TY - GEN
T1 - Collusion detection in online rating systems
AU - Allahbakhsh, Mohammad
AU - Ignjatovic, Aleksandar
AU - Benatallah, Boualem
AU - Beheshti, Seyed Mehdi Reza
AU - Bertino, Elisa
AU - Foo, Norman
PY - 2013/4/10
Y1 - 2013/4/10
N2 - Online rating systems are subject to unfair evaluations. Users may try to individually or collaboratively promote or demote a product. Collaborative unfair rating, i.e., collusion, is more damaging than individual unfair rating. Detecting massive collusive attacks as well as honest looking intelligent attacks is still a real challenge for collusion detection systems. In this paper, we study impact of collusion in online rating systems and asses their susceptibility to collusion attacks. The proposed model uses frequent itemset mining technique to detect candidate collusion groups and sub-groups. Then, several indicators are used for identifying collusion groups and to estimate how damaging such colluding groups might be. The model has been implemented and we present results of experimental evaluation of our methodology.
AB - Online rating systems are subject to unfair evaluations. Users may try to individually or collaboratively promote or demote a product. Collaborative unfair rating, i.e., collusion, is more damaging than individual unfair rating. Detecting massive collusive attacks as well as honest looking intelligent attacks is still a real challenge for collusion detection systems. In this paper, we study impact of collusion in online rating systems and asses their susceptibility to collusion attacks. The proposed model uses frequent itemset mining technique to detect candidate collusion groups and sub-groups. Then, several indicators are used for identifying collusion groups and to estimate how damaging such colluding groups might be. The model has been implemented and we present results of experimental evaluation of our methodology.
UR - http://www.scopus.com/inward/record.url?scp=84875853292&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-37401-2_21
DO - 10.1007/978-3-642-37401-2_21
M3 - Conference proceeding contribution
AN - SCOPUS:84875853292
SN - 9783642374005
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 196
EP - 207
BT - Web Technologies and Applications
A2 - Ishikawa, Yoshiharu
A2 - Li, Jianzhong
A2 - Wang, Wei
A2 - Zhang, Rui
PB - Springer, Springer Nature
T2 - 15th Asia-Pacific Web Conference on Web Technologies and Applications, APWeb 2013
Y2 - 4 April 2013 through 6 April 2013
ER -