http://www.security-informatics.com The latest research articles published by Security Informatics 2013-05-01T00:00:00Z Criminal network investigation involves a number of complex tasks and problems. Overall tasks include collection, processing, and analysis of information, in which analysis is the key to successful use of information since it transforms raw data into intelligence. Analysts have to deal with problems such as information volume and complexity which are typically resolved with more resources. This approach together with sequential thinking introduces compartmentalization, inhibits information sharing, and ultimately results in intelligence failure. We view analysis as an iterative and incremental process of creative synthesis and logic-based sense-making where all stakeholders participate and contribute. This paper presents a novel tool that supports a human-centered, target-centric model for criminal network investigation. The developed tool provides more comprehensive support for analysis tasks than existing tools and measures of performance indicate that the integration of synthesis and sense-making is feasible. http://www.security-informatics.com/content/2/1/10 Rasmus Petersen Uffe Wiil Security Informatics 2013, null:10 2013-05-01T00:00:00Z doi:10.1186/2190-8532-2-10 /content/figures/2190-8532-2-10-toc.gif Security Informatics 2190-8532 ${item.volume} 10 2013-05-01T00:00:00Z PDF This paper considers the role of virtual communities as a tool for recruitment used by terrorist and extremist movements. Considering involvement as a psychological process and thinking about recruitment from a psychological perspective, the facilitation of online elements important to this process are highlighted in this paper. In addition a short case study taken from the use of the Internet by the Radical Right movement provides examples of how the Internet can be used to promote involvement and encourage recruitment into terrorist and extremist movements. http://www.security-informatics.com/content/2/1/9 Lorraine Bowman-Grieve Security Informatics 2013, null:9 2013-03-23T00:00:00Z doi:10.1186/2190-8532-2-9 /content/figures/2190-8532-2-9-toc.gif Security Informatics 2190-8532 ${item.volume} 9 2013-03-23T00:00:00Z XML Efforts to combat and prevent transnational terrorism rely, to a great extent, on the effective allocation of security resources. Critical to the success of this allocation process is the identification of the likely geopolitical sources and targets of terrorism. We construct the network of transnational terrorist attacks, in which source (sender) and target (receiver) countries share a directed edge, and we evaluate a network analytic approach to forecasting the geopolitical sources and targets of terrorism. We integrate a deterministic, similarity-based, link prediction framework into a probabilistic modeling approach in order to develop an edge-forecasting method. Using a database of over 12,000 transnational terrorist attacks occurring between 1968 and 2002, we show that probabilistic link prediction is not only capable of accurate forecasting during a terrorist campaign, but is a promising approach to forecasting the onset of terrorist hostilities between a source and a target. http://www.security-informatics.com/content/2/1/8 Bruce Desmarais Skyler Cranmer Security Informatics 2013, null:8 2013-03-15T00:00:00Z doi:10.1186/2190-8532-2-8 /content/figures/2190-8532-2-8-toc.gif Security Informatics 2190-8532 ${item.volume} 8 2013-03-15T00:00:00Z PDF Police patrols play an important role in public safety. The patrol district design is an important factor affecting the patrol performances, such as average response time and workload variation. The redistricting or redrawing police command boundaries can be described as partitioning a police jurisdiction into command districts with the constraints such as contiguity and compactness. The size of the possible sample space is large and the corresponding graph-partitioning problem is NP-complete. In our approach, the patrol districting plans generated by a parameterized redistricting procedure are evaluated using an agent-based simulation model we implemented in Java Repast in a geographic information system (GIS) environment. The relationship between districting parameters and response variables is studied and better districting plans can be generated. After in-depth evaluations of these plans, we perform a Pareto analysis of the outputs from the simulation to find the non-dominated set of plans on each of the objectives. This paper also includes a case study for the police department of Charlottesville, VA, USA. Simulation results show that patrol performance can be improved compared with the current districting solution. http://www.security-informatics.com/content/2/1/7 Yue Zhang Donald Brown Security Informatics 2013, null:7 2013-03-02T00:00:00Z doi:10.1186/2190-8532-2-7 /content/figures/2190-8532-2-7-toc.gif Security Informatics 2190-8532 ${item.volume} 7 2013-03-02T00:00:00Z XML While the use of the internet and social media as a tool for extremists and terrorists has been well documented, understanding the mechanisms at work has been much more elusive. This paper begins with a grounded theory approach guided by a new theoretical approach to power that utilizes both terrorism cases and extremist social media groups to develop an explanatory model of radicalization. Preliminary hypotheses are developed, explored and refined in order to develop a comprehensive model which is then presented. This model utilizes and applies concepts from social theorist Michel Foucault, including the use of discourse and networked power relations in order to normalize and modify thoughts and behaviors. The internet is conceptualized as a type of institution in which this framework of power operates and seeks to recruit and radicalize. Overall, findings suggest that the explanatory model presented is a well suited, yet still incomplete in explaining the process of online radicalization. http://www.security-informatics.com/content/2/1/6 Robyn Torok Security Informatics 2013, null:6 2013-02-12T00:00:00Z doi:10.1186/2190-8532-2-6 /content/figures/2190-8532-2-6-toc.gif Security Informatics 2190-8532 ${item.volume} 6 2013-02-12T00:00:00Z XML Computational criminology has been seen primarily as computer-intensive simulations of criminal wrongdoing. But there is a growing menu of computer-intensive applications in criminology that one might call “computational,” which employ different methods and have different goals. This paper provides an introduction to computer-intensive, tree-based, machine learning as the method of choice, with the goal of forecasting criminal behavior. The approach is “black box,” for which no apologies are made. There are now in the criminology literature several such applications that have been favorably evaluated with proper hold-out samples. Peeks into the black box indicate that conventional, causal modeling in criminology is missing significant features of crime etiology. http://www.security-informatics.com/content/2/1/5 Richard Berk Security Informatics 2013, null:5 2013-01-23T00:00:00Z doi:10.1186/2190-8532-2-5 /content/figures/2190-8532-2-5-toc.gif Security Informatics 2190-8532 ${item.volume} 5 2013-01-23T00:00:00Z XML Despite their importance for stakeholders in the criminal justice system, few methods have been developed for determining which criminal behavior variables will produce accurate sentence predictions. Some approaches found in the literature resort to techniques based on indirect variables, but not on the social network behavior with exception of the work of Baker and Faulkner [ASR 58: 837–860, 1993]. Using information on the Caviar Network narcotics trafficking group as a real-world case, we attempt to explain sentencing outcomes employing the social network indicators. Specifically, we report the ability of centrality measures to predict a) the verdict (innocent or guilty) and b) the sentence length in years. We show that while the set of indicators described by Baker and Faulkner yields good predictions, introduction of the additional centrality measures generates better predictions. Some ideas for orienting future research on further improvements to sentencing outcome prediction are discussed. http://www.security-informatics.com/content/2/1/4 Carlo Morselli Victor Masias Fernando Crespo Sigifredo Laengle Security Informatics 2013, null:4 2013-01-22T00:00:00Z doi:10.1186/2190-8532-2-4 /content/figures/2190-8532-2-4-toc.gif Security Informatics 2190-8532 ${item.volume} 4 2013-01-22T00:00:00Z XML The objectives of this research are to display the utility of using agent based model and simulated experiments in understanding criminal behavior. In particular, this research focuses upon the distance decay function that has wide applicability in understanding ways in which offenders move about their awareness space and select their targets for committing crime. The basis for distance decay is an assumption that the offender apprehends recognition by his neighbors and so tends to commit his crime a little away but not too far from his home location. But this is an untested assumption and based upon another assumption that recognition comes from frequent interactions. There is no simple way to test these assumptions in real life. This paper argues that simulated experiments using agent based modeling are appropriate methods for difficult to test criminological concepts. In this research, two types of agents are created- one representing the offender and the other- the victim. They are assigned specific characteristics that control their action such as moving in a neighborhood, making rational choice to maximize their gain while minimizing the risk of apprehension from interaction with other residents of the neighborhood. The simulation result displays that beginning with these small principles the final model emerges as a pattern of target selection similar to the distance decay function. The importance of this technique lies in the fact that such experiments provide the means to apply agent based modeling to validate a variety of criminological concepts. While the technique has limitations of validation it can help in understanding the behavior of offenders as they commit their crimes individually as well as in groups. http://www.security-informatics.com/content/2/1/3 Arvind Verma Ramyaa Ramyaa Suresh Marru Security Informatics 2013, null:3 2013-01-19T00:00:00Z doi:10.1186/2190-8532-2-3 /content/figures/2190-8532-2-3-toc.gif Security Informatics 2190-8532 ${item.volume} 3 2013-01-19T00:00:00Z XML Computational criminology seeks to address criminological and criminal justice problems through the use of applied mathematics, computer science, and criminology. The development of mathematical and computational methods along with the emergence of cyberspace demonstrates the need for innovative degree programs that focus on computational criminology. The purpose of this article is to highlight the significance of dual computer-criminology degree programs. The article first discuses two major shifts in the study of criminology: the facilitation of new methodologies and data techniques; and, the development of new types of crime and delinquency through advancements in computer technology. Next, the article describes the need for dual computer-criminology degree programs and employs Florida State University’s program as an example of what these programs offer aspiring criminologists. Finally, the article concludes with discussion of future plans for the Florida State University dual computer-criminology degree program that are applicable to other criminology programs both within the United States and also internationally. http://www.security-informatics.com/content/2/1/2 Colby Valentine Carter Hay Kevin Beaver Thomas Blomberg Security Informatics 2013, null:2 2013-01-16T00:00:00Z doi:10.1186/2190-8532-2-2 /content/figures/2190-8532-2-2-toc.gif Security Informatics 2190-8532 ${item.volume} 2 2013-01-16T00:00:00Z XML Dynamic activity involving social networks often has distinctive temporal patterns that can be exploited in situations involving incomplete information. Gang rivalry networks, in particular, display a high degree of temporal clustering of activity associated with retaliatory behavior. A recent study of a Los Angeles gang network shows that known gang activity between rivals can be modeled as a self-exciting point process on an edge of the rivalry network. In real-life situations, data is incomplete and law-enforcement agencies may not know which gang is involved. However, even when gang activity is highly stochastic, localized excitations in parts of the known dataset can help identify gangs responsible for unsolved crimes. Previous work successfully incorporated the observed clustering in time of the data to identify gangs responsible for unsolved crimes. However, the authors assumed that the parameters of the model are known, when in reality they have to be estimated from the data itself. We propose an iterative method that simultaneously estimates the parameters in the underlying point process and assigns weights to the unknown events with a directly calculable score function. The results of the estimation, weights, error propagation, convergence and runtime are presented. http://www.security-informatics.com/content Rachel Hegemann Erik Lewis Andrea Bertozzi Security Informatics 2013, null:1 2013-01-12T00:00:00Z doi:10.1186/2190-8532-2-1 /content/figures/2190-8532-2-1-toc.gif Security Informatics 2190-8532 ${item.volume} 1 2013-01-12T00:00:00Z XML