GPU-Accelerated Password Cracking of PDF Files
Digital document file such as Adobe Acrobat or MS-Office is encrypted by its own ciphering algorithm with a user password. When this password is not known to a user or a forensic inspector, it is necessary to recover the password to open the encrypted file. Password cracking by brute-force search is a perfect approach to discover the password but a time consuming process. This paper presents a new method of speeding up password recovery on Graphic Processing Unit (GPU) using a Compute Unified Device Architecture (CUDA). PDF files are chosen as a password cracking target, and the Abode Acrobat password recovery algorithm is examined. Experimental results show that the proposed method gives high performance at low cost, with a cluster of GPU nodes significantly speeding up the password recovery by exploiting a number of computing nodes. Password cracking performance is increased linearly in proportion to the number of computing nodes and GPUs.
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