title: Chaos-Based Simultaneous Compression and Encryption for Hadoop.
abstract: Data compression and encryption are key components of commonly deployed platforms such as Hadoop. Numerous data compression and encryption tools are presently available on such platforms and the tools are characteristically applied in sequence, i.e., compression followed by encryption or encryption followed by compression. This paper focuses on the open-source Hadoop framework and proposes a data storage method that efficiently couples data compression with encryption. A simultaneous compression and encryption scheme is introduced that addresses an important implementation issue of source coding based on Tent Map and Piece-wise Linear Chaotic Map (PWLM), which is the infinite precision of real numbers that result from their long products. The approach proposed here solves the implementation issue by removing fractional components that are generated by the long products of real numbers. Moreover, it incorporates a stealth key that performs a cyclic shift in PWLM without compromising compression capabilities. In addition, the proposed approach implements a masking pseudorandom keystream that enhances encryption quality. The proposed algorithm demonstrated a congruent fit within the Hadoop framework, providing robust encryption security and compression.
authors.affiliation: HPCC Service Center, Department of Computer & Information Sciences, Universiti Teknologi PETRONAS, Seri Iskandar, Tronoh, Perak, Malaysia.
authors.forename: Muhammad
authors.identifier: http://orcid.org/0000-0003-0153-1201
authors.initials: M
authors.lastname: Usama
authors.affiliation: HPCC Service Center, Department of Computer & Information Sciences, Universiti Teknologi PETRONAS, Seri Iskandar, Tronoh, Perak, Malaysia.
authors.forename: Nordin
authors.initials: N
authors.lastname: Zakaria
mesh_terms: D000465:Algorithms; D016494:Computer Security; D044962:Data Compression / Q000379:methods; D017711:Nonlinear Dynamics