Enhancing border security: Mutual information analysis to identify suspect vehicles
Decision Support SystemsPublished 20 October 2006
Siddharth Kaza, Yuan Wang, Hsinchun Chen
Citations23
SJR quartileQ1
SJR score2.37
SNIP2.59
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
This work proposes to modify the MI formulation to include heuristics by using law enforcement data from border-area jurisdictions that perform significantly better than classical MI in identifying potentially criminal vehicles.
Abstract
In recent years border safety has been identified as a critical part of homeland security. The Department of Homeland Security searches vehicles entering the country for drugs and other contraband. Customs and Border Protection (CBP) agents believe that such vehicles operate in groups and if the criminal links of one vehicle are known then their border crossing patterns can be used to identify other partner vehicles. We perform this association analysis by using mutual information (MI) to identify pairs of vehicles that may be involved in criminal activity. CBP agents also suggest that criminal vehicles may cross at certain times or ports to try and evade inspection. We propose to modify the MI formulation to include these heuristics by using law enforcement data from border-area jurisdictions. Statistical tests and selected cases judged by domain experts show that modified MI performs significantly better than classical MI in identifying potentially criminal vehicles.
Keywords
Social SciencesMedicine
Bell System Technical JournalA Mathematical Theory of Communication
80,675 Citations1948Claude E. Shannon
Mining association rules between sets of items in large databases
14,720 Citations1993Rakesh Agrawal, Tomasz Imieliński +1 more
An efficient algorithm is presented that generates all significant association rules between items in the database of customer transactions and incorporates buffer management and novel estimation and pruning techniques.
Fast algorithms for mining association rules
10,739 Citations1998Rakesh Agrawal, Ramakrishnan Srikant
Word association norms, mutual information, and lexicography
3,674 Citations1990Kenneth Church, Patrick Hanks
IEEE Transactions on Neural NetworksUsing mutual information for selecting features in supervised neural net learning
2,605 Citations1994Roberto Battiti
This paper investigates the application of the mutual information criterion to evaluate a set of candidate features and to select an informative subset to be used as input data for a neural network classifier.
Data Mining Approaches for Intrusion Detection
1,191 Citations2000Wenke Lee, Salvatore J. Stolfo
An agent-based architecture for intrusion detection systems where the learning agents continuously compute and provide the updated (detection) models to the detection agents is proposed.
Fast Binary Feature Selection with Conditional Mutual Information
833 Citations2004François Fleuret
It is shown that this feature selection method outperforms other classical algorithms, and that a naive Bayesian classifier built with features selected that way achieves error rates similar to those of state-of-the-art methods such as boosting or SVMs.
Journal of Machine Learning ResearchFast Binary Feature Selection with Conditional Mutual Information
598 Citations2004FleuretFrançois
Noun classification from predicate-argument structures
543 Citations1990Donald Hindle
The resulting quasi-semantic classification of nouns demonstrates the plausibility of the distributional hypothesis, and has potential application to a variety of tasks, including automatic indexing, resolving nominal compounds, and determining the scope of modification.
Data Mining and Knowledge DiscoveryEfficient Adaptive-Support Association Rule Mining for Recommender Systems
395 Citations2002Weiyang Lin, Sergio A. Álvarez +1 more
A collaborative recommendation technique based on a new algorithm specifically designed to mine association rules for this purpose, which reveals performance that is significantly better than that of traditional correlation-based approaches.
Parsing a natural language using mutual information statistics
127 Citations1990David M. Magerman, Mitchell P. Marcus
The generalized mutual information statistic is derived, the parsing algorithm is described, and results and sample output from the parser are presented.
BMC BioinformaticsExtending the mutual information measure to rank inferred literature relationships
116 Citations2004Jonathan D. Wren
Mutual information calculations can be effectively extended into implied relationships and a significance cutoff estimated from analysis of random word networks and the shared minimum MIM (MMIM) model is found to correlate best with the observed strength and frequency of known associations.
Decision Support SystemsData association methods with applications to law enforcement
72 Citations2003Donald E. Brown, Stephen Hagen
Tests show that data association methods significantly reduced the time required by manual methods with accuracy comparable to experienced crime analysts, and in comparison to analysis using the structured query language (SQL), the methods were both faster and more accurate.
DBMS Research at a Crossroads: The Vienna Update
63 Citations1993Michael Stonebraker, Rakesh Agrawal +3 more
This paper summarizes the discussion which took place at the IEEE International Conference on Data Engineering in Vienna, Austria on April 23, 1993 and contrasts the recommendations of the Laguna Beach participants with those obtained four years later by a similar group.
UA Campus Repository (The University of Arizona)Updateable PAT-Tree Approach to Chinese Key PhraseExtraction using Mutual Information: A Linguistic Foundation for Knowledge Management
55 Citations1999Thian‐Huat Ong, Hsinchun Chen
The requirements for a data structure that facilitates implementation of any statistical approaches to key-phrase extraction, including PATtree, PAT-array and suffix array with semi-infinite strings are reviewed.
Decision Support SystemsLarge-scale regulatory network analysis from microarray data: modified Bayesian network learning and association rule mining
53 Citations2006Zan Huang, Jiexun Li +3 more
Two algorithms for learning large-scale gene regulatory networks from microarray data are presented: a modified information-theory-based Bayesian network algorithm and a modified association rule algorithm.
Lecture notes in computer scienceMining market basket data using share measures and characterized itemsets
43 Citations1998Robert J. Hilderman, Colin L. Carter +2 more
The share-confidence framework for knowledge discovery from databases is proposed which addresses the problem of mining itemsets from market basket data and suggests how characterized itemsets can be generalized according to concept hierarchies associated with the characteristic attributes.
Cross-jurisdictional criminal activity networks to support border and transportation security
40 Citations2005Byron Marshall, Siddharth Kaza +5 more
A framework for effectively integrating data from local, state, federal, and international sources to create cross-jurisdictional criminal activity networks (CAN)s is proposed and a CAN system is created as part of the DHS-funded BorderSafe project.
International Journal of Artificial Intelligence ToolsMINING ASSOCIATION RULES FROM MARKET BASKET DATA USING SHARE MEASURES AND CHARACTERIZED ITEMSETS
29 Citations1998Robert J. Hilderman, Howard J. Hamilton +2 more
The share-confidence framework for knowledge discovery from databases is proposed which addresses the problem of mining characterized association rules from market basket data (i.e., itemsets) and shows how characterized itemsets can be generalized according to concept hierarchies associated with the characteristic attributes.
Applied BioinformaticsA Study of Statistical Methods for Function Prediction of Protein Motifs
16 Citations2004Tao Tao, Cheng Xiang Zhai +2 more
Among the methods tested, a probabilistic translation model with a popularity prior performs the best, suggesting that they can all be useful for predicting the function of an unknown motif.
Target vehicle identification for border safety using mutual information
14 Citations2005Siddharth Kaza, Tao Wang +2 more
The mutual information measure can be used to identify vehicles that can be potentially targeted at the border to reduce wait times for commerce, vehicles, and people as they cross the border.
International Conference on Digital Government ResearchAligning database columns using mutual information
13 Citations2005Patrick Pantel, Andrew Philpot +1 more
Identification of fundamental building blocks in protein sequences using statistical association measures
10 Citations2004Deborah K. Weisser, Judith Klein‐Seetharaman
A comparison with segment boundaries implied indirectly from secondary structure prediction and expert knowledge demonstrates that the algorithm can be used to statistically predict feature positions in protein sequences generically, without assumptions on the feature type to be detected.
Lecture notes in computer scienceSuspect Vehicle Identification for Border Safety with Modified Mutual Information
9 Citations2006Siddharth Kaza, Yuan Wang +1 more
This work performs association analysis by using mutual information (MI) to identify pairs of vehicles that are potentially involved in criminal activity and finds that the modified MI with time heuristics performs better than classical MI in identifying potentially criminal vehicles.
Target vehicle identification for border safety with modified mutual information
3 Citations2006Siddharth Kaza, Yuan Wang +1 more
This work proposes to modify the MI formulation to include this heuristic by using cross-jurisdictional criminal data from border-area jurisdictions to identify pairs of vehicles that are potentially involved in criminal activity.