Abstract: A method and system for adaptive vulnerability scanning (AVS) of an application is provided. The adaptive vulnerability scanning of an application assists in identifying new vulnerabilities dynamically. The endpoints of an application are scanned using a predefined set of rules. Subsequently, one or more possible vulnerabilities are presented. The vulnerabilities are analyzed and predefined rules are modified. The steps of scanning the application and modification of rules are iteratively repeated till the adaptive vulnerability scanning capability is achieved. A neural network is used for training the adaptive vulnerability scanner. This neural network is made to learn some rules based on predefined set of rules while undergoing the training phase. At least one weight in neural networks is altered while imparting the self learning capability.

Abstract: A method for validating authenticity of identity claims of one or more communicating entities in an online transaction over a network is disclosed. The method includes extracting identity information of the first communicating entity by the second communicating entity during online transaction and prompting a client to provide a unique resource name of the first entity. Further, the method includes validating the identity information extracted from the first entity by checking identity information already registered in a registry. Later the method includes authenticating the identity claims of the first entity based on the validation results. The method also includes steps for registering identity information of the first entity within the registry.

Abstract: A method and system for adaptive vulnerability scanning (AVS) of an application is provided. The adaptive vulnerability scanning of an application assists in identifying new vulnerabilities dynamically. The endpoints of an application are scanned using a predefined set of rules. Subsequently, one or more possible vulnerabilities are presented. The vulnerabilities are analyzed and predefined rules are modified. The steps of scanning the application and modification of rules are iteratively repeated till the adaptive vulnerability scanning capability is achieved. A neural network is used for training the adaptive vulnerability scanner. This neural network is made to learn some rules based on predefined set of rules while undergoing the training phase. At least one weight in neural networks is altered while imparting the self learning capability.

Abstract: A method for validating authenticity of identity claims of one or more communicating entities in an online transaction over a network is disclosed. The method includes extracting identity information of the first communicating entity by the second communicating entity during online transaction and prompting a client to provide a unique resource name of the first entity. Further, the method includes validating the identity information extracted from the first entity by checking identity information already registered in a registry. Later the method includes authenticating the identity claims of the first entity based on the validation results. The method also includes steps for registering identity information of the first entity within the registry.