Using Unstable SRAM Bits for Physical Unclonable Function Applications on OffTheShelf SRAM Physical Unclonable Function (PUF) is recently used in modern electronic systems for device authentication and secret key generation. SRAM PUF is a popular memorybased PUF because it is a standard component for most electronic devices. Previously only strongly stable RAM bits are selected as PUF bits in order to achieve high reliability, hence requiring relatively large SRAM. Furthermore, SRAM PUF might suffer from PUF clone attack for using stable bits. Attackers may use Photon Emission Analysis (PEA) to observe the behavior of the stable bits and conducted Focused Ion Beam circuit edit (FIBCE) to produce an identical physical response. In this paper, we propose a new method that employs unstable bits as PUF bits in addition to the stable bits to increase the SRAM bit usage rate. We also show that this method can efficiently resist the PUF clone attack. Experimental results show that even though our proposed method uses unstable bits as PUF bits, it can still achieve high reliability. It can reach an average 2% intraHD without Error Correction Code (ECC) under various conditions and an average interHD of 49.33%.

Weak and Strong SRAM cells analysis in embedded memories for PUF applications The deployment of IoT platforms for SmartCity applications is demanding solutions to assure security and integrity levels. In this context, physical unclonable functions (PUF) may overcome the security drawbacks of storing the security key in a nonvolatile memory. The existence of SRAM in embedded systems has driven the implementation of PUF solutions using memory circuit as entropy sources. The use of a nonspecific memory design requires the need of identify the adequate cells useful for PUF applications. This work proposes a new methodology to distinguish the adequate cells based on mismatch factor calculation. The mismatch analysis using physical and performance parameters shows the viability of the selection methodology and computes the robustness of the responses in terms of probability of error in the startup value.