Trust Enabled Secure Multiparty Computation

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.