Criminal Database Research Articles

An efficient ensemble explainable AI (XAI) approach for morphed face detection

Numerous deep neural convolutional architectures have been proposed in literature for face Morphing Attack Detection (MADs) to prevent such attacks and lessen the risks associated with them. Although, deep learning models achieved optimal results in terms of performance, it is difficult to understand and analyze these networks since they are black box/opaque in nature. As a consequence, incorrect judgments may be made. There is, however, a dearth of literature that explains decision-making methods of black box deep learning models for biometric Presentation Attack Detection (PADs) or MADs that can aid the biometric community to have trust in deep learning-based biometric systems for identification and authentication in various security applications such as border control, criminal database establishment etc. In this work, we present a novel visual explanation approach named Ensemble XAI integrating Saliency maps, Class Activation Maps (CAM) and Gradient-CAM (Grad-CAM) to provide a more comprehensive visual explanation for a deep learning prognostic model (EfficientNet-B1) that we have employed to predict whether the input presented to a biometric authentication system is morphed or genuine. The experimentations have been performed on three publicly available datasets namely Face Research Lab London (FRLL) dataset, Wide Multi-Channel Presentation Attack (WMCA) dataset, and Makeup Induced Face Spoofing (MIFS) dataset. The experimental evaluations affirms that the resultant visual explanations highlight more fine-grained details of image features/areas focused by EfficientNet-B1 to reach decisions along with appropriate reasoning.

Insider Threats to the Military Health System: A Systematic Background Check of TRICARE West Providers.

To address the pandemic, the Defense Health Agency (DHA) expanded its TRICARE civilian provider network by 30.1%. In 2022, the DHA Annual Report stated that TRICARE's provider directories were only 80% accurate. Unlike Medicare, the DHA does not publicly reveal National Provider Identification (NPI) numbers. As a result, TRICARE's 9.6 million beneficiaries lack the means to verify their doctor's credentials. Since 2013, the Department of Health and Human Services' (HHS) Office of Inspector General (OIG) has excluded 17,706 physicians and other providers from federal health programs due to billing fraud, neglect, drug-related convictions, and other offenses. These providers and their NPIs are included on the OIG's List of Excluded Individuals and Entities (LEIE). Patients who receive care from excluded providers face higher risks of hospitalization and mortality. We sought to assess the extent to which TRICARE screens health care provider names on their referral website against criminal databases. Between January 1-31, 2023, we used TRICARE West's provider directory to search for all providers within a 5-mile radius of 798 zip codes (38 per state, ≥10,000 residents each, randomly entered). We then copied and pasted all directory results' first and last names, business names, addresses, phone numbers, fax numbers, degree types, practice specialties, and active or closed statuses into a CSV file. We cross-referenced the search results against US and state databases for medical and criminal misconduct, including the OIG-LEIE and General Services Administration's (GSA) SAM.gov exclusion lists, the HHS Office of Civil Rights Health Insurance Portability and Accountability Act (HIPAA) breach reports, 15 available state Medicaid exclusion lists (state), the International Trade Administration's Consolidated Screening List (CSL), 3 Food and Drug Administration (FDA) debarment lists, the Federal Bureau of Investigation's (FBI) list of January 6 federal defendants, and the OIG-HHS list of fugitives (FUG). Our provider search yielded 111,619 raw results; 54 zip codes contained no data. After removing 72,156 (64.65%) duplicate entries, closed offices, and non-TRICARE West locations, we identified 39,463 active provider names. Within this baseline sample group, there were 2398 (6.08%) total matches against all exclusion and sanction databases, including 2197 on the OIG-LEIE, 2311 on the GSA-SAM.gov list, 2 on the HIPAA list, 54 on the state Medicaid exclusion lists, 69 on the CSL, 3 on the FDA lists, 53 on the FBI list, and 10 on the FUG. TRICARE's civilian provider roster merits further scrutiny by law enforcement. Following the National Institute of Standards and Technology 800, the DHA can mitigate privacy, safety, and security clearance threats by implementing an insider threat management model, robust enforcement of the False Claims Act, and mandatory security risk assessments. These are the views of the author, not the Department of Defense or the US government.

Facial Recognition for Criminal Identification using Convolutional Neural Network

The process of identifying and recognising the criminal is the time consuming and difficult task. There are several ways to identify culprits at the crime site, including fingerprinting, DNA matching, and eyewitness testimony. The criminal face identification system will be built on a existing criminal database. The method for identifying a human face using features extrapolated from an image is presented in this study. The technique for identifying a human face using characteristics extrapolated from a picture is presented in this research. It is quite difficult to develop a computer model for recognizing the human face since it is a complicated multidimensional visual representation. The video captured by the camera will be translated into frames as part of the suggested process. To increase detection accuracy, this suggested a Binary Gradient Alignment (BGA) algorithm a description texture classification technique. When a facial feature is detected in an image frame, it undergoes pre-processing to eliminate unnecessary data and reduce unwanted distortions. The real- time processed image is compared to the trained images that have previously been saved in the database. The technology will send an automatic email notice to the police officials if the surveillance camera detects a criminal.

The Benefits of Using INTERPOL’s Criminal Databases – The Hungarian Perspective

Aim: The aim of this article is to give an overview of the benefits of INTERPOL’s databases and to present the related Hungarian experiences. The article was written for the centenary celebration of INTERPOL.Methodology: The article is based on the relevant professional literature, statistics and the author’s professional experience.Findings: The INTERPOL serves as a vital partner in Hungary’s efforts to combat crime, ensure public safety, and protect national security.Value: The article serves as an explanation of worldwide used law enforcement products and gives unique picture on a national practice.

CNN Based Facial Recognition with Age Invariance

Abstract : As the world has seen exponential expansion over the previous decade, there has been an unusual increase in the crime rate as well as an increase in the number of criminals/missing persons. Face recognition can extract the individualistic characteristics of the human face. A straightforward and adaptable biometric technology is face recognition. The technology used to recognize and identify faces in images or videos is called face detection and recognition. The process of removing facial features has gotten easier as technology has advanced. This study describes the use of an automated security camera for realtime face recognition. With this system, we can instantly identify and detect the faces of the criminals in a live video feed captured by a camera. Criminal records typically include the offender's picture and personal information. Thus, we are able to use these photos in addition to his information. The security camera's recorded footage is transformed into frames. After a face is identified in a frame, it undergoes pre-processing and feature extraction. The characteristics of the real-time image processing are compared to those of the images kept in the criminal database.

The Benefits of Using INTERPOL’s Criminal Databases – The Hungarian Perspective

Aim: The aim of this article is to give an overview of the benefits of INTERPOL’s databases and to present the related Hungarian experiences. The article was written for the centenary celebration of INTERPOL.Methodology: The article is based on the relevant professional literature, statistics and the author’s professional experience.Findings: The INTERPOL serves as a vital partner in Hungary’s efforts to combat crime, ensure public safety, and protect national security.Value: The article serves as an explanation of worldwide used law enforcement products and gives unique picture on a national practice.

Design and Analysis of an Expert System for the Detection and Recognition of Criminal Faces

The process of identifying a person using their facial traits is referred to as face recognition, and it is a form of biometric identification. The use of facial recognition might range from that of an entertainment tool to one of a security tool. Even while other forms of biometric identification, such as fingerprints and iris scans, are reliable, they require the active participation of an individual. As a result, criminals cannot rely on them as the most reliable means of verification. When a criminal database, which stores the individual details of a criminal, and facial recognition technology are brought together, it can identify a criminal who is depicted in an image or seen in a video feed. Not only does a criminal recognition system needs to have a high level of accuracy, but it also needs to be able to adapt to significant changes in lighting, occlusion, aging, expressions, and other factors. In this study, they were analyzed and compared with the many methods of face detection and face recognition, such as HAAR cascades, local binary patterns histogram, support vector machines, convolutional neural networks, and ResNet-34. These methods include a variety of different approaches to recognizing faces. An analysis of these strategies is also conducted and then put into practice to those that seem to be the most effective for the designed criminal recognition system. In addition to that, a variety of uses of this criminal recognition in the real world are also discussed.

Blockchain-Based Approach for Tracking Global Criminals

Blockchain is the latest technology, which is now widely used in various fields due to its benefits such as higher tamper-proof security. Each transaction is stored in an immutable distributed ledger on each blockchain node. Criminal records are confidential and should be kept safe from hackers and intruders. Law enforcement agencies or investigative agencies can use these security recordings to analyze and detect criminal activity. Due to the lack of a global online system, Investigative agencies are having difficulty locating and researching the past of anonymous foreign criminal who is committing crimes abroad. This problem will only be solved if investigative agencies have a common global criminal database and applications to extract information. Investigation agencies, Copes, and other organizations can access global crime data using this technology on the distributed node of the blockchain in their nation. Authorities can instantly and efficiently access global criminal histories from local blockchain databases and identify the names and details of anonymous individuals in response to any foreigners suspected of engaging in unsocial activities in their country of origin. This will reduce the time and process of gathering information from the country where the suspect is located. The system would eliminate the possibility of falsification and tamper with criminal records. Key Words: Blockchain, light, Global Criminal, Criminal information

Deep Learning Based Face Detection and Identification of Criminal Suspects

Occurrence of crimes has been on the constant rise despite the emerging discoveries and advancements in the technological field in the past decade. One of the most tedious tasks is to track a suspect once a crime is committed. As most of the crimes are committed by individuals who have a history of felonies, it is essential for a monitoring system that does not just detect the person’s face who has committed the crime, but also their identity. Hence, a smart criminal detection and identification system that makes use of the OpenCV Deep Neural Network (DNN) model which employs a Single Shot Multibox Detector for detection of face and an auto-encoder model in which the encoder part is used for matching the captured facial images with the criminals has been proposed. After detection and extraction of the face in the image by face cropping, the captured face is then compared with the images in the Criminal Database. The comparison is performed by calculating the similarity value between each pair of images that are obtained by using the Cosine Similarity metric. After plotting the values in a graph to find the threshold value, we conclude that the confidence rate of the encoder model is 0.75 and above.

Implementing machine learning algorithms on criminal databases to develop a criminal activity index

Criminal activity is a major concern in today's society. Local police agencies collect and analyze vast amounts of data to prevent future crimes from taking place and protect vulnerable populations. However, despite the availability of publicly accessible data, such as the Open Justice California website, there remains a lack of efficient methods for relaying this information to the public in a digestible format. Our research aims to bridge this gap by utilizing machine learning techniques to correlate crime data with a range of explanatory factors. We first employed a clustering algorithm to normalize the data based on population. Then we tested five different predictive algorithms to determine the most effective machine learning model. Our results indicated that a neural network approach was more accurate based on our training in predicting crime rates. Additionally, we hypothesized that higher median income, lower population density, lower unemployment duration, and lower median age would be associated with lower crime rates and that these associations would be statistically significant. Our results show that median income, population, and unemployment duration all have a significant correlation with crime rates in California while median age does not.

Evaluation of loci to predict ear morphology using two SNaPshot assays.

Human ear morphology prediction with SNP-based genotypes is growing in forensic DNA phenotyping and is scarcely explored in Pakistan as a part of EVCs (externally visible characteristics). The ear morphology prediction assays with 21 SNPs were assessed for their potential utility in forensic identification of population.The SNaPshot™ multiplex chemistries, capillary electrophoresis methods and GeneMapper™ software were used for obtaining genotypic data. A total of 33 ear phenotypes were categorized with digital photographs of 300 volunteers. SHEsis software was applied to make LD plot. Ordinal and multinomial logistic regression was implemented for association testing. Multinomial logistic regression was executed to construct the prediction model in 90% training and 10% testing subjects.Several influential SNPs for ear phenotypic variation were found in association testing. The model based on genetic markers predicted ear phenotypes with moderate to good predictive accuracies demonstrated with the area under curve (AUC), sensitivity and specificity of predicted phenotypes.As an additional EVC, the estimated ear phenotypic profiles have the possibility of determining the human ear morphology differences in unknown biological samples found in crimes that do not result in a criminal database hit. Furthermore, this can help in facial reconstruction and act as an investigational lead.

How to regulate forensic familial DNA searching in Hungary?

Forensic DNA analysis has the potential to provide useful information for criminal justice even in cases where there is no match, neither between the DNA profile generated from the crime scene and the existing DNA profiles in criminal databases, nor between the DNA collected at a crime scene and potential suspects. In contrast to traditional forensic genetic testing, forensic familial DNA searching does not provide evidence, but helps to generate investigative leads and narrow down the range of potential offenders. The aim of this study is to examine, whether there is a need for special regulation of this topic in Hungary.

CRIME DETECTION SYSTEM USING FACE RECOGNITION

Real-time crime detection application using face recognition. Identication of criminal is done through thumbprint identication. However, this type of identication is constrained as most of criminal nowadays getting cleverer not to leave their thumbprint on the scene. With the advent of security technology, cameras especially CCTV have been installed in many public and private areas to provide surveillance activities. The footage of the CCTV can be used to identify suspects on scene. In this paper, an automated facial recognition system for criminal database was proposed. This system will be able to detect face and recognize face automatically. The results show that about 98% of input photo can be matched with the template data. Face recognition is one of the most challenging topics in computer vision today. It has applications ranging from security and surveillance to entertainment websites. Face recognition software are useful in banks, airports, and other institutions for screening customers. Human face is a dynamic object having high degree of variability in its appearance which makes face recognition a difcult problem in computer vision. In this eld, accuracy and speed of identication is a main issue. It is a particular form of biometric technology that describes the automatic face identication of computing systems by looking at the face. As a result, a robust system with good generalisation capability can be built by adopting cutting-edge techniques from learning, computer vision, and pattern recognition. Earlier methods treated face recognition as a standard pattern recognition problem; later methods focused more on the representation aspect after realising its uniqueness using domain knowledge; and more recent methods have been concerned with both representation and recognition. This system consists of four phases- database creation, face detection, face recognition, attendance updation. The goal of this paper is to evaluate face detection and recognition techniques and provide a complete solution for image based face detection and recognition with higher accuracy, better response rate and an initial step for video surveillance.

Contrastive Personalization Approach to Suspect Identification (Student Abstract)

Targeted image retrieval has long been a challenging problem since each person has a different perception of different features leading to inconsistency among users in describing the details of a particular image. Due to this, each user needs a system personalized according to the way they have structured the image in their mind. One important application of this task is suspect identification in forensic investigations where a witness needs to identify the suspect from an existing criminal database. Existing methods require the attributes for each image or suffer from poor latency during training and inference. We propose a new approach to tackle this problem through explicit relevance feedback by introducing a novel loss function and a corresponding scoring function. For this, we leverage contrastive learning on the user feedback to generate the next set of suggested images while improving the level of personalization with each user feedback iteration.

Establishment of criminal/profile DNA database and use of forensic intelligence to combat nationwide insecurity issues in Nigeria

Criminal activity is on the rise in Nigeria. The nefarious activity of bandits is on the increase with kidnapping of students and attack on farmers. This creates fear in the terrorized communities. Armed robbery as well as rape of citizens going about their normal duties is also on the increase. The road is becoming increasingly unsafe for the citizenry as well as government officials. The government has mandated individuals to register in the National Identification Number NIN which is linked to the Bank Verification Number (BVN) (a database established to curb crime in the banking sector) and the Subscriber Identity module (SIM). The Establishment of such databases is pertinent however the NIN, BVN, SIM-NIN linkage and fingerprints may not be sufficient in solving criminal cases without DNA profiling of convicted individuals, establishment of forensic laboratories and the creation of criminal DNA profile database CRODER – a Criminal offender DNA Exert Repertoire. The role of DNA profiling as an additional measure is to keep a record of all convicted individuals and the CRODER will be an additional useful measure in profiling criminals and individuals can be adopted as a forensic tool in addition to the captured databases of NIN, BVN and NIN-SIM and will be on the watch list of security operatives. The CRODER forensic tool can be done stepwise by availability of an emergency number to dial for emergency, a dispatch personnel to respond to the call, and vigilante groups or other adhoc security officer in the vicinity of the emergency call to get to the vicinity and preserve the crime scene environment for investigators and detectives to work on. CRODER Forensic tool can then be adopted to solve the crime. Offenders trying to escape enroute the airport, can be checked via CRODER and fingerprint compared and matched with the collection in the database. The CRODER may be a necessary stride to bring kidnappers, bandits, and armed robbers to book in record time and curb the rise in criminal activity, insurgency, banditry, and insecurity in general. If properly done, Nigeria will be a haven for citizens and would-be investors.

1991 by Franck Thilliez

Reviewed by: 1991 by Franck Thilliez Nathalie G. Cornelius Thilliez, Franck. 1991. Fleuve, 2021. ISBN 978-2-265-14428-6. Pp. 504. Rather than being another detective thriller situated during our present time, the latest installment in the Franck Sharko/Lucie Henebelle series takes the reader decades into the past. Inspector Sharko, who was initially introduced in the 2003 debut Train d'enfer pour Ange rouge, and has been aging in real time since, appears in this literary time capsule as a thirty-year-old lieutenant freshly transferred to the Paris Brigade criminelle. In his world, the policewoman at 36, quai des Orfèvres is a groundbreaking novelty. Faxes and pay-phones are basic modes of communication. DNA profiling is just starting to gain ground and computerized criminal databases are virtually nonexistent. Binders and carbon paper are the standard for record-keeping. As the newest recruit, Sharko is relegated to the tedious task of reviewing the archives of a cold case of the brutal killing of several women in the south of Paris. Slogging through massive piles of paperwork, the eager lieutenant nevertheless takes to the trying task with assiduity. But Franck's real trial by fire comes when his team must track down an elusive murderer intent on perturbing the Parisians' present. Le Méticuleux, as the criminal is nicknamed, seems able to do the inexplicable. By somehow compelling an innocent citizen to uncover a shocking photograph through an anonymous letter and a copy of Baudelaire's Les fleurs du mal, the felon leads the police to a reclusive crime scene peppered with hidden clues in a room sealed from the inside. As the case evolves, a frustrated and exhausted Franck finds it increasingly difficult to compartmentalize his emotions. Ghosts from his past resurge, shedding light on the origins of Sharko's dogged determination to become a criminal investigator. Despite the graphic violence of some scenes, Thilliez's old-school procedural is thoroughly entertaining. The fast-paced, well-written plot immerses the reader in a foreboding atmosphere where mentalism, voodoo rituals, and Houdini's escapist illusions overlap, highlighting a time when intuition and emotion guided investigations more than in today's increasingly regimented and computerized police environment. The nostalgia elicited through the cultural and historical references to the early 1990s is an appealing escape from the contemporary reader's heavily computerized environment. As intimated by the novel's palindromic title, number games, magic tricks, and word play are the order of the day, although not as well-integrated and developed as in some of Thilliez's prior novels. Particularly appealing is the insertion of a preliminary mental exercise which gains relevance later as the investigation unfolds, while also cleverly demonstrating how society influences individual thought. The mystery's solution is satisfying as well, although somewhat predictable for those familiar with Thilliez's thrillers. As an entry-point into the author's universe, 1991 is an excellent choice. For avid fans, this novel finally answers some key questions about one of the best-known popular heroes of the French thriller. [End Page 261] Nathalie G. Cornelius Bloomsburg University of Pennsylvania Copyright © 2022 American Association of Teachers of French

Cohesion index for investigate criminal organizations in criminal big databases

Background: The disarticulation of criminal organizations reduces the rates of victimization and insecurity in the population. One of the main characteristics of a criminal organization is the cohesion among its members. This investigation proposes a cohesion index that allows identifying quickly in Big databases individuals suspect to belong to criminal organizations and focus investigation resources on them. Methods: To obtain the index, we analyze the information provided by the Criminal Analysis and Investigative Focus System from the Regional Public Prosecutor’s Office in Biobío and the Investigation Police of Chile. Findings: The results show that the suspects with a higher cohesion index and a higher number of criminal cases commit crimes associated with criminal organizations. Keywords: Criminal Cohesion; Crimes Against Property; Criminal Organization; Criminal Databases

Biometric Technology 20 Years After 9/11 – Opportunities and Threats

The aim of the article is to present the development of biometric technology as a consequence of 9/11 terrorist attacks in the USA and issuing the PATRIOT ACT in 2001. Nowadays biometric technology is popular not only in the public security area (e.g. criminal data bases, face recognition surveillance systems) but is also used in everyday life (e.g. smartphones with touch ID/face recognition). The article shows both sides of biometric devices utilization: advantages and potential negative consequences for individuals.

Attitudes towards police use of consumer/private DNA databases in investigations

Consumer DNA products, such as databases that allow the public to explore familial relationships, have recently been used by police to assist in investigations. This has moved the collection of DNA used in criminal investigations away from the limitations of criminal databases and has opened up ethical concerns regarding privacy and consent. This study explored public attitudes and support towards police use of consumer DNA databases in investigations to assess whether different crime types or moral and attitude alignments influenced the level of public support of police using these consumer products. An international survey of 438 adults, using theory and scales pertaining specifically to retributive punishment and attitudes towards law, courts and police, found that moral alignment and attitudes did influence the level of public acceptability towards police usage of these techniques and that support did vary based on crime type. This research found that higher levels of public support was given for the most serious case types explored (sexual assault and homicide). Participant support for police access to private DNA databases by case type was as follows; 83.5% for sexual assault, 83.2% for homicide, 85.2% for identifying unidentified human remains, 62.8% for robbery and 58.9% for illicit drug related cases. Small to medium effects sizes were observed for these results. Although these findings provided context towards public attitudes, further research specific to international attitude differences and variance between serious crime types and public acceptability could further develop these findings.

A Decision-Making Tool for Creating and Identifying Face Sketches

A criminal can be quickly identified and prosecuted using a face sketch based on an eyewitness description . Several applications for converting hand-drawn face drawings and using them to automatically identify and recognize the suspect from the police database have been proposed in the past, but the existing system dealt with some drawbacks. It featured a lot of flaws, including as a limited facial features kit and a cartoonish feel to the constructed suspect face, which made it much more difficult to use these apps and acquire the results and efficiency that were required. In this paper, we present a stand- alone tool that allows users to create composite face sketches of suspects without the need for forensic artists. The application offers a drag-and-drop feature that can match the produced composite facial sketch with the criminal database in real time. This can be done considerably more rapidly and efficiently using deep learning and cloud infrastructure.