Relevant bibliographies by topics / Criminal investigation Data processing

Academic literature on the topic 'Criminal investigation Data processing'

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Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Criminal investigation Data processing"

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Lukić, Tatjana. "Automatic computer based data processing as a special investigation activity." Glasnik Advokatske komore Vojvodine 78, no. 9 (2006): 602–15. http://dx.doi.org/10.5937/gakv0611602l.

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The application of special investigation activities is characteristic for proactive investigations related to the organized crime. One of these special investigation activities, that became more and more important, is a computer based automatic data processing which was introduced in Serbia by the new Law on Criminal Procedure. The subject matter of this paper is legal solution in Serbia related to this special investigation activity. Apart from that, the author demonstrated its comparative regulation by analyzing legal basis for its application, terms and means of its approval, duration, use of computer excerpts as evidence in the criminal procedure and supervision over its legality. The author paid special attention to the personal data processing on the international level and issue of criminal investigation analytics in combating terrorism.
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Pang, Xinzhao. "On the Protection of Personal Data Information in Big Data Investigation Activities." Journal of Social Science Studies 8, no. 2 (December 30, 2021): 160. http://dx.doi.org/10.5296/jsss.v8i2.19421.

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In the context of the vigorous development of big data and network communication technologies, the universality of personal data information processing, the openness of concept definitions, and the potential risks in practice have led to theoretical and practical changes in the definition of personal data information. With the widespread use of big data technology in criminal investigations, the theoretical and practical activities of big data investigation have gradually formed. Big data investigation activities are often accompanied by infringements on citizens' personal data and other legitimate rights and interests. At present, the traditional model of personal data information protection cannot restrict the code of conduct in big data investigation activities. For this reason, it is necessary to introduce a comprehensive governance model, which mainly includes relative control of individuals, balance of multiple interests and dynamic risk adjustment. Etc., and focus on the transformation of the legal protection model of personal information.
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Dehtiarova, Olha. "Ensuring information security in criminal proceedings." Law Review of Kyiv University of Law, no. 2 (August 10, 2020): 401–4. http://dx.doi.org/10.36695/2219-5521.2.2020.78.

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The scientific article considers the issue of information protection during the investigation of criminal proceedings, informationsecurity. The position of researchers and practitioners on information security at the stage of pre-trial investigation of criminal procee -dings is studied.The provisions of the Law of Ukraine «On Information», the Strategy for the Development of the System of the Ministry of InternalAffairs of Ukraine until 2020, the Regulations on the Procedure for Maintaining the Unified Register of Pre-trial Investigations toEnsure Information Security in Proceedings are analyzed.The introduction of information technology in criminal procedure has become an urgent issue, and their application has necessitatedthe need to address the issue of information security in criminal proceedings. When investigating proceedings, the investigatorsuse databases and enter into these databases information that must be securely protected. Information in criminal proceedings needsspecial protection, as it is subject to encroachment by interested parties on its disclosure and transmission.Ensuring information security is to create appropriate conditions for the storage, processing and exchange of information that inany way relates to the investigation of criminal proceedings. Interference in the activities of pre-trial investigation bodies through informationsystems is an undermining of the principle of independence of the law enforcement system. It is important not only to combatunauthorized interference, but also to increase the degree of responsibility for such actions. Because all data collected in criminal proceedingsare protected by law and are a secret of the investigation.Information security in criminal proceedings is the protection of the information environment of electronic criminal proceedingswith the help of means and methods of information storage, which ensures the proper functioning of criminal proceedings and facilitatesthe implementation of its tasks.
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Han, Mee Lan, Byung Il Kwak, and Huy Kang Kim. "CBR-Based Decision Support Methodology for Cybercrime Investigation: Focused on the Data-Driven Website Defacement Analysis." Security and Communication Networks 2019 (December 20, 2019): 1–21. http://dx.doi.org/10.1155/2019/1901548.

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Criminal profiling is a useful technique to identify the most plausible suspects based on the evidence discovered at the crime scene. Similar to offline criminal profiling, in-depth profiling for cybercrime investigation is useful in analysing cyberattacks and for speculating on the identities of the criminals. Every cybercrime committed by the same hacker or hacking group has unique traits such as attack purpose, attack methods, and target. These unique traits are revealed in the evidence of cybercrime; in some cases, these unique traits are well hidden in the evidence such that it cannot be easily perceived. Therefore, a complete analysis of several factors concerning cybercrime can provide an investigator with concrete evidence to attribute the attacks and narrow down the scope of the criminal data and grasp the criminals in the end. We herein propose a decision support methodology based on the case-based reasoning (CBR) for cybercrime investigation. This study focuses on the massive data-driven analysis of website defacement. Our primary aim in this study is to demonstrate the practicality of the proposed methodology as a proof of concept. The assessment of website defacement was performed through the similarity measure and the clustering processing in the reasoning engine based on the CBR. Our results show that the proposed methodology that focuses on the investigation enables a better understanding and interpretation of website defacement and assists in inferring the hacker’s behavioural traits from the available evidence concerning website defacement. The results of the case studies demonstrate that our proposed methodology is beneficial for understanding the behaviour and motivation of the hacker and that our proposed data-driven analytic methodology can be utilized as a decision support system for cybercrime investigation.
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Kāršenieks, Jānis. "INFORMATION PROCESSING ON CRIMINAL CONVICTIONS OF A PERSON FOR INVESTIGATIVE PURPOSES." Administrative and Criminal Justice 2, no. 87 (June 30, 2019): 43. http://dx.doi.org/10.17770/acj.v2i87.4299.

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In the paper, the author analyzes the personal data protection problems of the individuals for investigative purposes in the context of operational actions. In order to understand the essence of the problem, the author of the paper, using legislation and judicial practice, analyzes the essence of the personal data (data relating to criminal offenses, criminal convictions) protection rights to of individuals, the procedure for conducting criminal procedure and operational actions and the necessary amount personal data information.The scientific basis of the research is the normative acts regulating both subjects of research, and judicial practice.The paper addresses the issues, which that have not previously been investigated. The research specifies the criteria, rules and principles, which have to be considered and applied in practice when processing information on individuals’ criminal record for investigative purposes in a operational actions’ context.The aim of the paper is to investigate the guidelines for the protection of natural persons in criminal proceedings while processing information on criminal convictions. The tasks of the investigation are as follows: to analyze the prerequisites for the personal data lawfulness’s processing relating to criminal convictions in the framework of criminal proceedings and operational activities; to identify the cases, in which the criminal prosecutors are entitled to obtain information on a person’s criminal record. The following research methods have been used in the paper: analytical, comparative, inductive, deductive and logical methods.
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Carnaz, Gonçalo, Mário Antunes, and Vitor Beires Nogueira. "An Annotated Corpus of Crime-Related Portuguese Documents for NLP and Machine Learning Processing." Data 6, no. 7 (June 26, 2021): 71. http://dx.doi.org/10.3390/data6070071.

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Criminal investigations collect and analyze the facts related to a crime, from which the investigators can deduce evidence to be used in court. It is a multidisciplinary and applied science, which includes interviews, interrogations, evidence collection, preservation of the chain of custody, and other methods and techniques of investigation. These techniques produce both digital and paper documents that have to be carefully analyzed to identify correlations and interactions among suspects, places, license plates, and other entities that are mentioned in the investigation. The computerized processing of these documents is a helping hand to the criminal investigation, as it allows the automatic identification of entities and their relations, being some of which difficult to identify manually. There exists a wide set of dedicated tools, but they have a major limitation: they are unable to process criminal reports in the Portuguese language, as an annotated corpus for that purpose does not exist. This paper presents an annotated corpus, composed of a collection of anonymized crime-related documents, which were extracted from official and open sources. The dataset was produced as the result of an exploratory initiative to collect crime-related data from websites and conditioned-access police reports. The dataset was evaluated and a mean precision of 0.808, recall of 0.722, and F1-score of 0.733 were obtained with the classification of the annotated named-entities present in the crime-related documents. This corpus can be employed to benchmark Machine Learning (ML) and Natural Language Processing (NLP) methods and tools to detect and correlate entities in the documents. Some examples are sentence detection, named-entity recognition, and identification of terms related to the criminal domain.
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Korostelova, L. A. "DATA CLEANING AS ONE OF THE METHODS OF DATA PROCESSING FOR CRIMINAL INVESTIGATIONS." Juridical scientific and electronic journal, no. 5 (2022): 568–70. http://dx.doi.org/10.32782/2524-0374/2022-5/136.

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Tymchyshyn, Andriy, Anna Semeniaka, Serhii Bondar, Nataliia Akhtyrska, and Olena Kostiuchenko. "The use of big data and data mining in the investigation of criminal offences." Revista Amazonia Investiga 11, no. 56 (October 18, 2022): 278–90. http://dx.doi.org/10.34069/ai/2022.56.08.27.

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The aim of this study was to determine the features and prospects of using Big Data and Data Mining in criminal proceedings. The research involved the methods of a systematic approach, descriptive analysis, systematic sampling, formal legal approach and forecasting. The object of using Big Data and Data Mining are various crimes, the common features of which are the seriousness and complexity of the investigation. The common tools of Big Data and Data Mining in crime investigation and crime forecasting as interrelated tasks were identified. The creation of databases is the result of the processing of data sources by Data Mining methods, each being distinguished by the specifics of use. The main risks of implementing Big Data and Data Mining are violations of human rights and freedoms. Improving the use of Big Data and Data Mining requires standardization of procedures with strict adherence to the fundamental ethical, organizational and procedural rules. The use of Big Data and Data Mining is a forensic innovation in the investigation of serious crimes and the creation of an evidence base for criminal justice. The prospects for widespread use of these methods involve the standardization of procedures based on ethical, organizational and procedural principles. It is appropriate to outline these procedures in framework practical recommendations, emphasizing the responsibility of officials in case of violation of the specified principles. The area of further research is the improvement of innovative technologies and legal regulation of their application.
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Bozhyk, Valerii I., Yan V. Streliuk, Vitaliy A. Maziychuk, Anatoliy O. Voightko, Myroslava V. Kokoshko, and Anatoliy M. Kisliy. "Problems of implementing international digitalisation standards of criminal investigation." Cuestiones Políticas 39, no. 71 (December 25, 2021): 317–33. http://dx.doi.org/10.46398/cuestpol.3971.16.

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The study consisted of identifying the existing problems in the implementation of international standards of digitization of criminal investigation at the legislative level. The research was carried out in stages as a summary, based on the logic of presentation of the material, to achieve and meet the objectives set out in the article. The method of direct observation, the method of comparison and analysis of the content of the documents, the method of systemic and pragmatic approach were used. The key results of the study were the analysis of the experience of implementing digital standards in forensic activities in the United States, Canada, Great Britain, Denmark, England, Austria, Estonia, and Ukraine. It is concluded that the problems that exist in the implementation of these standards, were identified from the criteria of evaluation of the efficiency and capacity of digital data processing by the agencies involved in the criminal investigation. In addition, the problems and difficulties faced by the authorities in implementing existing international digitization standards, indicate the need for comprehensive measures to organize criminal investigations. To overcome them, appropriate measures must be taken in the field of legislative changes.
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Funta, Rastislav, and Peter Ondria. "Data Protection in Law Enforcement and Judicial Cooperation in Criminal Matters." TalTech Journal of European Studies 11, no. 2 (September 1, 2021): 148–66. http://dx.doi.org/10.2478/bjes-2021-0019.

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Abstract The redesign of data protection in the police and judicial area is intended to create uniformity at the European level for the citizens of EU Member States. This scientific article analyses the subject of data protection in law enforcement and judicial cooperation in criminal matters. The focus is primarily on the existing provisions and the latest developments of the EU with regard to Directive (EU) 2016/680 on the protection of natural persons with regard to the processing of personal data by competent authorities for the purposes of the prevention, investigation, detection or prosecution of criminal offences or the execution of criminal penalties, and on the free movement of such data, and repealing Council Framework Decision 2008/977/JHA. The international level with regard to data protection in the police and judicial area and possible changes due to the developments in data protection under European law are also examined in more detail.
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Dissertations / Theses on the topic "Criminal investigation Data processing"

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Carnaz, Gonçalo José Freitas. "A graph-based framework for data retrieved from criminal-related documents." Doctoral thesis, Universidade de Évora, 2021. http://hdl.handle.net/10174/29954.

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A digitalização das empresas e dos serviços tem potenciado o tratamento e análise de um crescente volume de dados provenientes de fontes heterogeneas, com desafios emergentes, nomeadamente ao nível da representação do conhecimento. Também os Órgãos de Polícia Criminal (OPC) enfrentam o mesmo desafio, tendo em conta o volume de dados não estruturados, provenientes de relatórios policiais, sendo analisados manualmente pelo investigadores criminais, consumindo tempo e recursos. Assim, a necessidade de extrair e representar os dados não estruturados existentes em documentos relacionados com o crime, de uma forma automática, permitindo a redução da análise manual efetuada pelos investigadores criminais. Apresenta-se como um desafio para a ciência dos computadores, dando a possibilidade de propor uma alternativa computacional que permita extrair e representar os dados, adaptando ou propondo métodos computacionais novos. Actualmente existem vários métodos computacionais aplicados ao domínio criminal, nomeadamente a identificação e classificação de entidades nomeadas, por exemplo narcóticos, ou a extracção de relações entre entidades relevantes para a investigação criminal. Estes métodos são maioritariamente aplicadas à lingua inglesa, e em Portugal não há muita atenção à investigação nesta área, inviabilizando a sua aplicação no contexto da investigação criminal. Esta tese propõe uma solução integrada para a representação dos dados não estruturados existentes em documentos, usando um conjunto de métodos computacionais: Preprocessamento de Documentos, que agrupa uma tarefa de Extracção, Transformação e Carregamento adaptado aos documentos relacionados com o crime, seguido por um pipeline de Processamento de Linguagem Natural aplicado à lingua portuguesa, para uma análise sintática e semântica dos dados textuais; Método de Extracção de Informação 5W1H que agrupa métodos de Reconhecimento de Entidades Nomeadas, a detecção da função semântica e a extracção de termos criminais; Preenchimento da Base de Dados de Grafos e Enriquecimento, permitindo a representação dos dados obtidos numa base de dados de grafos Neo4j. Globalmente a solução integrada apresenta resultados promissores, cujos resultados foram validados usando protótipos desemvolvidos para o efeito. Demonstrou-se ainda a viabilidade da extracção dos dados não estruturados, a sua interpretação sintática e semântica, bem como a representação na base de dados de grafos; Abstract: The digitalization of companies processes has enhanced the treatment and analysis of a growing volume of data from heterogeneous sources, with emerging challenges, namely those related to knowledge representation. The Criminal Police has similar challenges, considering the amount of unstructured data from police reports manually analyzed by criminal investigators, with the corresponding time and resources. There is a need to automatically extract and represent the unstructured data existing in criminal-related documents and reduce the manual analysis by criminal investigators. Computer science faces a challenge to apply emergent computational models that can be an alternative to extract and represent the data using new or existing methods. A broad set of computational methods have been applied to the criminal domain, such as the identification and classification named-entities (NEs) or extraction of relations between the entities that are relevant for the criminal investigation, like narcotics. However, these methods have mainly been used in the English language. In Portugal, the research on this domain, applying computational methods, lacks related works, making its application in criminal investigation unfeasible. This thesis proposes an integrated solution for the representation of unstructured data retrieved from documents, using a set of computational methods, such as Preprocessing Criminal-Related Documents module. This module is supported by Extraction, Transformation, and Loading tasks. Followed by a Natural Language Processing pipeline applied to the Portuguese language, for syntactic and semantic analysis of textual data. Next, the 5W1H Information Extraction Method combines the Named-Entity Recognition, Semantic Role Labelling, and Criminal Terms Extraction tasks. Finally, the Graph Database Population and Enrichment allows us the representation of data retrieved into a Neo4j graph database. Globally, the framework presents promising results that were validated using prototypes developed for this purpose. In addition, the feasibility of extracting unstructured data, its syntactic and semantic interpretation, and the graph database representation has also been demonstrated.
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Yalcinkaya, Ramazan. "Police officers' adoption of information technology: A case study of the Turkish POLNET system." Thesis, University of North Texas, 2007. https://digital.library.unt.edu/ark:/67531/metadc3900/.

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One of the important branches of government and vital to the community, police agencies are organizations that have high usage rates of information technology systems since they are in the intelligence sector and thus have information incentives. Not only can information technologies develop intra- and inter-relationships of law enforcement agencies, but they also improve the efficiency and effectiveness of the police officers and agencies without adding additional costs. Thus, identifying the factors that influence the police officers' adoption of information technology can help predict and determine how information technology will contribute to the social organization of policing in terms of effectiveness and efficiency gains. A research framework was developed by integrating three different models, theory of planned behavior (TPB), technology acceptance theory (TAM), and diffusion of innovation theory (DOI) while adding two other factors, facility and voluntariness, to better determine the factors affecting the implementation and adoption of the POLNET software system used by the Turkish National Police (TNP). The integrated model used in this study covers not only basic technology acceptance factors, but also the factors related to policing. It also attempts to account for the factors of cultural differences by considering the important aspects of Turkish culture. A cross sectional survey was conducted among TNP officers using the POLNET system. The LISREL 8.5® analysis for the hypothesized model resulted in a good model fit; 13 of the 15 hypotheses were supported.
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Hargreaves, C. J. "Assessing the Reliability of Digital Evidence from Live Investigations Involving Encryption." Thesis, Department of Informatics and Sensors, 2009. http://hdl.handle.net/1826/4007.

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The traditional approach to a digital investigation when a computer system is encountered in a running state is to remove the power, image the machine using a write blocker and then analyse the acquired image. This has the advantage of preserving the contents of the computer’s hard disk at that point in time. However, the disadvantage of this approach is that the preservation of the disk is at the expense of volatile data such as that stored in memory, which does not remain once the power is disconnected. There are an increasing number of situations where this traditional approach of ‘pulling the plug’ is not ideal since volatile data is relevant to the investigation; one of these situations is when the machine under investigation is using encryption. If encrypted data is encountered on a live machine, a live investigation can be performed to preserve this evidence in a form that can be later analysed. However, there are a number of difficulties with using evidence obtained from live investigations that may cause the reliability of such evidence to be questioned. This research investigates whether digital evidence obtained from live investigations involving encryption can be considered to be reliable. To determine this, a means of assessing reliability is established, which involves evaluating digital evidence against a set of criteria; evidence should be authentic, accurate and complete. This research considers how traditional digital investigations satisfy these requirements and then determines the extent to which evidence from live investigations involving encryption can satisfy the same criteria. This research concludes that it is possible for live digital evidence to be considered to be reliable, but that reliability of digital evidence ultimately depends on the specific investigation and the importance of the decision being made. However, the research provides structured criteria that allow the reliability of digital evidence to be assessed, demonstrates the use of these criteria in the context of live digital investigations involving encryption, and shows the extent to which each can currently be met.
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Hargreaves, Christopher James. "Assessing the reliability of digital evidence from live investigations involving encryption." Thesis, Cranfield University, 2009. http://dspace.lib.cranfield.ac.uk/handle/1826/4007.

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The traditional approach to a digital investigation when a computer system is encountered in a running state is to remove the power, image the machine using a write blocker and then analyse the acquired image. This has the advantage of preserving the contents of the computer’s hard disk at that point in time. However, the disadvantage of this approach is that the preservation of the disk is at the expense of volatile data such as that stored in memory, which does not remain once the power is disconnected. There are an increasing number of situations where this traditional approach of ‘pulling the plug’ is not ideal since volatile data is relevant to the investigation; one of these situations is when the machine under investigation is using encryption. If encrypted data is encountered on a live machine, a live investigation can be performed to preserve this evidence in a form that can be later analysed. However, there are a number of difficulties with using evidence obtained from live investigations that may cause the reliability of such evidence to be questioned. This research investigates whether digital evidence obtained from live investigations involving encryption can be considered to be reliable. To determine this, a means of assessing reliability is established, which involves evaluating digital evidence against a set of criteria; evidence should be authentic, accurate and complete. This research considers how traditional digital investigations satisfy these requirements and then determines the extent to which evidence from live investigations involving encryption can satisfy the same criteria. This research concludes that it is possible for live digital evidence to be considered to be reliable, but that reliability of digital evidence ultimately depends on the specific investigation and the importance of the decision being made. However, the research provides structured criteria that allow the reliability of digital evidence to be assessed, demonstrates the use of these criteria in the context of live digital investigations involving encryption, and shows the extent to which each can currently be met.
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Ask, Karl. "Criminal investigation : motivation, emotion and cognition in the processing of evidence /." Göteborg : Dept. of Psychology Göteborg Univ, 2006. http://www.gbv.de/dms/spk/sbb/recht/toc/513716297.pdf.

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Padhye, Manoday D. "Use of data mining for investigation of crime patterns." Morgantown, W. Va. : [West Virginia University Libraries], 2006. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=4836.

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Thesis (M.S.)--West Virginia University, 2006.
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Brouse, Andrew. "The interharmonium : an investigation into networked musical applications and brainwaves." Thesis, McGill University, 2001. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=33878.

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This work surveys currently available methods for measuring human brainwaves in order to generate music and technologies for real-time transmission of audio and music over the Internet. The end goal is to produce a performable music system which sends live human brainwaves over the Internet to produce sounding music at another, physically separated location.
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Slingsby, T. P. "An investigation into the development of a facilities management system for the University of Cape Town." Master's thesis, University of Cape Town, 2004. http://hdl.handle.net/11427/5585.

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Todd, Peter A. "An experimental investigation of the impact of computer based decision aids on the process of preferential choice." Thesis, University of British Columbia, 1988. http://hdl.handle.net/2429/29442.

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This research examines the impact of Decision Support Systems (DSS) on the decision making process for preferential choice tasks. The potential impact of DSS on the decision process is evaluated in terms of how the system alters the decision maker's cognitive load. Competing hypotheses are developed based on the possible objectives of the decision maker with respect to decision effort and decision quality. One line of reasoning assumes that the DSS will be used in such a way as to maximise decision quality. The other asserts that the use of the DSS will be geared towards effort conservation. These hypotheses about the impact of the DSS on the decision process are tested in three experiments. The three studies employed concurrent verbal protocols to capture data about the decision process. In experiment 1 subjects were placed in either and aided or unaided decision setting and given problems of either five or ten alternatives from which to make a choice. The results showed that decision strategy changed as a results of the use of the decision aid. In general, subjects behaved as effort minimisers. There were no significant effects related to the amount of information processing. Experiment 2 was similar to experiment 1 except that subjects were given problems with either ten or twenty alternatives. The results were consistent with, though stronger than those of experiment 1. Almost all aided group subjects used Elimination by aspects strategy while the unaided group used a Conjunctive strategy. This is consistent with the notion of effort minimisation. There were no significant differences in the amount of information processing Experiment 3 was designed to test whether the results in experiments 1 and 2 were a due to the tendency of decision makers to minimise effort or because the aid was not powerful enough to induce additive processing. In this study the DSS was altered to both increase the support for the additive difference strategy and reduce support for the elimination by aspects approach. The results of experiment 3 show that decision makers tend to adapt their strategy to the type of decision aids available. There is evidence that if additive strategies are made sufficiently less effortful to use they will be employed. Similarly, when the degree of effort to follow a particular elimination strategy is manipulated decision makers tend to adapt in such a way as to minimise effort. Overall the results of the three experiments are consistent in demonstrating the adaptivity of decision makers to the types of support tools available to them. This adaptivity centres around the minimisation of decision effort. It appears that decision makers are highly conscious of the effort required to make decisions and work in such a way as to minimise that expenditure. When faced with the use a decision aid they appear to calibrate their own decision effort to that provided by the decision aid. There is some evidence that sufficient changes in the relative effort required to use various strategies can lead decision makers to follow more effortful approaches than they might otherwise consider. The precise nature of this effort-accuracy relationship needs to be studied more closely. The basic contribution of the dissertation has been to provide a formal approach for the study of DSS, based on concepts drawn from behavioural decision theory and information processing psychology. This work also has implications for behavioural decision theorists, consumer researchers and practical implications for the development of DSS in preferential choice settings.
Business, Sauder School of
Graduate
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Olson, Chandra. "Jini an investigation in distributed computing /." [Florida] : State University System of Florida, 2001. http://etd.fcla.edu/etd/uf/2001/ank7122/chandra.PDF.

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Thesis (M.E.)--University of Florida, 2001.
Title from first page of PDF file. Document formatted into pages; contains viii, 71 p.; also contains graphics. Vita. Includes bibliographical references (p. 69-70).
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Books on the topic "Criminal investigation Data processing"

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Ishchenko, E. P. Algoritmizat︠s︡ii︠a︡ sledstvennoĭ dei︠a︡telʹnosti: Monografii︠a︡. Moskva: I︠U︡rlitinform, 2010.

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al-Dalīl al-raqmī wa-maʻāyīr jūdatuhu fī al-ithbāt al-jināʼī. ʻAmmān: Markaz al-Kitāb al-Akādīmī, 2014.

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Keppel, Robert D. Improving the investigation of violent crime: The Homicide Investigation and Tracking System. [Washington, D.C.]: U.S. Dept. of Justice, Office of Justice Programs, National Institute of Justice, 1993.

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G, Weis Joseph, and National Institute of Justice (U.S.), eds. Improving the investigation of violent crime: The Homicide Investigation and Tracking System. [Washington, D.C.]: U.S. Dept. of Justice, Office of Justice Programs, National Institute of Justice, 1993.

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Khrustalev, V. N. Problemy ispolʹzovanii︠a︡ avtomatizirovannykh sistem v ėkspertno-kriminalisticheskoĭ praktike: Materialy nauchno-prakticheskoĭ konferent︠s︡ii. Saratov: Saratovskiĭ i︠u︡rid. in-t, 2000.

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Ishchenko, P. P. Informat︠s︡ionnoe obespechenie sledstvennoĭ dei︠a︡telʹnosti: Nauchno-prakticheskoe posobie. Moskva: I︠U︡rlitinform, 2011.

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Belov, O. A. Informat︠s︡ionnoe obespechenie rassledovanii︠a︡ prestupleniĭ, sovershaemykh v ispravitelʹnykh uchrezhdenii︠a︡kh: Uchebnoe posobie. Moskva: Izdatelʹstvo "I︠U︡rlitinform", 2012.

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Vodi︠a︡nova, N. B. Osnovy planirovanii︠a︡ i programmirovanii︠a︡ sledstvennoĭ dei︠a︡telʹnosti: Monografii︠a︡. Moskva: I︠U︡rlitinform, 2010.

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Informationelle Selbstbestimmung und strafrechtliche Ermittlung: Zum verfassungskonformen Technikeinsatz im Strafverfahren. Pfaffenweiler: Centaurus-Verlagsgesellschaft, 1990.

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Schumacher, Joachim. Verwertbarkeit rechtswidrig erhobener Daten im Polizeirecht. Aachen: Shaker, 2001.

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Book chapters on the topic "Criminal investigation Data processing"

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Mann, Greg. "Data Management Techniques for Criminal Investigations." In Advanced Information and Knowledge Processing, 81–94. London: Springer London, 2011. http://dx.doi.org/10.1007/978-1-4471-2140-4_6.

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Gutiérrez Zarza, Ángeles. "Processing and Protection of Personal Data in National Investigations and Criminal Proceedings." In Exchange of Information and Data Protection in Cross-border Criminal Proceedings in Europe, 211–17. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-40291-3_17.

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Mcnary, Sarah, and Aaron Hunter. "Wearable Device Data for Criminal Investigation." In Security, Privacy, and Anonymity in Computation, Communication, and Storage, 60–71. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-05345-1_5.

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Lasagni, Giulia. "Real-Time Monitoring of Banking Data: State of Play." In Banking Supervision and Criminal Investigation, 285–325. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12161-7_7.

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Lasagni, Giulia. "Introducing a Regulation on (Banking) Data Surveillance in the EU: Some Proposals." In Banking Supervision and Criminal Investigation, 327–57. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12161-7_8.

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Vervaele, John A. E. "Surveillance and Criminal Investigation: Blurring of Thresholds and Boundaries in the Criminal Justice System?" In Reloading Data Protection, 115–28. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-7540-4_7.

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Jourdain, G. "Advanced Methods for the Investigation of the Underwater Channel." In Underwater Acoustic Data Processing, 69–85. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-009-2289-1_6.

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Guo, Shaotong, Longbiao Wang, Sheng Li, Ju Zhang, Cheng Gong, Yuguang Wang, Jianwu Dang, and Kiyoshi Honda. "Investigation of Effectively Synthesizing Code-Switched Speech Using Highly Imbalanced Mix-Lingual Data." In Neural Information Processing, 36–47. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63830-6_4.

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Amalvict, Martine, Jacques Hinderer, Jean-Paul Boy, Pascal Gegout, Muriel Llubes, and Nicolas Florsch. "Methodological Investigation of the Processing of Absolute Gravity Data." In Gravity, Geoid and Geodynamics 2000, 179–83. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04827-6_30.

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Gutiérrez Zarza, Ángeles. "The European Investigation Order Draft Directive." In Exchange of Information and Data Protection in Cross-border Criminal Proceedings in Europe, 207–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-40291-3_15.

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Conference papers on the topic "Criminal investigation Data processing"

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Santos, Rafael, Fábio Nunes, Manoela Oliveira, and Methanias Júnior. "Um Survey sobre a utilização de técnicas de Data Mining e Data Analytics por agências de investigação criminal do Brasil." In XIII Simpósio Brasileiro de Sistemas de Informação. Sociedade Brasileira de Computação, 2017. http://dx.doi.org/10.5753/sbsi.2017.6092.

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Abstract:
Em investigações criminais complexas, os envolvidos lidam com uma quantidade enorme e complexa de dados que necessitam de recursos computacionais especializados na extração de informações e correlações relevantes para o processo investigativo. Neste cenário, é necessário que haja apoio computacional, desde a etapa de armazenamento e integração entre diferentes bases de dados, até a etapa de análise estatística e descoberta de padrões. Este artigo discute os resultados de um Survey aplicado aos principais órgãos de combate ao crime organizado, tais como as agências de Inteligência de Segurança Pública – ISP, os Laboratórios de Tecnologia de Combate à Lavagem de Dinheiro – LABLDs e os Grupos de Atuação Especial de Repressão ao Crime Organizado – GAECO. O objetivo principal foi o de conhecer o cenário atual da utilização de ferramentas de análise de dados nessas agências, projetando as necessidades de pesquisa e investimentos nesta área. Entre os resultados encontrados, observou-se que 40% dos pesquisados não conhecem e 15% não utilizam soluções de ETL (Extract, Transform and Load), apesar de todos (100%) declararem possuir pelo menos uma ferramenta de Data Mining no seu local de trabalho, bem como também declararem (100%) possuir pelo menos uma ferramenta de OLAP/BI (Online Analytical Processing/Business Intelligence). Por fim e com proeminente destaque, apenas 2,77% dos pesquisados utilizam diretamente algum algoritmo de Mineração de Dados para extração de conhecimento. Este cenário evidencia, inicialmente, que a maior parte dos órgãos especializados em investigação do Brasil ainda não aplica efetivamente as técnicas de Data Mining e de Data Analytics em suas atividades.
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Khan, Saiqa, Firoz Ansari, Hamza Azmi Dhalvelkar, and Sabiqua Computer. "Criminal investigation using Call Data Records (CDR) through Big Data technology." In 2017 International Conference on Nascent Technologies in Engineering (ICNTE). IEEE, 2017. http://dx.doi.org/10.1109/icnte.2017.7947942.

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Shi, Weiyi. "The Application of Image Processing in the Criminal Investigation." In 2016 4th International Conference on Machinery, Materials and Information Technology Applications. Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/icmmita-16.2016.28.

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McNary, Sarah, and Aaron Hunter. "Using Wearable Device Data in a Criminal Investigation: A Preliminary Study." In 2018 European Intelligence and Security Informatics Conference (EISIC). IEEE, 2018. http://dx.doi.org/10.1109/eisic.2018.00023.

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Johnsen, Jan William, and Katrin Franke. "The impact of preprocessing in natural language for open source intelligence and criminal investigation." In 2019 IEEE International Conference on Big Data (Big Data). IEEE, 2019. http://dx.doi.org/10.1109/bigdata47090.2019.9006006.

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Wadhwa, Mridul, Tushar Jha, Bishal Kumar Prasad, Abhishek Bajaj, Lakshya Nagpal, and Deepa Bura. "A Hybrid approach on Tracking Criminal Investigation and Suspect Prediction." In 2022 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COM-IT-CON). IEEE, 2022. http://dx.doi.org/10.1109/com-it-con54601.2022.9850763.

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Khan, Er Saiqa, Hamza Azmi, Firoz Ansari, and Sabiqua Dhalvelkar. "Simple Implementation of Criminal Investigation using Call Data Records (CDRs) through Big Data Technology." In 2018 International Conference on Smart City and Emerging Technology (ICSCET). IEEE, 2018. http://dx.doi.org/10.1109/icscet.2018.8537389.

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Liao, Mancheng. "Establishing a Knowledge Base of an Expert System for Criminal Investigation." In 2022 3rd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE). IEEE, 2022. http://dx.doi.org/10.1109/icbaie56435.2022.9985927.

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Liu, Benyong, Jing Zhang, and Xiang Liao. "Projection Kernel Regression for Image Registration and Fusion in Video-Based Criminal Investigation." In 2011 International Conference on Multimedia and Signal Processing (CMSP). IEEE, 2011. http://dx.doi.org/10.1109/cmsp.2011.77.

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Iqbal, Asif, Mathias Ekstedt, and Hanan Alobaidli. "Exploratory studies into forensic logs for criminal investigation using case studies in industrial control systems in the power sector." In 2017 IEEE International Conference on Big Data (Big Data). IEEE, 2017. http://dx.doi.org/10.1109/bigdata.2017.8258360.

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