Improvement on Traditional LDS Structures to Crack the Passwords Based on Individual’s Information

While it is not favored, internet users wish to include personal information in their passwords for easy recognition. In this paper, we disjoint user passwords from a Chinese website to inspect the intensity to which personal information resides in a password. Then we bring out a new measurement called Depth to find the interrelation between personal information and passwords. Afterwards, based on our analysis, we propose Individual-PCFG as a supplement to the Probabilistic Context-Free Grammar method to be semantics-rich. We manifest that Individual-PCFG cracks password much faster than PCFG by generating personal information related guesses and makes online attacks much more faster to succeed.