IPASS: A novel open-source intelligence password scoring system

Password is one of the first and simplest lines of defence that is usually implemented to protect against unauthorized access to a network, local computer, or software application. Unfortunately, all security reports warn that more than 80% of cyber incidents and security breaches are caused by a weak or stolen password. Thus, users should maintain strong passwords for all the online and offline accounts they have. However, determining what makes a strong password is no easy task, with current methods of password scoring producing various degrees of accuracy and success. This paper outlines a novel password scoring method that utilises a person's social media accounts to improve the accuracy of password scoring by building custom word lists, comparing the password to words found in a person's social media and searching through a large database of leaked or breached passwords. The testing results show that the proposed method is more accurate than the classic zxcvbn scoring method. We also intend to address privacy concerns that may arise as a result of the access to user personal data by using a blockchain-based data sharing solution that can ensure respect of the individual's privacy and allow them to control the trade-offs around disclosure of their personal information.