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Semantic Representation and Integration of Digital Evidence
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: Procedia Computer Science, ISSN 1877-0509, Vol. 22, 1266-1275 p.Article in journal (Refereed) Published
Abstract [en]

The ever-increasing complexity and sophistication of computer and network attacks challenge society's dependability on digital infrastructure. Digital investigations recover and reconstruct the digital trails of such events and may employ practices from various subfields (computer, network forensics), each with its own set of techniques and tools. Integration of evidence from heterogeneous sources of data (e.g. disk images, network packet captures, logs) is often a manual and time- consuming process relying significantly on the investigator's expertise. In this paper, we propose and develop an approach, based on the Semantic Web framework, for ontologically representing and integrating digital evidence. The presented approach enhances existing forensic analysis techniques by providing partial and eventually full automation of the investigative process.

Place, publisher, year, edition, pages
2013. Vol. 22, 1266-1275 p.
Keyword [en]
Digital evidence, Ontology, Semantic Web, Evidence Integration, Knowledge Representation
National Category
Information Systems
Research subject
Computer and Systems Sciences
URN: urn:nbn:se:su:diva-97234DOI: 10.1016/j.procs.2013.09.214OAI: diva2:676278
17th International Conference in Knowledge Based and Intelligent Information and Engineering Systems - KES 2013
Available from: 2013-12-05 Created: 2013-12-05 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.
Report Series / Department of Computer & Systems Sciences, ISSN 1101-8526 ; 16-004
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
urn:nbn:se:su:diva-130742 (URN)
2016-04-25, L30, Nod Building, Borgarfjordsgatan 12 (Nodhuset), Campus Kista, Stockholm, 10:00 (English)
Available from: 2016-06-17 Created: 2016-06-02 Last updated: 2016-06-20Bibliographically approved

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