A review of quality procedures in the UK forensic sciences: What can the field of digital forensics learn?

Abstract

With a growing reliance on the various forms of forensic science evidence in complex criminal investigations, the measures for ensuring its quality are facing increasing scrutiny. Improvements to quality management systems to ensure both the robust application of scientific principles and the accurate interpretation and reporting of results, have arisen as a consequence of high-profile rebuttals of forensic science evidence combined with process improvements driven by evaluation of current practice. These improvements are crucial to ensure validity of results as well as maintaining the trust of all those involved in the Criminal Justice System. This work first examines the quality management systems utilised for the examination and analysis of fingerprint, body fluid and DNA evidence. It then proceeds to highlight an apparent lack of comparable quality assurance mechanisms within the field of digital forensics, the newest branch of forensic science. Proposals are provided for the improvement of quality assurance for the digital forensics arena, drawing on the experiences of, and more well-established practices within, other forensic disciplines.

Towards reliable digital forensics investigations through measurement science

“…Recent research has identified human factors that can cause error during the analysis of digital evidence. Page et al () noted that digital forensics lacks formalized qualifications for examiners, needs more rigorous standards for peer review, and lacks a regulating body. As issues related to the correct interpretation of evidence can persist even when considering reliable data using multiple tools or fully validated tools cannot ensure overall reliability absent analyst competence.…”

“…Error is the estimation of how often a tool reports inaccurate information, both in terms of failing to reject a true null hypothesis (false positive) or failing to reject a false null hypothesis (false negative). In the context of digital forensics examination, the sources of potential error and uncertainty are understood as primarily originating from problems in the algorithms used during analysis, problems in the implementation and execution of the algorithms, and human factors (Horsman, ; Lyle, ; Page et al, ). However, quantifying the contributions of those factors remains elusive and difficult (Lyle, ).…”

Standard Representation for Digital Forensic Processing

“…Currently, the scientific validation in digital forensics is predominantly focused on tool testing [16]. Often objective measurements for the forensic processing, reproducibility documentation, and quality of the decisions taken by the examiner are missing [17]. The current situation will be further complicated due to advancement in new research focused on machine-intelligence approaches to utilize computer power and reduce the information overhead in digital forensics [18].…”

Collective responses to heterospecifics emerge from individual differences in aggression

“…We further determined the relationship between aggressive behavior and spatial exploration, a repeatable behavior in L. humile B A T. sessile workers (Page et al 2019). We examined the relationship between aggression and spatial exploration because the collective behaviors we observed (detailed below) could be interpreted as either a result of variation in aggression or variation in spatial exploration.…”

“…For a list of spices used see Hui and Pinter-Wollman (2014). It has been recently shown that this assay provides a reliable, repeatable, and real-time quantification of the spatial exploration of L. humile workers in an open field and in natural conditions (Page et al 2019).…”