Research Article Open Access

Accelerating Digital Forensics through Parallel Computing

Ghada Elkabbany1, Mohamed Rasslan1 and Heba Aslan1
  • 1 Electronics Research Institute, Egypt


Digital crimes in the era of big data and cloud computing imposes significant challenges in digital forensics. Cloud environment provides low cost, easy management and reasonable solutions. Moreover, it supports big data structures and solutions (i.e., security, privacy and digital forensics). In order to achieve a secure digital forensics analysis in cloud environment, researchers have proposed solutions with expensive communication cost and computation overheads. Among these solutions Nasereldin et al. proposed a protocol which solves the problem of authenticity and integrity of evidence using signcryption technique. This leads to low communication and implementation overheads. Furthermore, identity-based cryptography is used to solve Public Key Infrastructure (PKI) problems. In addition, it is characterized by the ability to divide the message into small messages which is suitable for pipelining techniques. Nasreldin et al.'s signcryption protocol is based on Elliptic Curve Cryptography (ECC) which is implemented by using different mathematical operations. In this protocol, ECC mathematical operations take huge time during the execution of the algorithm. ECC consists of point doubling and point addition operations. These operations require the execution of many Montgomery modular multiplications that consume time. In this study, we introduce a technique to speed up ECC operations in order to enhance the efficiency of Nasreldin et al. protocol. In particular, we propose a multi-stage parallel design which consists of three stages. First, we speed up the point doubling and point addition operation. Secondly, we enhance the execution time of Montgomery multiplications. Finally, pipelining is used to obtain a better performance. The results show that the proposed design enhances Nasreldin et al. protocol’s execution time by 47.1, 64.7, 73.5 and 79.4%, assuming that the number of nodes is 2, 4, 6 and 12, respectively.

Journal of Computer Science
Volume 14 No. 2, 2018, 238-252


Submitted On: 24 December 2017 Published On: 20 February 2018

How to Cite: Elkabbany, G., Rasslan, M. & Aslan, H. (2018). Accelerating Digital Forensics through Parallel Computing. Journal of Computer Science, 14(2), 238-252.

  • 0 Citations



  • Digital Forensics
  • Evidence Collecting
  • Signcryption
  • Elliptic Curve Cryptography
  • Parallel Computing