Text Mining for Social Harm and Criminal Justice Applications

Indiana University-Purdue University Indianapolis (IUPUI)Increasing rates of social harm events and plethora of text data demands the need of employing text mining techniques not only to better understand their causes but also to develop optimal prevention strategies. In this work, we study three social harm issues: crime topic models, transitions into drug addiction and homicide investigation chronologies. Topic modeling for the categorization and analysis of crime report text allows for more nuanced categories of crime compared to official UCR categorizations. This study has important implications in hotspot policing. We investigate the extent to which topic models that improve coherence lead to higher levels of crime concentration. We further explore the transitions into drug addiction using Reddit data. We proposed a prediction model to classify the users’ transition from casual drug discussion forum to recovery drug discussion forum and the likelihood of such transitions. Through this study we offer insights into modern drug culture and provide tools with potential applications in combating opioid crises. Lastly, we present a knowledge graph based framework for homicide investigation chronologies that may aid investigators in analyzing homicide case data and also allow for post hoc analysis of key features that determine whether a homicide is ultimately solved. For this purpose we perform named entity recognition to determine witnesses, detectives and suspects from chronology, use keyword expansion to identify various evidence types and finally link these entities and evidence to construct a homicide investigation knowledge graph. We compare the performance over several choice of methodologies for these sub-tasks and analyze the association between network statistics of knowledge graph and homicide solvability

A Graph Database Representation of Portuguese Criminal-Related Documents

Organizations have been challenged by the need to process an increasing amount of data, both structured and unstructured, retrieved from heterogeneous sources. Criminal investigation police are among these organizations, as they have to manually process a vast number of criminal reports, news articles related to crimes, occurrence and evidence reports, and other unstructured documents. Automatic extraction and representation of data and knowledge in such documents is an essential task to reduce the manual analysis burden and to automate the discovering of names and entities relationships that may exist in a case. This paper presents SEMCrime, a framework used to extract and classify named-entities and relations in Portuguese criminal reports and documents, and represent the data retrieved into a graph database. A 5WH1 (Who, What, Why, Where, When, and How) information extraction method was applied, and a graph database representation was used to store and visualize the relations extracted from the documents. Promising results were obtained with a prototype developed to evaluate the framework, namely a name-entity recognition with an F-Measure of 0.73, and a 5W1H information extraction performance with an F-Measure of 0.65

Assessing the Quantified Impact of a Hybrid POGIL Methodology on Student Averages in a Forensic Science Survey Course

A causal-comparative/quasi experimental study examined the effect of incorporating a hybrid teaching methodology that blended lecture with Process Oriented Guided Inquiry Lessons (POGILs) on the overall academic achievement of a diverse student body in a large lecture setting. Additional considerations included student gender, ethnicity, declared major (STEM or non-STEM), and SAT scores. An evaluation of the effect that these characteristics had on student achievement due to differentiating import placed on the use of POGILs as a learning tool was included. This study used data obtained from a longitudinal examination of eight years of student data from an introductory forensic science survey course offered in a R1 northeastern university. This study addressed the effectiveness of applying a proscribed active learning methodology, one proposed effective in collegiate education, to a new environment, forensic science. The methodology employed combined fourteen POGILs, created specifically for the chosen course, with didactic lecture during the entire semester of a forensic science survey course. This quasi-experimental design used the manipulation of the independent variable, the use of a hybrid lecture instead of exclusive use of traditional didactic lectures, on the students’ academic achievement on exams given during the course. Participants in this study (N=1436) were undergraduate students enrolled in the single semester introductory science course. A longitudinal study that incorporated eight years of data was completed, 4 years pre-intervention (2007-2010) and 4 years post-intervention (2011-2014). The forensic science survey course, taught by only one professor during the eight-year period, was a science discipline that had yet to integrate an active learning educational model. Findings indicate four variables significantly contributed to explaining nearly 28% of the variation seen in the student class averages earned during the eight-year period: the intervention, gender, STEM majors, and SAT scores. On average, the intervention significantly altered exam scores, F (1, 1431) = 43.019, p \u3c 0.000, R2 = 0.029, raising exam averages 3.1%. Within the population, females outperformed their male counterparts by 1.9%, although both genders were significantly affected by the intervention, F (1, 1431) = 13.698, p \u3c 0.000, R2 = 0.009. Students with declared majors in the STEM fields outperformed the non-STEM fields by 5.6%, a strong factor in the model, F (1, 1431) = 91.918, p \u3c 0.000, R2 = 0.060, with both STEM and non-STEM students being positively affected by the intervention. The SAT scores, however, showed the strongest effect, F (1, 1431) = 345.026, p \u3c 0.000, R2 = 0.179, where an increase of 3.1% in the student class averages could be seen for every 100 points earned on the SATs. Further discussions include implications and correlations to recent research and directions for future research

Image and Video Forensics

Nowadays, images and videos have become the main modalities of information being exchanged in everyday life, and their pervasiveness has led the image forensics community to question their reliability, integrity, confidentiality, and security. Multimedia contents are generated in many different ways through the use of consumer electronics and high-quality digital imaging devices, such as smartphones, digital cameras, tablets, and wearable and IoT devices. The ever-increasing convenience of image acquisition has facilitated instant distribution and sharing of digital images on digital social platforms, determining a great amount of exchange data. Moreover, the pervasiveness of powerful image editing tools has allowed the manipulation of digital images for malicious or criminal ends, up to the creation of synthesized images and videos with the use of deep learning techniques. In response to these threats, the multimedia forensics community has produced major research efforts regarding the identification of the source and the detection of manipulation. In all cases (e.g., forensic investigations, fake news debunking, information warfare, and cyberattacks) where images and videos serve as critical evidence, forensic technologies that help to determine the origin, authenticity, and integrity of multimedia content can become essential tools. This book aims to collect a diverse and complementary set of articles that demonstrate new developments and applications in image and video forensics to tackle new and serious challenges to ensure media authenticity

Applications of micro-CT in the Criminal Justice System of England and Wales: an impact assessment

The Criminal Justice System of England and Wales is currently facing major challenges. One is the financial pressure of government funding cuts, the other the increasing need for professionalisation and rigour within the system. This thesis presents the use of micro Computed Tomography, Additive Manufacturing, and 3D visualisation to address both challenges. By drawing on data from live murder investigations the project examines how these digital technologies can be used to improve the investigation of strangulation deaths, sharp force injuries, and fractures. Each of these categories was treated as a separate case in the overall multiple-case study research design. The increased detail enabled by micro-CT assisted pathologists in the diagnosis of strangulation as previously undetected injuries of the larynx could be identified. A validation study comparing injured to uninjured samples was conducted to increase the strength of the interpretations. For sharp force injuries analysis, micro-CT proved useful for providing the necessary injury characteristics and highly accurate measurements to allow weapon identification. The high resolution of micro-CT scanning also enabled the visualisation of trauma on the smallest of skeletal elements, often encountered in non-accidental injuries in children. The cross-case synthesis revealed the main themes of clarity, objectivity, and visualisation which were improved by using micro-CT irrespective of type of homicide. The significance of these themes further crystallised in semi-structured interviews conducted with various stakeholders of the Criminal Justice System. Management concepts proved suitable to assess the project’s success as the themes used in operations management such as quality, delivery, and cost apply to the delivery of justice as well. A good working relationship with West Midlands Police’s homicide investigators and researchers at WMG was crucial to providing the technology and expertise to address real-life problems whilst ultimately saving taxpayers’ money

Intensional Cyberforensics

This work focuses on the application of intensional logic to cyberforensic analysis and its benefits and difficulties are compared with the finite-state-automata approach. This work extends the use of the intensional programming paradigm to the modeling and implementation of a cyberforensics investigation process with backtracing of event reconstruction, in which evidence is modeled by multidimensional hierarchical contexts, and proofs or disproofs of claims are undertaken in an eductive manner of evaluation. This approach is a practical, context-aware improvement over the finite state automata (FSA) approach we have seen in previous work. As a base implementation language model, we use in this approach a new dialect of the Lucid programming language, called Forensic Lucid, and we focus on defining hierarchical contexts based on intensional logic for the distributed evaluation of cyberforensic expressions. We also augment the work with credibility factors surrounding digital evidence and witness accounts, which have not been previously modeled. The Forensic Lucid programming language, used for this intensional cyberforensic analysis, formally presented through its syntax and operational semantics. In large part, the language is based on its predecessor and codecessor Lucid dialects, such as GIPL, Indexical Lucid, Lucx, Objective Lucid, and JOOIP bound by the underlying intensional programming paradigm.Comment: 412 pages, 94 figures, 18 tables, 19 algorithms and listings; PhD thesis; v2 corrects some typos and refs; also available on Spectrum at http://spectrum.library.concordia.ca/977460

An examination of the Asus WL-HDD 2.5 as a nepenthes malware collector

The Linksys WRT54g has been used as a host for network forensics tools for instance Snort for a long period of time. Whilst large corporations are already utilising network forensic tools, this paper demonstrates that it is quite feasible for a non-security specialist to track and capture malicious network traffic. This paper introduces the Asus Wireless Hard disk as a replacement for the popular Linksys WRT54g. Firstly, the Linksys router will be introduced detailing some of the research that was undertaken on the device over the years amongst the security community. It then briefly discusses malicious software and the impact this may have for a home user. The paper then outlines the trivial steps in setting up Nepenthes 0.1.7 (a malware collector) for the Asus WL-HDD 2.5 according to the Nepenthes and tests the feasibility of running the malware collector on the selected device. The paper then concludes on discussing the limitations of the device when attempting to execute Nepenthes

Neurological and Mental Disorders

Mental disorders can result from disruption of neuronal circuitry, damage to the neuronal and non-neuronal cells, altered circuitry in the different regions of the brain and any changes in the permeability of the blood brain barrier. Early identification of these impairments through investigative means could help to improve the outcome for many brain and behaviour disease states.The chapters in this book describe how these abnormalities can lead to neurological and mental diseases such as ADHD (Attention Deficit Hyperactivity Disorder), anxiety disorders, Alzheimer’s disease and personality and eating disorders. Psycho-social traumas, especially during childhood, increase the incidence of amnesia and transient global amnesia, leading to the temporary inability to create new memories.Early detection of these disorders could benefit many complex diseases such as schizophrenia and depression

A descriptive analysis of suicides and their interface with healthcare facilities in the Western Cape, South Africa: 2011-2015

BACKGROUND: Suicide is a preventable public health problem affecting 800 000 people every year and 79% occurs in low to middle incomes countries. Males are mostly affected, and at-risk age groups are adolescents and young adults. Hanging, firearms and ingestion of pesticides are amongst the most common methods of suicide. Prevention strategies have been applied by various countries to target the use of common methods of suicide however there is little evidence that supports detection of suicide risk in healthcare facilities. This study profiles all suicides that occurred in the Western Cape during the year 2011-2015 and their interface with the healthcare facilities up to one year prior to death. OBJECTIVES: This study assesses the incidence of suicides in the Western Cape. It tests for associations between methods of suicide and demographic characteristics for suicide. Ascertains the characteristics of those suicide cases who made previous contact with a healthcare facility in the past 12 months and proposes context specific interventions for the prevention of suicides. METHODS: A retrospective descriptive study was conducted. All suicides recorded by the forensic pathology service during the years 2011-2015 were linked to patient data held by the provincial health data centre. A total of 3 561 suicides were recorded during the study period. Crude suicide rates were calculated using population denominator from the Statistics South Africa's national census projections. Multiple logistic regression was used to determine associations between the group utilising various methods of suicide and demographic characteristics. FINDINGS: Males were found to be four times more likely to die from suicide compared to females. The age groups most at risk were 20-39 years. Hanging was the method of choice by males and overdose on medication, in females. Two thirds of the 2 367 suicides were positively linked to healthcare facilities. Most cases who sought healthcare up to one year prior to suicide were males that presented with ‘other medical conditions' rather than mental health conditions. CONCLUSION: This study highlights missed opportunities for the detection of suicide risk for those who seek healthcare for all healthcare conditions. Although suicide rates have remained constant over the assessment period, a key focus for prevention should be interventions applied at healthcare facilities as well as other ‘upstream' preventions that reduce the availability of various methods for suicide