Forensic Field Research Articles

Indonesian news article authorship attribution multilabel multiclass classification using IndoBERT

<p class="p1">Recent developments in technology have made it easier to produce digital con- tent, especially textual articles. But, it has a negative impact in the form of a rising public skepticism of digital data due to plagiarism. Indonesia, one of the world’s most populous countries, is not resistant to this problem. To resolve it, the authorship attribution (AA) task must be executed. However, there has been little investigation on AA for Indonesian articles. As a result, this research applies the AA task to an Indonesian digital news articles dataset. Continuing the previous research, dataset modification was carried out to increase data com- plexity by adding a new class, namely the author’s gender, and also by balancing the distribution of data versus labels to minimize potential overfitting, and model hyper-parameter configurations were carried out to enhance the results gained. This research successfully applied the IndoBERT model to the Indonesian AA task, yielding results in the form of precision = 0.92, recall = 0.90, and F1-score = 0.91. These results indicate that the Indonesian AA task has a lot of potential for development since it identifies writing patterns that may benefit the forensic field, detect plagiarism, and analyze Indonesian texts.</p>

Evaluating Nuclear Forensic Signatures for Advanced Reactor Deployment: A Research Priority Assessment

The development and deployment of a new generation of nuclear reactors necessitates a thorough evaluation of techniques used to characterize nuclear materials for nuclear forensic applications. Advanced fuels proposed for use in these reactors present both challenges and opportunities for the nuclear forensic field. Many efforts in pre-detonation nuclear forensics are currently focused on the analysis of uranium oxides, uranium ore concentrates, and fuel pellets since these materials have historically been found outside of regulatory control. The increasing use of TRISO particles, metal fuels, molten fuel salts, and novel ceramic fuels will require an expansion of the current nuclear forensic suite of signatures to accommodate the different physical dimensions, chemical compositions, and material properties of these advanced fuel forms. In this work, a semi-quantitative priority scoring system is introduced to identify the order in which the nuclear forensics community should pursue research and development on material signatures for advanced reactor designs. This scoring system was applied to propose the following priority ranking of six major advanced reactor categories: (1) molten salt reactor (MSR), (2) liquid metal-cooled reactor (LMR), (3) very-high-temperature reactor (VHTR), (4) fluoride-salt-cooled high-temperature reactor (FHR), (5) gas-cooled fast reactor (GFR), and (6) supercritical water-cooled reactor (SWCR).

Examining Wrongful Convictions Based on Fingerprint Evidence

Fingerprint evidence has long been seen as a cornerstone of forensic science, valued for its unique traits and reliability. However, some wrongful conviction cases reveal significant flaws in how fingerprint evidence is collected, interpreted, and relied upon, highlighting its limitations. This article reviews key cases like those of Brandon Mayfield, Stephen Cowans, and Shirley McKie, where mistaken interpretations led to serious injustices. Contributing factors to these erroneous convictions include unclear or incomplete prints, personal biases, laboratory errors, and systemic issues within fingerprint databases. Moreover, cognitive biases can influence analysts' judgments, especially in high-stress scenarios. To improve accuracy and ensure justice, the forensic field must refine evidence collection techniques, enhance examiner training, establish reliable databases, include independent witnesses in searches and seizures, record processes with video documentation from scene of crime to the forensic laboratory, and support fingerprint evidence with additional methods along with improved protocols, blind testing, and independent verification to mitigate risks and preserve the reliability of fingerprint evidence in the justice system. While fingerprints remain vital in forensic investigations, it’s crucial to reevaluate their use to prevent future wrongful convictions.

The photographic sign and the trichotomy of the trace

This article offers a novel perspective on the specific understanding of the photographic sign, situating the trace at the core of its functioning. The photographic sign is subjected to Peirce semiotics analysis, which reveals its underlying structure. This decomposition allows the establishment of a semiotic model that clarifies the essence and characteristics of photography and draws certain broader lessons about the notion of trace. On this basis, three categories of object are distinguished the trace, the indicant and the print. These three objects constitute what we call the Trichotomy of the trace which takes on its full meaning in the forensic field. Building upon this triadic model and our analysis of photography, we propose a refined definition of the trace.

A preliminary study on detecting human DNA in aquatic environments: Potential of eDNA in forensics

Human environmental DNA (eDNA) application have not been fully applied or adequately considered in the fields of eDNA and forensics. Nonetheless, this technique holds great potential as a complementary tool for detecting human DNA in aquatic environments, particularly in cases involving crimes connect to such environments. However, the detectability or stability of eDNA can vary depending on several factors. Therefore, this preliminary study investigates the detection and degradation rates of human eDNA, as well as the recovery of nuclear short tandem repeat (STR) profiles and mitochondrial DNA (mtDNA) sequencing, using water samples from both saltwater and freshwater sources. To conduct the experiment, whole human blood was spiked into the water samples. Water samples were then filtered using a 5 µm pore size filter, and samples were collected at various time intervals up to 23 days. A human specific qPCR assay targeting HV1 region of human mtDNA was used to detect human eDNA. Results demonstrated that human eDNA remains detectable for up to 36 hours in freshwater samples and up 84 hours in saltwater samples. The limit of detection (LOD) of human eDNA, (205 copies/µl), was achieved after 60 hours in freshwater and 180 hours in saltwater samples. Partial STR profiles could be recovered up to 24 hours for freshwater and saltwater. Results from mtDNA sequencing indicate that full mtDNA profiles could be recovered from freshwater samples up to 48 hours and remained detectable up to 72 hours in saltwater. Overall, the findings of this study underscore the importance of considering and incorporating human eDNA analysis as a valuable tool in forensic practice. By harnessing the power of eDNA, law enforcement agencies can enhance their investigation capabilities, improve the accuracy of forensic reconstructions, and ultimately contribute to the resolution of cases involving aquatic environments. Further research and validation are needed to optimize and expand the utilization of eDNA techniques in forensic investigations.

Decoding digital interactions: An extensive study of TeamViewer's Forensic Artifacts across Windows and android platforms

The pervasive influence of digital technology has ushered in a new era of connectivity, reshaping the landscape of forensic science and challenging investigators to adapt to evolving methods of digital interaction. Remote access applications (RAAs) like TeamViewer have become integral tools for facilitating remote collaboration and support across various platforms. However, the widespread adoption of such applications has also led to an increase in cybercrimes, underscoring the critical need for meticulous forensic analysis. This study presents a comprehensive examination of TeamViewer's forensic artifacts across Windows and Android platforms, employing advanced forensic techniques such as registry analysis, disk forensics, memory forensics, and Android forensics. By meticulously dissecting digital evidence and uncovering valuable insights into user interactions, configuration settings, and session dynamics, this research aims to enhance understanding of remote access activities and empower forensic investigators with the tools needed to combat cybercrimes effectively. The findings highlight the forensic significance of each investigative approach and underscore the importance of continuous innovation in the field of digital forensics.

Towards a unified XAI-based framework for digital forensic investigations

Explainable Artificial Intelligence (XAI) aims to alleviate the black-box AI conundrum in the field of Digital Forensics (DF) (and others) by providing layman-interpretable explanations to predictions made by AI models. It also handles the increasing volumes of forensic images that are impossible to investigate via manual methods; or even automated forensic tools. A holistic, generalized, yet exhaustive framework detailing the workflow of XAI for DF is proposed for standardization. A case study examining the implementation of the framework in a network forensics investigative scenario is presented for demonstration. In addition, the XAI-DF project lays the basis for a collaborative effort from the forensics community, aimed at creating an open-source forensic database that may be employed to train AI models for the digital forensics domain. As an onset contribution to the project, we create a memory forensics database of 27 memory dumps (Windows 7, 10, and 11) simulating malware activity and extracting relevant features (specific to processes, injected code, network connections, API hooks, and process privileges) that may be used for training, testing, and validating AI models in keeping with the XAI-DF framework.

Unveiling image source: Instance-level camera device linking via context-aware deep Siamese network

Unveiling the source of an image is one of the most effective ways to validate the originality, authenticity, and reliability in the field of digital forensics. Source camera device identification can identify the specific camera device used to take a photo under investigation. While great progress has been made by the photo-response non-uniformity (PRNU)-based methods over the past decade, the challenge of instance-level source camera device linking, which verifies whether two images in question were captured by the same camera device, remains significant. This challenge is mainly due to the absence of auxiliary images to construct a clean camera fingerprint for each camera, particularly dealing with small image sizes. To overcome this limitation, in this paper, we formulate the task of source device linking as a binary classification problem and propose a simple yet effective framework based on a context-aware deep Siamese network. We take advantage of a Siamese architecture to extract the intrinsic camera device-related noise patterns from a pair of image patches in parallel for comparisons without any auxiliary images. Moreover, a recurrent criss-cross group is utilized to aggregate contextual information in the noise residual maps to alleviate the problem that PRNU noise maps are easily contaminated by the additive noises from image contents. For reliable device linking, we employ a patch-selection strategy on a pair of test images to adaptively choose suitable image patch pairs according to image contents. The final decision of a pair of test images is obtained from the average similarity score of the selected image patch pairs. Compared with existing state-of-the-art methods, our proposed framework can achieve better performance on both the tasks of source camera identification and source device linking without any prior knowledge, i.e., reliable camera fingerprints, regardless of whether the camera devices are “seen” or “unseen” in the training stage. The experimental results on two standard image forensic datasets demonstrate that the proposed method not only shows robustness with respect to different image patch sizes and image quality degenerations, but also has a generalization ability across digital camera and smartphone devices.

Forensic analysis of bad USB attacks: A methodology for detecting and mitigating malicious USB device activities

BadUSB is one of the most dangerous cybersecurity threats, given that it uses the firmware of USB devices to perform various undetectable actions with numerous tools. This research aims to evaluate the efficiency of different forensic approaches, such as signature-based detection, behavioral analysis, and the machine learning (ML) approach, in detecting and analyzing BadUSB attacks. Experiments were conducted with preconfigured USB peripherals to perform keystroke injection, data exfiltration, malware delivery, and network traffic manipulation. The analysis shows that the behavioral analysis and the ML-based methods show high detection accuracy and low false positives. Machine learning detection is the most efficient method. Behavioral analysis had higher accuracy in detecting abnormal device behavior but had a longer detection time than the ML methods. This research beneficently addresses the issues and challenges in the field of digital forensics and calls for further improvement in the detection methods. It proposes ways to implement these methods within the existing cybersecurity models. Future studies should focus on the best approaches to fine-tune these techniques, diversify datasets for machine learning detection methods, and advance methodologies in forensics to accommodate new generations of technologies like the Internet of Things and cloud systems.

Formation of Fully Stoichiometric, Oxidation-State Pure Neptunium and Plutonium Dioxides from Molecular Precursors.

Amidate-based ligands (N-(tert-butyl)isobutyramide, ITA) bind κ2 to form homoleptic, 8-coordinate complexes with tetravalent 237Np (Np(ITA)4, 1-Np) and 242Pu (Pu(ITA)4, 1-Pu). These compounds complete an isostructural series from Th, U-Pu and allow for the direct comparison between many of the early actinides with stable tetravalent oxidation states by nuclear magnetic resonance (NMR) spectroscopy and single crystal X-ray diffraction (SCXRD). The molecular precursors are subjected to controlled thermolysis under mild conditions with the exclusion of exogenous air and moisture, facilitating the removal of the volatile organic ligands and ligand byproducts. The preformed metal-oxygen bond in the precursor, as well as the metal oxidation state, are maintained through the decomposition, forming fully stoichiometric, oxidation-state pure NpO2 and PuO2. Powder X-ray diffraction (PXRD), scanning transmission electron microscopy (STEM), and energy dispersive X-ray spectroscopy (EDS) elemental mapping supported the evaluation of these high-purity materials. This chemistry is applicable to a wide range of metals, including actinides, with accessible tetravalent oxidation states, and provides a consistent route to analytical standards of importance to the field of nuclear nonproliferation, forensics, and fundamental studies.

In vivo video microscopy of the rupturing process of thin blood vessels to clarify the mechanism of bruising caused by blunt impact: an animal study

BackgroundThe thresholds of mechanical inputs for bruising caused by blunt impact are important in the fields of machine safety and forensics. However, reliable data on these thresholds remain inadequate owing to a lack of in vivo experiments, which are crucial for investigating the occurrence of bruising. Since experiments involving live human participants are limited owing to ethical concerns, finite-element method (FEM) simulations of the bruising mechanism should be used to compensate for the lack of experimental data by estimating the thresholds under various conditions, which requires clarifying the mechanism of formation of actual bruises. Therefore, this study aimed to visualize the mechanism underlying the formation of bruises caused by blunt impact to enable FEM simulations to estimate the thresholds of mechanical inputs for bruising.MethodsIn vivo microscopy of a transparent glass catfish subjected to blunt contact with an indenter was performed. The fish were anesthetized by immersing them in buffered MS-222 (75–100 mg/L) and then fixed on a subject tray. The indenter, made of transparent acrylic and having a rectangular contact area with dimensions of 1.0 mm × 1.5 mm, was loaded onto the lateral side of the caudal region of the fish. Blood vessels and surrounding tissues were examined through the transparent indenter using a microscope equipped with a video camera. The contact force was measured using a force-sensing table.ResultsOne of the processes of rupturing thin blood vessels, which are an essential component of the bruising mechanism, was observed and recorded as a movie. The soft tissue surrounding the thin blood vessel extended in a plane perpendicular to the compressive contact force. Subsequently, the thin blood vessel was pulled into a straight configuration. Next, it was stretched in the axial direction and finally ruptured.ConclusionThe results obtained indicate that the extension of the surrounding tissue in the direction perpendicular to the contact force as well as the extension of the thin blood vessels are important factors in the bruising mechanism, which must be reproduced by FEM simulation to estimate the thresholds.

Peculiarities of forensic characterization in the investigation of criminal offenses committed by judges

The article is devoted to the analysis of the degree of scientific development of the issues of criminalistic characterization. The scientific approaches to determining the essence of the criminalistic characterization of crimes in the structure of the investigation methodology are considered. The importance of this scientific category is emphasized. It is noted that one of the most important components in the structure of the forensic methodology is the forensic characterization of a crime. The author reviews the literature in the field of criminal law, criminal procedure, forensics, and operational and investigative activities related to abuse of power or official position by a judge in the administration of justice, and also their detection and investigation. The author presents different approaches to the concept and structure of forensic characteristics in general and, in particular, to the structure of forensic characteristics of acceptance of an offer, promise or receipt of an unlawful benefit. Based on the results of the analysis of court practice on combating undue advantage in Ukraine in recent years, it is established that a significant share of such encroachments falls on the judiciary. The author analyzes the concept and components of the forensic characterization of criminal offenses committed by judges. It is found that its structure includes the following elements: identity of the offender, identity of the victim, method of commission, object of the offense, setting, time and place of commission, motive and purpose of the criminal offense, typical traces of the crime (“trace pattern”). The existence of interrelations between the elements of forensic characterization makes it possible to use a systematic approach in the study of this issue. It is stated that the subject of criminal encroachment is an unlawful remuneration; the author identifies the ways of committing and concealing a crime; the author proposes to divide the ways of direct receipt of unlawful benefit into certain types; the elements of the “trace picture” are revealed; it is emphasized that the most typical places of giving and receiving unlawful benefit by judges are the office, other premises of a particular institution or organization, and public places; the author also emphasizes the characteristic features of the offender and the victim. The analysis of monographs, dissertations and other scientific works on the outlined issues has shown that the fundamentals of the methodology for investigating criminal offenses committed by judges remain undeveloped.

Smartphone-sensor-based human activities classification for forensics: a machine learning approach

The accurate classification of human activities in crime scenes during forensics (criminalistics) is of utmost importance in classifying suspicious and unlawful activities, easing their acceptability and interpretability by judges during legal procedures in courts or by other non-experts in the field of forensics. This paper implements machine learning (ML) algorithms: support vector machine (SVM) and decision tree (DT), to demonstrate with a high accuracy, how data emanating from smartphones’ sensors reveal and isolate relevant information about static and dynamic human activities in criminalistics. Smartphones’ data from five different sensors (accelerometer, gravity, orientation, Gyroscope and light), related to ten recurrent crime scenes activities, grouped into three classes of events (normal, felony and none-felony events) are classified by the proposed algorithms, with novelty being the classification decisions based on the entire period of the events and not instantaneous decision makings. Three independent data-subsets were made, with permutations done between them and at each time, two sets used for training and the third set used for testing. Time- and frequency-domain features were initially used separately and then combined for the model training and testing. The best average training accuracies of 100% and 97.8% were obtained for the DT and SVM, respectively, and the testing accuracies of 89.1% were obtained for both algorithms. We therefore believe that these results will serve as a solid persuasive and convincing argument to judges and non-experts of the field of forensics to accept and easily interpret computer-aided classification of suspicious activities emanating from criminalistic studies.

Artificial Intelligence in Forensic Sciences Revolution or Invasion? Part II

Aim: The study is on the emerging role of artificial intelligence in the forensic sciences. After clarifying the basic concepts and a brief historical overview, the possibilities of using AI in various forensic fields are discussed: genetics, pattern recognition, chemistry, toxicology, anthropology, forensic medicine, and scene reconstruction. Methodology: The study synthesises several recently published international papers. Findings: The penetration of the application of artificial intelligence into some fields of science is undoubtedly an ongoing process. Most of the varied forensic fields also cannot avoid this development. Analysing large databases unmanageable with traditional methods, pattern recognition, and machine learning can all be important tools for forensic science. However, an important conclusion is that AI is a supporter of human expert work, not a substitute. Value: In the field of forensic sciences, no such detailed summary article has been published in Hungarian so far.

Mesterséges intelligencia a törvényszéki tudományokban Revolúció vagy invázió? II. rész

Aim: The study is on the emerging role of artificial intelligence in the forensic sciences. After clarifying the basic concepts and a brief historical overview, the possibilities of using AI in various forensic fields are discussed: genetics, pattern recognition, chemistry, toxicology, anthropology, forensic medicine, and scene reconstruction. Methodology: The study synthesises several recently published international papers. Findings: The penetration of the application of artificial intelligence into some fields of science is undoubtedly an ongoing process. Most of the varied forensic fields also cannot avoid this development. Analysing large databases unmanageable with traditional methods, pattern recognition, and machine learning can all be important tools for forensic science. However, an important conclusion is that AI is a supporter of human expert work, not a substitute. Value: In the field of forensic sciences, no such detailed summary article has been published in Hungarian so far.

Development of an accelerated ageing protocol for the study of phytocannabinoid stability in Cannabis sativa L.

Cannabis sativa L. is a plant belonging to the Cannabaceae family known primarily for its recreational use due to the psychoactive properties of Δ9-tetrahydrocannabinol (THC). Despite this, several compounds belonging to the category of phytocannabinoids have shown in recent years a number of potentially promising therapeutic effects that have increased the interest in the pharmaceutical field towards this plant. However, the content of these compounds is very variable and influenced by different factors, such as growing conditions and time of the year. An indication of the status and age of Cannabis samples is provided by the content of CBN, a minor phytocannabinoid and degradation product of other phytocannabinoids, including THC. In this research work an innovative, solid state analytical approach has been developed to observe and evaluate the variations in the content of two phytocannabinoids (CBN and CBD) in Cannabis-derived products over time. In order to simulate the ageing of the Cannabis samples, an artificially accelerated ageing procedure has been developed and optimised by using high temperatures. The analyses were carried out using an innovative ATR-FTIR method for solid state analysis, enabling direct analysis of a solid sample without any pretreatment phase. This study has allowed the development of an innovative analytical approach for the evaluation of the age and state of conservation of Cannabis samples and may be a useful tool both in the industrial, pharmaceutical and forensic fields.

IoT Forensics: Current Perspectives and Future Directions.

The Internet of Things forensics is a specialised field within digital forensics that focuses on the identification of security incidents, as well as the collection and analysis of evidence with the aim of preventing future attacks on IoT networks. IoT forensics differs from other digital forensic fields due to the unique characteristics of IoT devices, such as limited processing power and connectivity. Although numerous studies are available on IoT forensics, the field is rapidly evolving, and comprehensive surveys are needed to keep up with new developments, emerging threats, and evolving best practices. In this respect, this paper aims to review the state of the art in IoT forensics and discuss the challenges in current investigation techniques. A qualitative analysis of related reviews in the field of IoT forensics has been conducted, identifying key issues and assessing primary obstacles. Despite the variety of topics and approaches, common issues emerge. The majority of these issues are related to the collection and pre-processing of evidence because of the counter-analysis techniques and challenges associated with gathering data from devices and the cloud. Our analysis extends beyond technological problems; it further identifies the procedural problems with preparedness, reporting, and presentation as well as ethical issues. In particular, it provides insights into emerging threats and challenges in IoT forensics, increases awareness and understanding of the importance of IoT forensics in preventing cybercrimes, and ensures the security and privacy of IoT devices and networks. Our findings make a substantial contribution to the field of IoT forensics, as they not only involve a critical analysis of the challenges presented in existing works but also identify numerous problems. These insights will greatly assist researchers in identifying appropriate directions for their future research.

ВОЗМОЖНОСТИ ПОЛУЧЕНИЯ И ИСПОЛЬЗОВАНИЯ КРИМИНАЛИСТИЧЕСКИ ЗНАЧИМОЙ ИНФОРМАЦИИ ИЗ МЕТАДАННЫХ ФАЙЛОВ ПРИ РАСКРЫТИИ И РАССЛЕДОВАНИИ ПРЕСТУПЛЕНИЙ

Modern technologies and the digitalization of society have led to the fact that most of the information in the world is stored and transmitted electronically. This circumstance opens up new opportunities for law enforcement agencies in the detection and investigation of crimes. In today's world, where technology plays a key role in society, digital footprints are becoming an important element in crime investigation. Everyone has already got used to the fact that the main object of computer expertise in the field of computer information is the contents of files. However, such an important area as the study of file metadata remains underestimated in the investigation process. Metadata is an integral part of mod-ern crime investigation, providing investigators with valuable data for analysis and helping to restore the chronology of events and actions of persons associated with the crime. In the field of digital fo-rensics, special attention should be paid to the study and analysis of electronic traces that can be found in metadata. The issues of using file metadata have been touched upon in one way or another by many scien-tists, such as L.A. Buraeva [1], V.A. Gauzhaeva [2], R.R. Kardanov [3], Yu.M. Usoltsev [4], A.S. Arutyunov [5] and others. However, these authors made only an attempt to draw attention to the use of metadata in the investigation of crimes. Metadata may contain information about the time the file was created, its author, location, and other data that can be used in proving criminal cases. Metadata in the commission of crimes related to the use of information and telecommunication technologies can be compared with micro-objects in the commission of traditional crimes. Both are invisible traces, which are not so easy to destroy and to which few criminals pay attention. At the same time, they can provide significant assistance to the investigation in uncovering and investigat-ing crimes. This article attempts to draw the attention of the scientific world and employees involved in the preliminary investigation of crimes to the problems and possibilities of using metadata in the process of disclosure and investigation of crimes.

Microscopic analysis of cut mark characteristics from chopping/hacking tools

Evaluating sharp force trauma (SFT) injuries to bone inflicted by a larger class of chopping/hacking tools (i.e., swords, axes, hatchets, machetes, and cleavers) is a growing area within the field of forensics. Previous studies have demonstrated promise regarding tool differentiation through the utilization of microscopic cut mark characteristics. However, this is an area that warrants additional investigation as there has yet to be a comprehensive study that incorporates the majority of these microscopic chopping/hacking cut mark characteristics into one analysis. The purpose of the current research was to analyze a large sample of microscopic cut mark characteristics derived from the current chopping/hacking literature to determine if differentiation of tool type could be made based on the microscopic cut mark characteristics. An additional goal of the current research is to develop standardization guidelines for the assessment of cut marks, focusing on a comprehensive suite of microscopic cut mark characteristics commonly observed in the existing literature. The skeletal sample for the current research was derived from a previous macroscopic cut mark characteristic experiment where trauma was inflicted to 20 partially fleshed domestic pig (Sus scrofa domesticus) limbs utilizing four chopping/hacking tools (i.e., axe, hatchet, machete, and cleaver) as well as a large carving knife for comparison. Cut marks were evaluated for 15 microscopic cut mark characteristics to assess statistical significance. Utilizing a chi-square analysis, nine of the 15 microscopic cut mark characteristics demonstrated statistically significant differences in relation to the tool utilized, indicating moderate to relatively strong effect sizes. For example, it should be possible to use a combination of microscopic cut mark characteristics to potentially indicate which chopping/hacking tool inflicted trauma when analyzing bones. In particular, examining the characteristics such as regularity of the cut mark edges along with the occurrence of uprising, fossae/depressions, and microscopic fractures can suggest or exclude tool class within forensic contexts.

Investigation of biodistribution by liquid-phase microextraction: Using a fatal diphenidol poisoning case

Liquid-phase microextraction (LPME) possesses a high potential to isolate organic substances from different sample matrices. In this work, LPME was applied for the first time to investigate the biodistribution of diphenidol in different biofluids, organs, and brain regions using a fatal poisoning case. Since the LPME of diphenidol hasn't been reported, the effect of supported liquid membrane (SLM), acceptor and donor phases, and extraction time on LPME performance was investigated first. The solvents of 2-nonanone and 2-nitrophenyl octyl ether (NPOE) were found to be stable and efficient SLMs for LPME of diphenidol from biofluids and tissue samples, respectively. At steady state, the LPME recoveries for different sample matrices were in the range of 87 %-91 %. Due to the clean-up capability of LPME and the relatively high concentration of diphenidol in the fatal poisoning case, the proposed LPME systems were validated with related sample matrices using HPLC-UV for the determination. The methods displayed good linearity (R² ≥ 0.9943), and the limits of detection were 0.30 mg L−1, 0.28 mg L−1, and 2.7 μg g−1 for blood, urine, and liver samples, respectively. Meanwhile, the precision (≤13%), accuracy (90–110%), and matrices effect (±15%) were satisfactory at low, medium, and high concentrations. In addition, the stability, carryover, and dilution integrity met the requirements of ASB Standard 036. Finally, the proposed method was successfully applied to evaluate the biodistribution of diphenidol in five different biofluids, five organs, and six brain regions from a fatal poisoning case. Generally, the distribution of diphenidol in biofluids was lower than that in the organs and brain regions, and the highest concentration of diphenidol was observed in the liver, which is very important for the selection of inspection samples in forensic toxicological analysis. Therefore, LPME was proved to be a powerful tool for the investigation of biodistribution and postmortem redistribution in the fields of forensics.