A novel IoT sensor authentication using HaLo extraction method and memory chip variability
Tóm tắt
Since the inception of encrypted messages thousands of years ago, mathematicians and scientists have continued to improve encryption algorithms in order to create more secure means of communication. These improvements came by means of more complex encryption algorithms that have stronger security features such as larger keys and trusted third parties. While many new processors can handle these more complex encryption algorithms, IoT devices on the edge often struggle to keep up with resource intensive encryption standards. In order to meet this demand for lightweight, secure encryption on the edge, this paper proposes a novel solution, called the High and Low (HaLo) method, that generates Physical Unclonable Function (PUF) signatures based on process variations within flash memory. These PUF signatures can be used to uniquely identify and authenticate remote sensors, and help ensure that messages being sent from remote sensors are encrypted adequately without requiring computationally expensive methods. The HaLo method consumes 20x less power than conventional authentication schemes commonly used with IoT devices, it has an average latency of only 39ms for 512 bit signature generation, and the average error rate is below 0.06%. Due to its low latency, low error rate, and high power efficiency, the HaLo method can progress the field of IoT encryption standards by accurately and efficiently authenticating remote sensors without sacrificing encryption integrity.
Tài liệu tham khảo
Camara C, Peris-Lopez P, Tapiador JE. Security and privacy issues in implantable medical devices: a comprehensive survey. J Biomed Inf. 2015;55:272. https://doi.org/10.1016/j.jbi.2015.04.007.
Palve A, Patel H, Towards Securing Real time data in IoMT Environment, In: 2018 8th International Conference on Communication Systems and Network Technologies (CSNT) 2018;113–119. https://doi.org/10.1109/CSNT.2018.8820213
Fakroon M, Gebali F, Mamun M. Multifactor authentication scheme using physically unclonable functions. Internet Things. 2021;13:100343. https://doi.org/10.1016/j.iot.2020.100343.
Berghel H, Uecker J. WiFi attack vectors. Commun ACM. 2005;48:21. https://doi.org/10.1145/1076211.1076229.
Ling Z, Luo J, Xu Y, Gao C, Wu K, Fu X. Security vulnerabilities of internet of things: a case study of the smart plug system. IEEE Internet Things J. 2017;4(6):1899. https://doi.org/10.1109/JIOT.2017.2707465.
Gordon H, Edmonds J, Ghandali S, Yan W, Karimian N, Tehranipoor F. Flash-based security primitives: evolution, challenges and future directions. Cryptography. 2021;5:1. https://doi.org/10.3390/cryptography5010007.
Luo Y, Ghose S, Cai Y, Haratsch EF, Mutlu O. Improving 3D NAND flash memory lifetime by tolerating early retention loss and process variation. Proc ACM Measure Anal Comput Syst. 2018;2(3):1.
Xu SQ, Yu Wk, Suh GE, Kan EC, Understanding sources of variations in flash memory for physical unclonable functions, In: 2014 IEEE 6th International Memory Workshop (IMW) 2014;1–4. https://doi.org/10.1109/IMW.2014.6849385
D.E. Holcomb, W.P. Burleson, K. Fu, Initial SRAM state as a fingerprint and source of true random numbers for RFID tags, In: Proceedings of the Conference on RFID Security 2007;
Prabhu P, Akel A, Grupp LM, Wing-Kei SY, Suh GE, Kan E, Swanson S, Extracting device fingerprints from flash memory by exploiting physical variations, In: International Conference on Trust and Trustworthy Computing (Springer, 2011), 188–201
Wang Y, Yu Wk, Wu S, Malysa G, Suh GE, Kan EC. Flash memory for ubiquitous hardware security functions: True random number generation and device fingerprints, In 2012 IEEE Symposium on Security and Privacy (IEEE, 2012), pp. 33–47
Jia S, Xia L, Wang Z, Lin J, Zhang G, Ji Y, Extracting robust keys from nand flash physical unclonable functions, In: International Conference on Information Security (Springer, 2015), pp. 437–454
T.S. et al., High-temperature stable physical unclonable functions with error-free readout scheme based on 28nm SG-MONOS Flash Memory for Security Applications, (IEEE, 2017), pp. 1–4
Wu M, Yang T, Chen L, Lin C, Hu H, Su F, Wang C, Huang JP, Chen H, Lu CC, Yang EC, Shen RS. A PUF scheme using competing oxide rupture with bit error rate approaching zero, In: 2018 IEEE International Solid - State Circuits Conference - (ISSCC) (2018), pp. 130–132. https://doi.org/10.1109/ISSCC.2018.8310218
Clark LT, Adams J, Holbert KE. Reliable techniques for integrated circuit identification and true random number generation using 1.5-transistor flash memory. Integration. 2019;65:263.
Poudel BRP, Milenkovic A. Microcontroller TRNGs using perturbed states of NOR flash memory cells. IEEE Trans Comput. 2019;68:307–13.
Mahmoodi M, Nili H, Larimian S, Guo X, Strukov D, ChipSecure: A reconfigurable analog eFlash-based PUF with machine learning attack resiliency in 55nm CMOS, In: 2019 56th ACM/IEEE Design Automation Conference (DAC) 2019;1–6
Sakib S, Milenković A, Rahman MT, Ray B. An aging-resistant NAND flash memory physical unclonable function. IEEE Trans Electron Devices. 2020;67(3):937.
M.R.M. S. Larimian, D.B. Strukov, Lightweight integrated design of PUF and TRNG security primitives based on eFlash memory in 55-nm CMOS, (IEEE, 2020), 67:1586–1592
Nguyen TN, Park S, Shin D. Extraction of device fingerprints using built-in erase-suspend operation of flash memory devices. IEEE Access. 2020;8:98637. https://doi.org/10.1109/ACCESS.2020.2995891.