Digital forensics and investigations meet artificial intelligence

In the frame of Digital Forensic (DF) and Digital Investigations (DI), the “Evidence Analysis” phase has the aim to provide objective data, and to perform suitable elaboration of these data so as to help in the formation of possible hypotheses, which could later be presented as elements of proof in...

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Vydáno v:Annals of mathematics and artificial intelligence Ročník 86; číslo 1-3; s. 193 - 229
Hlavní autoři: Costantini, Stefania, De Gasperis, Giovanni, Olivieri, Raffaele
Médium: Journal Article
Jazyk:angličtina
Vydáno: Cham Springer International Publishing 01.07.2019
Springer
Springer Nature B.V
Témata:
Artificial Intelligence
Complex Systems
Complexity
Computer forensics
Computer Science
Computers
Decision support systems
Declarative programming
Forensic computing
Hypotheses
Investigations
Mathematical programming
Mathematics
Services
Software
Digital investigation
Automatic investigation
68T27
Digital forensics
Answer set programming
Forensic models
Artificial intelligence
97R40
ISSN:1012-2443, 1573-7470
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Popis
Shrnutí:In the frame of Digital Forensic (DF) and Digital Investigations (DI), the “Evidence Analysis” phase has the aim to provide objective data, and to perform suitable elaboration of these data so as to help in the formation of possible hypotheses, which could later be presented as elements of proof in court. The aim of our research is to explore the applicability of Artificial Intelligence (AI) along with computational logic tools – and in particular the Answer Set Programming (ASP) approach — to the automation of evidence analysis. We will show how significant complex investigations, hardly solvable for human experts, can be expressed as optimization problems belonging in many cases to the ℙ or ℕℙ complexity classes. All these problems can be expressed in ASP. As a proof of concept, in this paper we present the formalization of realistic investigative cases via simple ASP programs, and show how such a methodology can lead to the formulation of tangible investigative hypotheses. We also sketch a design for a feasible Decision Support System (DSS) especially meant for investigators, based on artificial intelligence tools.
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ISSN:1012-2443
1573-7470
DOI:10.1007/s10472-019-09632-y