The results of the evidence analysis phase in Digital Forensics (DF) provide objective data which however require further elaboration by the investigators, that have to contextualize analysis results within an investigative environment so as to provide possible hypotheses that can be proposed as proofs in court, to be evaluated by lawyers and judges. Aim of our research has been that of exploring the applicability of Answer Set Programming (ASP) to the automatization of evidence analysis. This offers many advantages, among which that of making different possible investigative hypotheses explicit, while otherwise different human experts often devise and select different solutions in an implicit way. Moreover, ASP provides a potential for verifiability which is crucial in such an application field. Very complex investigations for which human experts can hardly find solutions turn out in fact to be reducible to optimization problems in classes P or NP or not far beyond, that can be thus expressed in ASP. As a proof of concept, in this paper we present the formulation of some real investigative cases via simple ASP programs, and discuss how this leads to the formulation of concrete investigative hypotheses.

How answer set programming can help in digital forensic investigation

COSTANTINI, STEFANIA;DE GASPERIS, GIOVANNI;OLIVIERI, RAFFAELE
2015-01-01

Abstract

The results of the evidence analysis phase in Digital Forensics (DF) provide objective data which however require further elaboration by the investigators, that have to contextualize analysis results within an investigative environment so as to provide possible hypotheses that can be proposed as proofs in court, to be evaluated by lawyers and judges. Aim of our research has been that of exploring the applicability of Answer Set Programming (ASP) to the automatization of evidence analysis. This offers many advantages, among which that of making different possible investigative hypotheses explicit, while otherwise different human experts often devise and select different solutions in an implicit way. Moreover, ASP provides a potential for verifiability which is crucial in such an application field. Very complex investigations for which human experts can hardly find solutions turn out in fact to be reducible to optimization problems in classes P or NP or not far beyond, that can be thus expressed in ASP. As a proof of concept, in this paper we present the formulation of some real investigative cases via simple ASP programs, and discuss how this leads to the formulation of concrete investigative hypotheses.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/111725
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