The Generation of Random Numbers Using the Quantum Tunnel Effect in Transistors

This paper proposes a random number generator based on the quantum tunnel effect that takes place in transistors. The main system is divided into two basic components: the entropy source and the postprocessing block. The quantum tunnel effect is subjected to a random character, which means that electrons have a probability to pass through the potential barrier of the transistor. Theoretically, the measurable output current of the transistor should have a random variance in a predetermined interval, that results into a random sequence. Afterwards, the postprocessing block extracts the bias from the generated array. It is implemented through a hash function which employs the Toeplitz matrix, resulting into a true random sequence. This paper accounts the preliminary stages of development of an original random number generator. The focus was the physical phenomena, the tunnel effect in transistors, and the study of its probability with respect to the device parameters. In terms of postprocessing the main regard was choosing the adequate extraction method for the quantum entropy source. The novelty of the paper is represented by using the tunnel FET as an entropy source and finding a suitable postprocessing model for a higher generation rate.

[1]  Imad Fakhri Taha Alshaikhli,et al.  Broad View of Cryptographic Hash Functions , 2013 .

[2]  Koen De Bosschere,et al.  XOR-based hash functions , 2005, IEEE Transactions on Computers.

[3]  Olivier Chevassut,et al.  Key Derivation and Randomness Extraction , 2005, IACR Cryptol. ePrint Arch..

[4]  Y. Peres.  Iterating Von Neumann's Procedure for Extracting Random Bits , 1992 .

[5]  Ronen Shaltiel,et al.  An Introduction to Randomness Extractors , 2011, ICALP.

[6]  Manisha Pattanaik,et al.  Design and Analysis of Tunnel FET for Low Power High Performance Applications , 2018 .

[7]  Turgay Kaya,et al.  True Random Number Generation from Bioelectrical and Physical Signals , 2018, Comput. Math. Methods Medicine.

[8]  A. Pan.  Physics and Modeling of Tunneling in Low Power Transistors , 2015 .

[9]  S. M. Sze,et al.  Physics of semiconductor devices , 1969 .

[10]  Benjamin J. Eggleton,et al.  Quantum random number generation using spontaneous raman scattering , 2014, 2014 Conference on Lasers and Electro-Optics (CLEO) - Laser Science to Photonic Applications.

[11]  Katherine Boucart,et al.  Simulation of Double-Gate Silicon Tunnel FETs with a High-k Gate Dielectric , 2010 .

[12]  Larry Carter,et al.  Universal Classes of Hash Functions , 1979, J. Comput. Syst. Sci..

[13]  M. Razavy,et al.  Quantum Theory of Tunneling , 2003 .

[14]  John Kelsey,et al.  Recommendation for the Entropy Sources Used for Random Bit Generation , 2018 .

[15]  Haihan Zhou,et al.  Quantum random number generator based on quantum tunneling effect , 2017, 1711.01752.

[16]  D. Kucerovský,et al.  On some properties of Toeplitz matrices , 2016 .

[17]  Markus Rohe,et al.  Obtaining True-Random Binary Numbers from a Weak Radioactive Source , 2005, ICCSA.

[18]  G. Geetha,et al.  Cryptographic Hash Functions: A Review , 2012 .

[19]  He Xu,et al.  Postprocessing for quantum random number generators: entropy evaluation and randomness extraction , 2012, ArXiv.

[20]  Generation of True Random Numbers based on Radioactive Decay , 2017 .

[21]  Nanjian Wu,et al.  An ultra-low power CMOS random number generator , 2008 .

[22]  Hao Liang,et al.  Fully integrated 3.2 Gbps quantum random number generator with real-time extraction , 2016, ArXiv.

[23]  Design and Analysis of High Frequency InN Tunnel Transistors , 2013, 1401.0024.

[24]  Zhu Cao,et al.  Quantum random number generation , 2015, npj Quantum Information.

[25]  Ibrahim Ethem Bagci,et al.  Extracting random numbers from quantum tunnelling through a single diode , 2017, Scientific Reports.

[26]  Xiongfeng Ma,et al.  Ultrafast quantum random number generation based on quantum phase fluctuations. , 2011, Optics express.