)In: World Congress on Internet Security (WorldCIS), IEEE Computer Society Digital Library, 2013, 156-161 p.Conference paper, Published paper (Refereed)
Abstract [en]

Given the complexity and velocity of the interactions among vastly heterogeneous elements on the Internet; the colossal amounts of information generated and exchanged, coupled with the increasingly evasive nature of new forms of electronic crimes, as well as the relative immaturity of current Digital Forensics tools, Law Enforcement Agencies are easily outpaced and overwhelmed with the types of electronic crimes experienced today. In this paper, we describe the architecture of a comprehensive automated Digital Investigation platform termed as the Live Evidence Information Aggregator (LEIA). It makes use of the strong points of hypervisor technologies, large scale distributed file systems, the resource description framework (RDF), peer-to-peer networks, and innovative collaborative mechanisms in order to introduce a level of speed, accuracy and efficiency to match up with the imminent age of massively distributed cybercrime in the context of Internet of Things.

Place, publisher, year, edition, pages
IEEE Computer Society Digital Library, 2013. 156-161 p.
Keyword [en]
Digital Forensics, Cybercrime, Digital Evidence, Big Data, Hadoop, Hypervisors, P2P, Collaborative Live Investigation
National Category
Information Systems
Research subject
Computer and Systems Sciences; Information Systems Security
Identifiers
URN: urn:nbn:se:su:diva-114705DOI: 10.1109/WorldCIS.2013.6751038ISBN: 978-1-908320-22-3 (print)OAI: oai:DiVA.org:su-114705DiVA: diva2:793811
Conference
World Congress on Internet Security (WorldCIS), London, 9-12 Dec. 2013
Available from: 2015-03-09 Created: 2015-03-09 Last updated: 2016-06-17Bibliographically approved
In thesis
1. Towards Automation in Digital Investigations: Seeking Efficiency in Digital Forensics in Mobile and Cloud Environments
Open this publication in new window or tab >>Towards Automation in Digital Investigations: Seeking Efficiency in Digital Forensics in Mobile and Cloud Environments
2016 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Cybercrime and related malicious activity in our increasingly digital world has become more prevalent and sophisticated, evading traditional security mechanisms. Digital forensics has been proposed to help investigate, understand and eventually mitigate such attacks. The practice of digital forensics, however, is still fraught with various challenges. Some of the most prominent of these challenges include the increasing amounts of data and the diversity of digital evidence sources appearing in digital investigations.

Mobile devices and cloud infrastructures are an interesting specimen, as they inherently exhibit these challenging circumstances and are becoming more prevalent in digital investigations today. Additionally they embody further characteristics such as large volumes of data from multiple sources, dynamic sharing of resources, limited individual device capabilities and the presence of sensitive data. These combined set of circumstances make digital investigations in mobile and cloud environments particularly challenging.

This is not aided by the fact that digital forensics today still involves manual, time consuming tasks within the processes of identifying evidence, performing evidence acquisition and correlating multiple diverse sources of evidence in the analysis phase. Furthermore, industry standard tools developed are largely evidence-oriented, have limited support for evidence integration and only automate certain precursory tasks, such as indexing and text searching.

In this study, efficiency, in the form of reducing the time and human labour effort expended, is sought after in digital investigations in highly networked environments through the automation of certain activities in the digital forensic process. To this end requirements are outlined and an architecture designed for an automated system that performs digital forensics in highly networked mobile and cloud environments. Part of the remote evidence acquisition activity of this architecture is built and tested on several mobile devices in terms of speed and reliability. A method for integrating multiple diverse evidence sources in an automated manner, supporting correlation and automated reasoning is developed and tested. Finally the proposed architecture is reviewed and enhancements proposed in order to further automate the architecture by introducing decentralization particularly within the storage and processing functionality. This decentralization also improves machine to machine communication supporting several digital investigation processes enabled by the architecture through harnessing the properties of various peer-to-peer overlays.

Remote evidence acquisition helps to improve the efficiency (time and effort involved) in digital investigations by removing the need for proximity to the evidence. Experiments show that a single TCP connection client-server paradigm does not offer the required scalability and reliability for remote evidence acquisition and that a multi-TCP connection paradigm is required. The automated integration, correlation and reasoning on multiple diverse evidence sources demonstrated in the experiments improves speed and reduces the human effort needed in the analysis phase by removing the need for time-consuming manual correlation. Finally, informed by published scientific literature, the proposed enhancements for further decentralizing the Live Evidence Information Aggregator (LEIA) architecture offer a platform for increased machine-to-machine communication thereby enabling automation and reducing the need for manual human intervention.

Place, publisher, year, edition, pages
Stockholm: Department of Computer and Systems Sciences, Stockholm University, 2016. 139 p.
Series
Report Series / Department of Computer & Systems Sciences, ISSN 1101-8526 ; 16-004
Keyword
Computer forensics, network forensics, mobile devices, mobile forensics, cloud computing, semantic web, hypervisors, virtualization, remote acquisition, automation, evidence analysis, correlation, P2P, bittorrent
National Category
Computer Science
Research subject
Computer Science; Information Systems Security
Identifiers
urn:nbn:se:su:diva-130742 (URN)
Presentation
2016-04-25, L30, Nod Building, Borgarfjordsgatan 12 (Nodhuset), Campus Kista, Stockholm, 10:00 (English)
Opponent
Supervisors
Available from: 2016-06-17 Created: 2016-06-02 Last updated: 2016-06-20Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Homem, IrvinPopov, Oliver
By organisation
Department of Computer and Systems Sciences
Information Systems

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 61 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf