33185297
Untangling Criminal Networks: A Case Study
Knowledge about criminal networks has important implications for crime investigation and the anti-terrorism campaign. However, lack of advanced, automated techniques has limited law enforcement and intelligence agencies' ability to combat crime by discovering structural patterns in criminal networks. In this research we used the concept space approach, clustering technology, social network analysis measures and approaches, and multidimensional scaling methods for automatic extraction, analysis, and visualization of criminal networks and their structural patterns. We conducted a case study with crime investigators from the Tucson Police Department. They validated the structural patterns discovered from gang and narcotics criminal enterprises. The results showed that the approaches we proposed could detect subgroups, central members, and between-group interaction patterns correctly most of the time. Moreover, our system could extract the overall structure for a network that might be useful in the development of effective disruptive strategies for criminal networks.
43179863
Analyzing Terrorist Networks: A Case Study of the Global Salafi Jihad Network
It is very important for us to understand the functions and structures of terrorist networks to win the battle against terror. However, previous studies of terrorist network structure have generated little actionable results. This is mainly due to the difficulty in collecting and accessing reliable data and the lack of advanced network analysis methodologies in the field. To address these problems, we employed several advance network analysis techniques ranging from social network analysis to Web structural mining on a Global Salafi Jihad network dataset collected through a large scale empirical study. Our study demonstrated the effectiveness and usefulness of advanced network techniques in terrorist network analysis domain. We also introduced the Web structural mining technique into the terrorist network analysis field which, to the best our knowledge, has never been used in this domain. More importantly, the results from our analysis provide not only insights for terrorism research community but also empirical implications that may help law-reinforcement, intelligence, and security communities to make our nation safer.
7877784
On the Topology of the Dark Web of Terrorist Groups
In recent years, terrorist groups have used the WWW to spread their ideologies, disseminate propaganda, and recruit members. Studying the terrorist websites may help us understand the characteristics of these websites and predict terrorist activities. In this paper, we propose to apply network topological analysis methods on systematically collected the terrorist website data and to study the structural characteristics at the Web page level. We conducted a case study using the methods on three collections of Middle-Eastern, US domestic, and Latin-American terrorist websites. We found that these three networks have the small-world and scale-free characteristics. We also found that smaller size websites which share same interests tend to make stronger inter-website linkage relationships.
16185032
Using Social Contextual Information to Match Criminal Identities
Criminal identity matching is crucial to crime investigation in law enforcement agencies. Existing techniques match identities that refer to the same individuals based on simple identity features. These techniques are subject to several problems. First, there is an effectiveness trade-off between the false negative and false positive rates. The improvement of one rate usually lowers the other. Second, in some situations such as identity theft, simple-feature-based techniques are unable to match identities that have completely different identity feature values. We argue that the information about the social context of an individual may provide additional information for revealing the individual’s identity, helping improve the effectiveness of identity matching techniques. We define two types of social contextual features: role-based personal features and social group features. Experiments showed that social contextual features, especially the structural similarity and the relational similarity, significantly improved the precision without lowering the recall of criminal identity matching tasks.
1639751
Expertise visualization: An implementation and study based on cognitive fit theory
Expertise management systems are being widely adopted in organizations to manage tacit knowledge. These systems have successfully applied many information technologies developed for document management to support collection, processing, and distribution of expertise information. In this paper, we report a study on the potential of applying visualization techniques to support more effective and efficient exploration of the expertise information space. We implemented two widely applied dimensionality reduction visualization techniques, the self-organizing map (SOM) and multidimensional scaling (MDS), to generate compact but distorted (due to the dimensionality reduction) map visualizations for an expertise data set. We tested cognitive fit theory in our context by comparing the SOM and MDS displays with a standard table display for five tasks selected from a low-level, domain-independent visual task taxonomy. The experimental results based on a survey data set of research expertise of the business school professors suggested that using both SOM and MDS visualizations is more efficient than using the table display for the associate, compare, distinguish, and cluster tasks, but not the rank task. Users generally achieved comparable effectiveness for all tasks using the tabular and map displays in our study. © 2006 Elsevier B.V. All rights reserved.
215893227
CrimeNet explorer: a framework for criminal network knowledge discovery
Knowledge about the structure and organization of criminal networks is important for both crime investigation and the development of effective strategies to prevent crimes. However, except for netw...
33666708
Topological Peeling and Applications
We present a new approach, called topological peeling, for traversing a portion AR of the arrangement formed by n lines within a convex region R on the plane. Topological peeling visits the cells of AR in a fashion of propagating a "wave" of a special shape (called a double-wriggle curve) starting at a single source point. This special traversal fashion enables us to solve several problems (e.g., computing shortest paths) on planar arrangements to which previously best known arrangement traversal techniques such as topological sweep and topological walk may not be directly applicable. Our topological peeling algorithm takes O(K + n log(n + r)) time and O(n + r) space, where K is the number of cells in AR and r is the number of boundary vertices of R. Comparing with topological walk, topological peeling uses a simpler and more efficient way to sweep different types of lines, and relies heavily on exploring small local structures, rather than a much larger global structure. Experiments show that, on average, topological peeling outperforms topological walk by 10–25% in execution time.
11432676
Building Embedded Fault-Tolerant Systems for Critical Applications: An Experimental Study
An increasing range of industries have a growing dependence on embedded software systems, many of which are safety-critical, real-time applications that require extremely high dependability. Two fundamental approaches — fault avoidance and fault tolerance — have been proposed to increase the overall dependability of such systems. However, the increased cost of using the fault tolerance approach may mean that this increase in dependability is not worth the extra expense involved. We describe an experiment undertaken in order to establish whether or not software redundancy (or the multi-version design method) can offer increased dependability over the traditional single-version development approach when given the same level of resources. The results of this and a subsequent follow-up study are then given. The analytic results from these experiments show that despite the poor quality of individual versions, the multi-version method results in a safer system than the single-version solution. It is evident that regarding the single-version method as a “seem-to-be” safer design decision for critical applications is not generally justifiable.
28468806
Space-code bloom filter for efficient per-flow traffic measurement
Per-flow traffic measurement is critical for usage accounting, traffic engineering, and anomaly detection. Previous methodologies are either based on random sampling (e.g., Cisco's NetFlow), which is inaccurate, or only account for the "elephants". We introduce a novel technique for measuring per-flow traffic approximately, for all flows regardless of their sizes, at very high-speed (say, OC768). The core of this technique is a novel data structure called space code bloom filter (SCBF). A SCBF is an approximate representation of a multiset; each element in this multiset is a traffic flow and its multiplicity is the number of packets in the flow. The multiplicity of an element in the multiset represented by SCBF can be estimated through either of two mechanisms-maximum likelihood estimation (MLE) or mean value estimation (MVE). Through parameter tuning, SCBF allows for graceful tradeoff between measurement accuracy and computational and storage complexity. SCBF also contributes to the foundation of data streaming by introducing a new paradigm called blind streaming. We evaluate the performance of SCBF through mathematical analysis and through experiments on packet traces gathered from a tier-1 ISP backbone. Our results demonstrate that SCBF achieves reasonable measurement accuracy with very low storage and computational complexity
23862247
The auxiliary space method and optimal multigrid preconditioning techniques for unstructured grids
An abstract framework ofauxiliary space method is proposed and, as an application, an optimal multigrid technique is developed for general unstructured grids. The auxiliary space method is a (nonnested) two level preconditioning technique based on a simple relaxation scheme (smoother) and an auxiliary space (that may be roughly understood as a nonnested coarser space). An optimal multigrid preconditioner is then obtained for a discretized partial differential operator defined on an unstructured grid by using an auxiliary space defined on a more structured grid in which a furthernested multigrid method can be naturally applied. This new technique makes it possible to apply multigrid methods to general unstructured grids without too much more programming effort than traditional solution methods. Some simple examples are also given to illustrate the abstract theory and for instance the Morley finite element space is used as an auxiliary space to construct a preconditioner for Argyris element for biharmonic equations. Some numerical results are also given to demonstrate the efficiency of using structured grid for auxiliary space to precondition unstructured grids.ZusammenfassungDas abstrakte Konzept derHilfsraummethode wird vorgeschlagen, und als Anwendung eine optimale Mehrgittertechnik für allgemeine unstrukturierte Gitter entwickelt. Die Hilfsraummethode ist eine (nichtgeschachtelte) Zweigitter-Präkonditionierungstechnik, bestehend aus einem einfachen Glättungsverfahren und einem Hilfsgitter, das etwa einem nichtgeschachtelten Grobgitter entspricht. Zu einer partiellen Differentialgleichung, die auf einem unstrukturierten Gitter diskretisiert ist, wird eine optimale Mehrgittermethode konstruiert, die einen Hilfsraum mit einem besser strukturierten Gitter verwendet. In diesem ist ein Mehrgitterverfahren mit geschachtelten Räumen anwendbar. Die neue Technik ermöglicht es, Mehrgittermethoden für unstrukturierte Gitter anzuwenden, die nur wenig mehr Programmieraufwand erfordern als traditionelle Methoden. Einige einfache Beispiele sollen die abstrakte Theorie illustrieren. Als Beispiel wird der Morley-FE-Raum als Hilfsraum zur Präkonditionierung der Argyris-Elemente für die biharmonische Gleichung benutzt. Einige numerische Resultate demonstrieren die Effizienz des Einsatzes des strukturierten Hilfsraumes.
207162632
Utility-based anonymization for privacy preservation with less information loss
Privacy becomes a more and more serious concern in applications involving microdata. Recently, efficient anonymization has attracted much research work. Most of the previous methods use global recoding, which maps the domains of the quasi-identifier attributes to generalized or changed values. However, global recoding may not always achieve effective anonymization in terms of discernability and query answering accuracy using the anonymized data. Moreover, anonymized data is often used for analysis. As well accepted in many analytical applications, different attributes in a data set may have different utility in the analysis. The utility of attributes has not been considered in the previous methods.
 In this paper, we study the problem of utility-based anonymization. First, we propose a simple framework to specify utility of attributes. The framework covers both numeric and categorical data. Second, we develop two simple yet efficient heuristic local recoding methods for utility-based anonymization. Our extensive performance study using both real data sets and synthetic data sets shows that our methods outperform the state-of-the-art multidimensional global recoding methods in both discernability and query answering accuracy. Furthermore, our utility-based method can boost the quality of analysis using the anonymized data.