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.
17196137
Fighting organized crimes: using shortest-path algorithms to identify associations in criminal networks
Effective and efficient link analysis techniques are needed to help law enforcement and intelligence agencies fight organized crimes such as narcotics violation, terrorism, and kidnapping. In this paper, we propose a link analysis technique that uses shortest-path algorithms, priority-first-search (PFS) and two-tree PFS, to identify the strongest association paths between entities in a criminal network. To evaluate effectiveness, we compared the PFS algorithms with crime investigators' typical association-search approach, as represented by a modified breadth-first-search (BFS). Our domain expert considered the association paths identified by PFS algorithms to be useful about 70% of the time, whereas the modified BFS algorithm's precision rates were only 30% for a kidnapping network and 16.7% for a narcotics network. Efficiency of the two-tree PFS was better for a small, dense kidnapping network, and the PFS was better for the large, sparse narcotics network.
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.
8575653
Using Shortest Path Algorithms to Identify Criminal Associations
Frequently in criminal investigations, law enforcement agencies face the problem of identifying associations between a group of entities such as individuals and organizations. In this paper we present a link analysis technique to solve such a problem. This approach uses shortest path algorithms to find the strongest associations between two or more given entities. The experimental results have demonstrated that our approach is potentially useful in terms of quality and efficiency. Specifically, we found that the two-tree Priority-First Search algorithm in most cases was the fastest algorithm to find shortest paths and the paths found consisted of meaningful criminal associations around 80 percent of the time.
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.
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...
16173548
Robust traffic matrix estimation with imperfect information: making use of multiple data sources
Estimation of traffic matrices, which provide critical input for network capacity planning and traffic engineering, has recently been recognized as an important research problem. Most of the previous approaches infer traffic matrix from either SNMP link loads or sampled NetFlow records. In this work, we design novel inference techniques that, by statistically correlating SNMP link loads and sampled NetFlow records, allow for much more accurate estimation of traffic matrices than obtainable from either information source alone, even when sampled NetFlow records are available at only a subset of ingress. Our techniques are practically important and useful since both SNMP and NetFlow are now widely supported by vendors and deployed in most of the operational IP networks. More importantly, this research leads us to a new insight that SNMP link loads and sampled NetFlow records can serve as "error correction codes" to each other. This insight helps us to solve a challenging open problem in traffic matrix estimation, "How to deal with dirty data (SNMP and NetFlow measurement errors due to hardware/software/transmission problems)?" We design techniques that, by comparing notes between the above two information sources, identify and remove dirty data, and therefore allow for accurate estimation of the traffic matrices with the cleaned dat.We conducted experiments on real measurement data obtained from a large tier-1 ISP backbone network. We show that, when full deployment of NetFlow is not available, our algorithm can improve estimation accuracy significantly even with a small fraction of NetFlow data. More importantly, we show that dirty data can contaminate a traffic matrix, and identifying and removing them can reduce errors in traffic matrix estimation by up to an order of magnitude. Routing changes is another a key factor that affects estimation accuracy. We show that using them as the a priori, the traffic matrices can be estimated much more accurately than those omitting the routing change. To the best of our knowledge, this work is the first to offer a comprehensive solution which fully takes advantage of using multiple readily available data sources. Our results provide valuable insights on the effectiveness of combining flow measurement and link load measurement.
52802993
Issues and challenges in the performance analysis of real disk arrays
The performance modeling and analysis of disk arrays is challenging due to the presence of multiple disks, large array caches, and sophisticated array controllers. Moreover, storage manufacturers may not reveal the internal algorithms implemented in their devices, so real disk arrays are effectively black-boxes. We use standard performance techniques to develop an integrated performance model that incorporates some of the complexities of real disk arrays. We show how measurement data and baseline performance models can be used to extract information about the various features implemented in a disk array. In this process, we identify areas for future research in the performance analysis of real disk arrays.
17229097
Distance irredundance and connected domination numbers of a graph
Let k be a positive integer and G be a connected graph. This paper considers the relations among four graph theoretical parameters: the k-domination number @c"k(G), the connected k-domination number @c"k^c(G); the k-independent domination number @c"k^i(G) and the k-irredundance number ir"k(G). The authors prove that if an ir"k-set X is a k-independent set of G, then ir"k(G)[email protected]"k(G)[email protected]"k^i(G), and that for k>=2, @c"k^c(G)=1 if ir"k(G)=1, @c"k^c(G)=
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.
17909513
Determining an optimal penetration among weighted regions in two and three dimensions
We present efficient algorithms for solving the problem of computing an optimal penetration (a ray or a semi-ray) among weighted regions in 2-D and 3-D spaces. This problem finds applications in several areas, such as radiation therapy, geological exploration, and environmental engineering. Our algorithms are based on a combination of geometric techniques and optimization methods. Our geometric analysis shows that the d-D (d = 2, 3) optimal penetration problem can be reduced to solving O(n2(d−1)) instances of certain special types of non-linear optimization problems, where n is the total number of vertices of the regions. We also give implementation results of our 2-D algorithms.