Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-319-93372-6_36 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
Terrorist network,Identification code,Computational complexity,Approximation algorithm | Approximation algorithm,Internet privacy,Human resources,Computer science,Terrorism,Suspect,Network monitoring,Law enforcement | Conference |
Volume | ISSN | Citations |
10899 | 0302-9743 | 2 |
PageRank | References | Authors |
0.40 | 7 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arunabha Sen | 1 | 859 | 118.33 |
| Victoria Horan Goliber | 2 | 4 | 0.81 |
| Chenyang Zhou | 3 | 30 | 5.33 |
| Kaustav Basu | 4 | 25 | 7.62 |