This paper presents a rigorous method for reconstructing events in digital systems. It is based on the idea, that once the system is described as a finite state machine, its state space can be explored to determine all possible scenarios of the incident. To formalize evidence, the evidential statement notation is introduced. It represents the facts conveyed by the evidence as a series of witness stories that restrict possible computations of the finite state machine. To automate event reconstruction, a generic event reconstruction algorithm is proposed. It computes the set of all possible explanations for the given evidential statement with respect to the given finite state machine.

Abstract. This paper introduces a novel approach to user event reconstruction by showing the practicality of generating and implementing signature-based analysis methods to reconstruct high-level user actions from a collection of low-level traces found during a post-mortem forensic analysis of a system. Traditional forensic analysis and the inferences an investigator normally makes when given digital evidence, are examined. It is then demonstrated that this natural process of inferring high-level events from low-level traces may be encoded using signature-matching techniques. Simple signatures using the defined method are created and applied for three popular Windows-based programs as a proof of concept.

This paper expands upon the finite state machine approach for the formal analysis of digital evidence. The proposed method may be used to support the feasibility of a given statement by testing it against a relevant system model. To achieve this, a novel method for modeling the system and evidential statements is given. The method is then examined in a case study example.Comment: 10 pages, 11 figures, Presented at the 1st International Conference on Digital Forensics & Cyber Crim

No abstract

No abstract

As the amount of digital devices suspected of containing digital evidence increases, case backlogs for digital investigations are also increasing in many organizations. To ensure timely investigation of requests, this work proposes the use of signature-based methods for automated action instance approximation to automatically reconstruct past user activities within a compromised or suspect system. This work specifically explores how multiple instances of a user action may be detected using signaturebased methods during a post-mortem digital forensic analysis. A system is formally defined as a set of objects, where a subset of objects may be altered on the occurrence of an action. A novel action-trace update time threshold is proposed that enables objects to be categorized by their respective update patterns over time. By integrating time into event reconstruction, the most recent action instance approximation as well as limited past instances of the action may be differentiated and their time values approximated. After the formal theory if signature-based event reconstruction is defined, a case study is given to evaluate the practicality of the proposed method.

No abstract

No abstract