Overview of PUF-based hardware security solutions for the internet of things

Abstract

The Internet of Things (IoT) consists of numerous interconnected resource-constrained devices such as sensors nodes and actuators, which are linked to the Internet. By 2020 it is anticipated that the IoT paradigm will include approximately 20 billion connected devices. The interconnection of such devices provides the ability to collect a huge amount of data for processing and analysis. A significant portion of the transacted data between IoT devices is private information, which must not in any way be eavesdropped on or tampered with. Security in IoT devices is therefore of paramount importance for further development of the technology. Such devices typically have limited area and energy resources, which makes the use of classic cryptography prohibitively expensive. Physically Unclonable Functions (PUFs) are a class of novel hardware security primitives that promise a paradigm shift in many security applications; their relatively simple architecture can answer many of the security challenges of energy-constrained IoT devices. In this paper, we discuss the design challenges of secure IoT systems; then we explain the principles of PUFs; finally we discuss the outstanding reliability and security problems of PUF technology and outline the open research questions in this field.

ARMOR: An Anti-Counterfeit Security Mechanism for Low Cost Radio Frequency Identification Systems

“…PUF is an integrated circuit which produces different outputs when it is implemented on different chips [15]. Manufacturing variability which causes the variation in the property of circuits is inevitable and uncontrollable, which serves PUF unclonability property.…”

“…The UID (uid) is always transmitted securely using Rabin encryption. Even when the uid is compromised, it is not possible to identify the tag from the encrypted message C because the plaintext M is padded with a random number as shown in Equation (15) and encrypted using the public key provided by the reader.…”

Defense Mechanisms against Machine Learning Modeling Attacks on Strong Physical Unclonable Functions for IOT Authentication: A Review

“…There are two sequential steps to accomplish authentication scheme for devices using PUF [4] as described below:…”

“…All the defense mechanisms resist or at least improve the resiliency of the PUFs against the ML-MA however they come with some shortcomings. In the case of design-based defense mechanisms, adding non-linearity using XOR [6], [7], analogizing the digital components [11] and exploiting the FPGA blocks [4], [10] increase the hardware overhead.…”

“…The success of the above authentication scheme relies on the fact that the verifier must collect many CRPs during the enrolment stage so that the CRPs will not run out as emphasized by Halak et al [4]. According to Maes [18], the PUF responses must reproduced within smaller intra distance to ensure that the replied response matches the stored response in the DB without possibility being predicted.…”