A platform for discovering and sharing confidential ballistic crime data.

Criminal investigations generate large volumes of complex data that detectives have to analyse and understand. This data tends to be "siloed" within individual jurisdictions and re-using it in other investigations can be difficult. Investigations into trans-national crimes are hampered by the problem of discovering relevant data held by agencies in other countries and of sharing those data. Gun-crimes are one major type of incident that showcases this: guns are easily moved across borders and used in multiple crimes but finding that a weapon was used elsewhere in Europe is difficult. In this paper we report on the Odyssey Project, an EU-funded initiative to mine, manipulate and share data about weapons and crimes. The project demonstrates the automatic combining of data from disparate repositories for cross-correlation and automated analysis. The data arrive from different cultural/domains with multiple reference models using real-time data feeds and historical databases

Solution Development to Prevent Crime Rate

Crime is one of the major problems encountered in a society. Thus, there is an urgent need for security agents and agencies to battle and eradicate crime. Preventive are taken to reduce the increasing number of cases of crime. A huge amount of data set is generated every year on the basis of reporting of crime. This data can prove very useful in analysing and predicting crime and help us prevent the crime to some extent. Crime analysis is an area of vital importance in police department. Study of crime data can help us analyse crime pattern, inter-related clues& important hidden relations between the crimes. That is why data mining can be great aid to analyse, visualize and predict crime using crime data set. We analyse data objects using machine learning techniques. Dataset is classified on the basis of tree based algorithm. In this prediction is done using random forest algoritm according to various types of crimes taking place in different states and cities. Crime mapping will help the administration to plan strategies for prevention of crime, further using Random forest algorithm technique data can be predicted and visualized in various form in order using leaflet and shiny package to provide better understanding of crime patterns

A comparative analysis of selected clustering algorithms for criminal profiling

Several criminal profiling systems have been developed to assist the Law Enforcement Agencies in solving crimes but the techniques employed in most of the systems lack the ability to cluster criminal based on their behavioral characteristics. This paper reviewed different clustering techniques used in criminal profiling and then selects one fuzzy clustering algorithm (Expectation Maximization) and two hard clustering algorithm (K-means and Hierarchical). The selected algorithms were then developed and tested on real life data to produce "profiles" of criminal activity and behavior of criminals. The algorithms were implemented using WEKA software package. The performance of the algorithms was evaluated using cluster accuracy and time complexity. The results show that Expectation Maximization algorithm gave a 90.5% clusters accuracy in 8.5s, while K-Means had 62.6% in 0.09s and Hierarchical with 51.9% in 0.11s. In conclusion, soft clustering algorithm performs better than hard clustering algorithm in analyzing criminal data. Keywords: Clustering Algorithm, Profiling, Crime, Membership valu

Influencing operational policing strategy by predictive service analytics

Everyday there are growing pressures to ensure that services are delivered efficiently, with high levels of quality and with acceptability of regulatory standards. For the Police Force, their service requirement is to the public, with the police officer presence being the most visible product of this criminal justice provision. Using historical data from over 10 years of operation, this research demonstrates the benefits of using data mining methods for knowledge discovery in regards to the crime and incident related elements which impact on the Police Force service provision. In the UK, a Force operates over a designated region (macro-level), which is further subdivided into Beats (micro-level). This research also demonstrates differences between the outputs of micro-level and macro-level analytics, where the lower level analysis enables adaptation of the operational Policing strategy. The evidence base provided through the analysis supports decisions regarding further investigations into the capability of flexible neighbourhood policing practices; alongside wider operations i.e. optimal officer training times

LEGAL ANALYSIS OF SEXTORTION CRIME IN THE COMPERATIVE LAW AND TURKISH LAW

Due to technological developments, cybercrime techniques evolve day by day. Nowadays, innocent users have been the target of cybercriminals who want to make money or extort sexual favor in the context of sextortion crime. This paper discusses the definition of sextortion with the techniques used by the criminals, legal framework of aforementioned crime in Turkey and discusses how to prevent and solve past crimes

IT-induced cognitive biases in intelligence analysis: big data analytics and serious games

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