Open Access
Review
22 April 2025Counterfeit Drug Investigations: Techniques, Challenges, and the Role of Abductive Reasoning
Variable types of investigations exist regarding counterfeit drug detection, disruption, and regulation. Counterfeit drugs are spurious drugs, falsely labelled, falsified, substandard, unregistered/unlicensed, and infringe trademarks. Counterfeit drugs can mimic both legitimate and illegitimate drugs and are often distributed in virtual environments, such as illicit online pharmacies, the surface web, and the dark web. Counterfeit drug operators and operations are the typically corrupt and/or criminal individuals, groups, and techniques by which counterfeit drugs are produced and distributed. The manufacture and distribution of counterfeit drugs are ever-changing, which results in the need for investigative techniques that are equally adaptable and collaborative. Counterfeit drug investigations can be defined according to four categories: medical investigations in hospitals and through autopsies, chemical and non-chemical drug investigations in forensic toxicology laboratories, various track-and-trace technologies used in pharmaceutical industry investigations, and national and global coordinated investigations. Due to the diverse counterfeit drug investigations present, the logic and practice of abduction are highlighted as a primary part of the investigative element to counter ongoing efforts by offenders to evade detection. Abductive rationalities are prioritized in that they are contrary to an increasing reliance on technoscientific modes of data production alone. Rather, abductive reasoning plays a central role in counterfeit drug investigations at the levels of instigating and directing investigations, as well as interpreting and responding to evidential findings.
Open Access
Article
18 June 2025Forensic Value of Exif Data: An Analytical Evaluation of Metadata Integrity across Image Transfer Methods
Exif metadata contained in digital photographs is an important forensic resource, offering authentic information like timestamps, geolocation, and device identifiers. The research assesses the integrity of Exif information on various methods of image transmission, such as USB, email, and messaging platforms like WhatsApp, Telegram, Signal, Instagram, Facebook Messenger, and Snapchat. With the controlled image dataset of Android, iOS phones, and the Flickr Creative Commons collection, we examined metadata preservation using forensic software (Magnet AXIOM, FTK, XRY, ExifTool). Document-based modes and direct transfers (USB, email) maintained all Exif fields and file hashes, providing forensic integrity. Chat/image-based transfers, fueled by compression, effectively remove metadata, changing the file integrity. These results emphasize the necessity of platform-aware evidence handling in order to preserve metadata integrity during digital forensic examinations.
Open Access
Article
23 June 2025A Structured Framework for Formalized and Quantitative Handwriting Examination
The demand for a formalized and transparent approach to handwriting assessment has long been recognized within forensic and legal contexts. A structured methodology not only reduces interpretative subjectivity but also enables quantifiable measurement and ensures greater consistency in evaluations. This article presents a practical framework that models the degree of similarity between handwriting samples—texts and signatures—through a two-stage process: feature-based evaluation and congruence analysis. Both stages produce quantitative markers that are integrated into a unified similarity score, forming the foundation for more complex comparisons involving multiple questions and known texts. The proposed procedure, which is the major result of the paper, is not merely theoretical; it has been applied in real forensic casework, yielding preliminary statistical outcomes. In particular, it demonstrates the discriminative power of different handwriting features. The paper also discusses future directions for development, with a focus on the integration of artificial intelligence (AI) to enhance specific components of the assessment process.
