TY - GEN
T1 - Terrorist network monitoring with identifying code
AU - Sen, Arunabha
AU - Goliber, Victoria Horan
AU - Zhou, Chenyang
AU - Basu, Kaustav
PY - 2018/1/1
Y1 - 2018/1/1
N2 - On multiple incidences of terrorist attacks in recent times across Europe, it has been observed that the perpetrators of the attack were in the suspect databases of the law enforcement authorities, but weren’t under active surveillance at the time of the attack due to resource limitations on the part of the authorities. As the suspect databases in various European countries are very large, and it takes significant amount of technical and human resources to monitor a suspect in the database, monitoring all the suspects in the database may be an impossible task. In this paper, we propose a scheme utilizing Identifying Codes that will significantly reduce the resource requirement of law enforcement authorities, and will have the capability of uniquely identifying a suspect in case the suspect becomes active in planning a terrorist attack. The scheme relies on the assumption that, when an individual becomes active in planning a terrorist attack, his/her friends/associates will have some inkling of the individuals plan. Accordingly, even if the individual is not under active surveillance by the authorities, but the individual’s friends/associates are, the individual planning the attack can be uniquely identified. We applied our technique on two terrorist networks, one involved in an attack in Paris and the other involved in the 9/11 attack. We show that, in the Paris network, if 5 of the 10 individuals were monitored, the attackers most likely would have been exposed. If only 15 out of the 37 individuals involved in the 9/11 attack were under surveillance, specific individuals involved in the planning of the 9/11 attack would have been exposed.
AB - On multiple incidences of terrorist attacks in recent times across Europe, it has been observed that the perpetrators of the attack were in the suspect databases of the law enforcement authorities, but weren’t under active surveillance at the time of the attack due to resource limitations on the part of the authorities. As the suspect databases in various European countries are very large, and it takes significant amount of technical and human resources to monitor a suspect in the database, monitoring all the suspects in the database may be an impossible task. In this paper, we propose a scheme utilizing Identifying Codes that will significantly reduce the resource requirement of law enforcement authorities, and will have the capability of uniquely identifying a suspect in case the suspect becomes active in planning a terrorist attack. The scheme relies on the assumption that, when an individual becomes active in planning a terrorist attack, his/her friends/associates will have some inkling of the individuals plan. Accordingly, even if the individual is not under active surveillance by the authorities, but the individual’s friends/associates are, the individual planning the attack can be uniquely identified. We applied our technique on two terrorist networks, one involved in an attack in Paris and the other involved in the 9/11 attack. We show that, in the Paris network, if 5 of the 10 individuals were monitored, the attackers most likely would have been exposed. If only 15 out of the 37 individuals involved in the 9/11 attack were under surveillance, specific individuals involved in the planning of the 9/11 attack would have been exposed.
KW - Approximation algorithm
KW - Computational complexity
KW - Identification code
KW - Terrorist network
UR - http://www.scopus.com/inward/record.url?scp=85049773670&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85049773670&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-93372-6_36
DO - 10.1007/978-3-319-93372-6_36
M3 - Conference contribution
AN - SCOPUS:85049773670
SN - 9783319933719
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 329
EP - 339
BT - Social, Cultural, and Behavioral Modeling - 11th International Conference, SBP-BRiMS 2018, Proceedings
A2 - Bisgin, Halil
A2 - Thomson, Robert
A2 - Hyder, Ayaz
A2 - Dancy, Christopher
PB - Springer Verlag
T2 - 11th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction conference and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2018
Y2 - 10 July 2018 through 13 July 2018
ER -