A general strategy for differential forensic analysis

Garfinkel, Simson L.; Nelson, Alexander J.; Young, Joel

doi:10.1016/j.diin.2012.05.003

Cited by 33 publications

(8 citation statements)

References 14 publications

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“…In order to quantify the changes made by the Windows PE operating system mounting process, a differential analysis was performed on the hard drive images taken before and after running Forensics2020. Differential analysis allows a forensic examiner to focus on the changes brought about as a result of the activity that takes place between the acquisition of an image A and the acquisition of an image B at a subsequent point in time [6]. Note that no images were acquired in the previous experiments.…”

Section: Methodsmentioning

confidence: 99%

Performance of a Logical, Five- Phase, Multithreaded, Bootable Triage Tool

Baggili

Marrington

Jafar

2014

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

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Part 4: Forensic Tools and TrainingInternational audienceThis paper describes a five-phase, multi-threaded bootable approach to digital forensic triage, which is implemented in a product called Forensics2020. The first phase collects metadata for every logical file on the hard drive of a computer system. The second phase collects EXIF camera data from each image found on the hard drive. The third phase analyzes and categorizes each file based on its header information. The fourth phase parses each executable file to provide a complete audit of the software applications on the system; a signature is generated for every executable file, which is later checked against a threat detection database. The fifth and final phase hashes each file and records its hash value. All five phases are performed in the background while the first responder interacts with the system. This paper assesses the forensic soundness of Forensics2020. The tool makes certain changes to a hard drive that are similar to those made by other bootable forensic examination environments, although the changes are greater in number. The paper also describes the lessons learned from developing Forensics2020, which can help guide the development of other forensic triage tools

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Section: Methodsmentioning

confidence: 99%

Performance of a Logical, Five- Phase, Multithreaded, Bootable Triage Tool

Baggili

Marrington

Jafar

2014

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

View full text Add to dashboard Cite

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“…More generally, the primary deductive tool of forensics is differential analysis [7], which allows us to build a knowledge base of state transitions that are of significance, and gives us a framework for approaching new situations.…”

Section: What Is Forensic Computing?mentioning

confidence: 99%

Building a Forensic Computing Language

Roussev

2015

2015 48th Hawaii International Conference on System Sciences

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The primary goal of this discussion is to motivate the need for the development of a domain-specific language (DSL) focused on the requirements of forensic and security analysis.We argue that, at present, there is no adequate mechanism that a) allows analysts to specify the forensic computation as a tool-agnostic, logical sequence of steps; b) provides a formal specification for tool developers; and c) seamlessly integrates different available tools to provides a complete and extensible solution.We present an initial design sketch for a forensic DSL called nugget, and use it to illustrate the ideas behind our approach.

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“…The PMF approach is based upon the concept of differential forensic analysis, as described by Garfinkel, Nelson, and Young . Automated differential analysis techniques used in PMF involve the comparison of forensic images taken at different times or the comparison of forensic images to a common baseline (i.e., “gold image”).…”

Section: Related Workmentioning

confidence: 99%

Generating a Corpus of Mobile Forensic Images for Masquerading user Experimentation

Guido

Brooks

Grover

et al. 2016

Journal of Forensic Sciences

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The Periodic Mobile Forensics (PMF) system investigates user behavior on mobile devices. It applies forensic techniques to an enterprise mobile infrastructure, utilizing an on-device agent named TractorBeam. The agent collects changed storage locations for later acquisition, reconstruction, and analysis. TractorBeam provides its data to an enterprise infrastructure that consists of a cloud-based queuing service, relational database, and analytical framework for running forensic processes. During a 3-month experiment with Purdue University, TractorBeam was utilized in a simulated operational setting across 34 users to evaluate techniques to identify masquerading users (i.e., users other than the intended device user). The research team surmises that all masqueraders are undesirable to an enterprise, even when a masquerader lacks malicious intent. The PMF system reconstructed 821 forensic images, extracted one million audit events, and accurately detected masqueraders. Evaluation revealed that developed methods reduced storage requirements 50-fold. This paper describes the PMF architecture, performance of TractorBeam throughout the protocol, and results of the masquerading user analysis.

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A general strategy for differential forensic analysis

Cited by 33 publications

References 14 publications

Performance of a Logical, Five- Phase, Multithreaded, Bootable Triage Tool

Performance of a Logical, Five- Phase, Multithreaded, Bootable Triage Tool

Building a Forensic Computing Language

Generating a Corpus of Mobile Forensic Images for Masquerading user Experimentation

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