8-Bit Quantizer for Chaotic Generator With Reduced Hardware Complexity

8-Bit Quantizer for Chaotic Generator With Reduced Hardware Complexity

Zamarrud (Z.H.C.E.T, A.M.U, Aligarh, India) and Muhammed Izharuddin (Z.H.C.E.T, A.M.U, Aligarh, India)
Copyright: © 2018 |Pages: 16
DOI: 10.4018/IJRSDA.2018070104

Abstract

This article describes how nowadays, data is widely transmitted over the internet in the real time. Wherever the transmission or storage is required, security is needed. High speed processing hardware machine with reduced complexity are used for the security of the data, that are transmitted in real time. The information which is to be secure are encoded by pseudorandom key. Chaotic numbers are used in place of a pseudorandom key. The generated chaotic values are analogous in nature, these analog values are digitized to generate encryption key like 8-bit, 16-bit, 32-bit. To generate an 8-bit key, an 8-bit quantizer is required. The design of 8-bit quantizer requires 256 levels which needs lot of complex hardware to implement. In this article, an 8-bit quantizer is designed with reduced complexity, where hardware requirement is reduced by more than 12 times. Without compromising the randomness of the sequence generated. To increase the randomness and confusion timed hop random selection is used. The randomness of the sequence generated by the chaotic generators is analyzed by NIST test suite, to test for its randomness.
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Introduction

Due to the fast development of the internet usage, and the massive growth of media files, and transmission of these information over the internet in the real time makes the information security one of the major challenge in the cryptographic field. For the classified information, proper laws and rules for the security measures has therefore become vital. Information protection from unauthorized access is the major problem face by the present research (Chen & Zhao, 2012), (Shaikh & Haider, 2011). The information, whose security is essential, is encrypted by using pseudorandom sequences as keys. Many cryptographic algorithms were considered as effective, but today because of advancement in the computing power those algorithms are no longer deliberated as safe.

Random number are widely uses for the generation of cryptographic key for the data encryption in various areas such as communication channels, security of bank, etc. Random number also used in design of encoder and decoder in noisy communication channels for sending and receiving the data. As a main important component of the systems security, random number generators (RNGs) have greater extent positioned conspicuously in the researcher’s focal points. Random numbers are used in a widespread way in many operations related to cryptography; like in both symmetric and asymmetric algorithm for key generation; such as in protocols use in validation and verification, data structure padding, blinding values, and in channel side attacks. When random number generators are implemented on finite state machines then it is known as pseudo-random generators (PRNGs). And these Pseudo-random number generators are able to generate the sequence of numbers which is looks random like in many aspects. With the help of simple software routine, secure PRNGs can be implemented easily. The random number sequences generated by many pseudo-random number generators are not random actually, because of the finiteness of the set of numbers. Like, stringent batteries of tests are used to know that the generated sequence is predictable or not. For the highest system security, it is required to have a perfect randomly generated key, which is generated by PRNGs and these are suitable in the cryptographic application. Since the periodicity possessed by PRNGs, so the randomness are not very rigorous that are required in cryptographic application. And the periodicity can be calculated or predictable by mathematically. For the improvement of the quality of pseudo-random number generators Chaos theory play an important. The disordered behavior and unpredictability nature of the chaos number will give the advantage of using chaos in the field of cryptography. When the chaos synchronization is discovery increases the interest of using chaotic signals in the implementation of security system for secure communication channels. The nature of Chaos is not completely disorder, in the deterministic dynamic system the chaos is in disorder in nature and can be predicted easily. Cryptographic researchers use chaotic systems properties (Dutta et al. 2014), like sensitivity towards seed, aperiodicity and systems parameters, the non-predictive chaotic behavior results by any small disruption and can grow exponentially in the system. Chaos is not completely disordered, in deterministic dynamic system which is always predictive the chaos is disorder. Chaotic signals (Mishra & Mankar, 2011) are evolved from nonlinear dynamic systems, chaotic signals look random in time domains, and they are uncorrelated, deterministic and aperiodic. The chaotic number is used in placed of pseudorandom number for key generation (Mishra et al., 2015) for the security of the information in the real time. But the chaotic number that generate are analog in nature and its value lies between ‘0’ and ‘1.’ So, to digitize the analog chaotic number into 8-bit binary number, 8-bit quantizer is required. The design of 8-bit quantizer requires 256 levels that needs very complex hardware and also complex to implement.

In this work, to generate the 8-bit chaotic number 8-bit quantizer is designed with reduced complexity where hardware requirement is reduced by more than 12 times. Without comprising with the randomness of the sequence generated for that timed hop random selection is used.

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