Abstract
Rapid developments in the field of cryptography and hardware security have increased the need for random number generators which are not only of low-complexity but are also secure to the point of being undeterminable. A random number generator is a part of most security systems, so it should be simple and area efficient. Many modern-day pseudorandom number generators (PRNGs) make use of linear feedback shift registers (LFSRs). Though these PRNGs are of low complexity, they fall short when it comes to being secure since they are not truly random in nature. Thus, in this chapter we propose a random seeding LFSR-based truly random number generator (TRNG) which is not only of low complexity, like the aforementioned PRNGs, but is also ‘truly random’ in nature. Our proposed design generates an n-bit truly random number sequence that can be used for a variety of hardware security based applications. Based on our proposed n-bit TRNG design, we illustrate an example which generates 16-bit truly random sequences, and a detailed analysis is shown based on National Institute of Standards and Technology (NIST) tests to highlight its randomness.
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References
Maiti, Abhranil, Raghunandan Nagesh, Anand Reddy and Patrick Schaumont. 2009. Physical Unclonable Function and True Random Number Generator: a Compact and Scalable implementation. In The 19th ACM great lakes symposium on VLSI, May 2009.
Reddy D.M., K.P. Akshay, R. Giridhar, S.D. Karan and N. Mohankumar 2017. BHARKS: Built-in Hardware Authentication using Random Key Sequence. In 4th International Conference on Signal Processing, Computing and Control (ISPCC), Solan 2017, on pp. 200–204. https://doi.org/10.1109/ISPCC.2017.8269675.
Karunakaran D.K., and N. Mohankumar 2014. Malicious combinational hardware trojan detection by gate level characterization in 90 nm technology. In 5th International conference on computing, communication and networking technologies (ICCCNT), China. pp. 1–7. https://doi.org/10.1109/ICCCNT.2014.6963036.
Koneru V.R.R., B.K. Teja, K.D.B. Reddy, M.V. GnanaSwaroop, B. Ramanidharan and N. Mohankumar 2017. HAPMAD: Hardware based authentication platform for malicious activity detection in digital circuits. In Information System Design and Intelligent Applications, Advances in Intelligent Systems and Computing, vol 672. Springer, Singapore. https://doi.org/10.1007/978-981-10-7512-4_60.
Aishwarya G., S. Hitha Revalla, S. Shruthi, V.P. Ananth and N. Mohankumar. 2017. Virtual instrumentation based malicious circuit detection using weighted average voting. In International conference on micro-electronics, electromagnetics and telecommunications (ICMEET-2017), India.
Bharath R., et al. 2015. Malicious circuit detection for improved hardware security. In: Security in computing and communications (SSCC’15), Communications in Computer and Information Science, vol 536. https://doi.org/10.1007/978-3-319-22915-7_42.
Kamala Nandhini S., Vallinayagam S., Harshitha H., Chandra Shekhar Azad V., Mohankumar N. 2018. Delay-based reference free hardware trojan detection using virtual intelligence. In Information system design and intelligent applications, Advances in Intelligent Systems and Computing, vol 672. https://doi.org/10.1007/978-981-10-7512-4_50.
Blum, Lenore and Milke Shub. 1986. A simple unpredictable pseudo random number generator. SIAM Journal on Computing.
Zalivako S.S., and Ivanuik A.A. The use of physical unclonable functions for true random number sequences generation.
Gupta, Sanjay Janusz Rajski, Jerzy Tyszer. 1996. Arithmetic additive generators of pseudo-exhaustive test patterns. IEEE Transactions on Computers 45 (8): 939–949.
Srinivasan, R., S.K. Gupta, and M.A. Breuer. 2000. Novel test pattern generators for pseudoexhaustive testing. IEEE Transactions on Computer 49 (11): 1228–1240.
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Shiva Prasad, R., Siripagada, A., Selvaraj, S., Mohankumar, N. (2019). Random Seeding LFSR-Based TRNG for Hardware Security Applications. In: Krishna, A., Srikantaiah, K., Naveena, C. (eds) Integrated Intelligent Computing, Communication and Security. Studies in Computational Intelligence, vol 771. Springer, Singapore. https://doi.org/10.1007/978-981-10-8797-4_44
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DOI: https://doi.org/10.1007/978-981-10-8797-4_44
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