Title :
Trust Enabled Secure Multiparty Computation
Author :
Dong, Renren ; Kresman, Ray
Author_Institution :
Dept. of Comput. Sci., Bowling Green State Univ., Bowling Green, OH, USA
Abstract :
Hamiltonian cycles play an important role in graph theory and data mining applications. Two Hamiltonian cycles that don´t have an edge in common are known as edge-disjoint Hamiltonian cycles (EDHCs). EDHCs are useful in computer networks. They have found applications in improving network capacity, fault-tolerance and collusion resistant mining algorithms. This paper extends previous work on collusion resistance capability of data mining algorithms. We first propose a new trust model for network computers. We then use this model as a basis to improve the collusion resistance capability of data mining algorithms. We use a performance metric to quantify the improvement.
Keywords :
data mining; graph theory; computer network; data mining; edge disjoint Hamiltonian cycles; fault tolerance; graph theory; network capacity; secure multiparty computation; trust model; Data mining; Greedy algorithms; Mathematical model; Measurement; Resistance; Safety; Silicon; Data mining; Privacy; Trust enabled;
Conference_Titel :
Information Visualisation (IV), 2010 14th International Conference
Conference_Location :
London
Print_ISBN :
978-1-4244-7846-0