Abstract
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.
Highlights
Big data and cloud computing are hot topics that shape the future of both academia and industry
Nasereldin et al.’s protocol makes use of identity-based cryptography to overcome Public Key Infrastructure (PKI) problems mentioned previously. This protocol needs larger number of Elliptic Curve Point Multiplication (ECPM) operations than other protocols (Zheng and Imai, 1998; Han et al, 2004; Hwang et al, 2005b; Toorani and Beheshti, 2009; Mohapatra, 2010; Singh, 2016), Nasreldin et al.'s (2015b) protocol allows message to be divided into small messages which is suitable for pipelining techniques
Nasreldin et al proposed a protocol for securing the digital evidence collection in cloud environments
Summary
Big data and cloud computing are hot topics that shape the future of both academia and industry. The amount of data generated through evidence acquisition is huge, complex and needs efficient analysis approaches in order to deal with its characteristics considering velocity and variety. Another problem could be raised while evidence collection, where the cloud administrator send the required data to the investigator. Zawoad et al (2015; 2016; Zawoad and Hasan, 2013) proposed solutions which are based on the identification of the desired properties to support trustworthy forensics in the cloud They proposed a Forensics Enabled Cloud (FECloud) architecture to maintain and afford required evidence. They do not solve the authenticity and integrity of evidence problem
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