Biswajit Ray

Habib Ur Rahman, Tharini Suresh, Sudeep Pasricha et al.

This paper presents MCFlash, a practical and immediately deployable technique for executing bulk bitwise operations directly within commercial off-the-shelf(COTS) 3D NAND flash chips. MCFlash relies solely on standard user-mode instructions, combining Multi-Level Cell (MLC) data encodings with dynamically tuned read reference voltages to execute in-place bitwise operations. We evaluate MCFlash across diverse NAND flash chips, both floating-gate and charge-trap variants, from different generations. Our results represent the first demonstration of error-free, on-chip bitwise operations, sustaining over one billion operations on fresh blocks and maintaining bit-error rates below 0.015% even after 10,000 program/erase (P/E) cycles.

B. M. S. Bahar Talukder, Vineetha Menon, Biswajit Ray et al.

Due to the globalization in the semiconductor supply chain, counterfeit dynamic random-access memory (DRAM) chips/modules have been spreading worldwide at an alarming rate. Deploying counterfeit DRAM modules into an electronic system can have severe consequences on security and reliability domains because of their sub-standard quality, poor performance, and shorter life span. Besides, studies suggest that a counterfeit DRAM can be more vulnerable to sophisticated attacks. However, detecting counterfeit DRAMs is very challenging because of their nature and ability to pass the initial testing. In this paper, we propose a technique to identify the DRAM origin (i.e., the origin of the manufacturer and the specification of individual DRAM) to detect and prevent counterfeit DRAM modules. A silicon evaluation shows that the proposed method reliably identifies off-the-shelf DRAM modules from three major manufacturers.

B. M. S. Bahar Talukder, Biswajit Ray, Domenic Forte et al.

Physically Unclonable Functions (PUFs) are potential security blocks to generate unique and more secure keys in low-cost cryptographic applications. Dynamic random-access memory (DRAM) has been proposed as one of the promising candidates for generating robust keys. Unfortunately, the existing techniques of generating device signatures from DRAM is very slow, destructive (destroy the current data), and disruptive to system operation. In this paper, we propose \textit{precharge} latency-based PUF (PreLatPUF) that exploits DRAM \textit{precharge} latency variations to generate signatures. The proposed PreLatPUF is fast, robust, least disruptive, and non-destructive. The silicon results from commercially available $DDR3$ chips from different manufacturers show that the proposed key generation technique is at least $ \sim 1,192X$ faster than the existing approaches, while reliably reproducing the key in extreme operating conditions.

B. M. S. Bahar Talukder, Joseph Kerns, Biswajit Ray et al.

True random number generator (TRNG) plays a vital role in a variety of security applications and protocols. The security and privacy of an asset rely on the encryption, which solely depends on the quality of random numbers. Memory chips are widely used for generating random numbers because of their prevalence in modern electronic systems. Unfortunately, existing Dynamic Random-access Memory (DRAM)-based TRNGs produce random numbers with either limited entropy or poor throughput. In this paper, we propose a DRAM-latency based TRNG that generates high-quality random numbers. The silicon results from Samsung and Micron DDR3 DRAM modules show that our proposed DRAM-latency based TRNG is robust (against different operating conditions and environmental variations) and acceptably fast.