Shadow Attacks Based on Password Patterns Password Reuses

As the number of websites is increasing, the security level of password enabled accounts is no longer secured. It may possible that end users can create the many accounts on either same website or multiple websites, hence the passwords for all accounts from the same user likely to similar or same. This leads the users account can compromised by attackers and then identify the same user passwords in sensitive accounts like banking accounts. This type of attacks on password is basically known as shadow attacks on password. In this project, we are presenting the framework to study the state of art of Cross Site Password Reused (CSPR) and Intra Site Password Reuses (ISPR) based on large scale password datasets in order to improve the password reuse success rate. The novelty of the proposed approach is detailed empirical study on web password reuses of both cross site and intra site password reuses. The pre-processing step is redesigned in our proposed work in which noise removal is done in terms of invalid email addresses, spaces etc. rather removing the duplicate accounts. This will helps to improve the guessing success rate performance as compared to previous work