A Novel Risk Recognition Method in Web Services

To deal with the risk recognition from the complex Web environment, a novel risk recognition method was studied through attribute reduction and rule extraction based an rough set. According to the indiscernible relation in rough set, discernible vector and its addition rule were defined. And meanwhile the core attribute set and the attribute reduction were obtained by scanning the information table just only one time depending on the discernible vector addition rule. Attribute value reduction was realized through gradually deleting the redundant attribute value for every rule in the information table by the correlation of condition attributes and decision attributes. Finally, a concise rule set for risk recognition was obtained. The illustration and experiment results indicate that the method is effective and efficient.