MeLPUF: Memory in Logic PUF

Physical Unclonable Functions (PUFs) are used for securing electronic designs across the implementation spectrum ranging from lightweight FPGA to server-class ASIC designs. However, current PUF implementations are vulnerable to model-building attacks; they often incur significant design overheads and are challenging to configure based on application-specific requirements. These factors limit their application, primarily in the case of the system on chip (SoC) designs used in diverse applications. In this work, we propose MeL-PUF - Memory-in-Logic PUF, a low-overhead, distributed, and synthesizable PUF that takes advantage of existing logic gates in a design and transforms them to create cross-coupled inverters (i.e. memory cells) controlled by a PUF control signal. The power-up states of these memory cells are used as the source of entropy in the proposed PUF architecture. These on-demand memory cells can be distributed across the combinational logic of various intellectual property (IP) blocks in a system on chip (SoC) design. They can also be synthesized with a standard logic synthesis tool to meet the area,power, or performance constraints of a design. By aggregating the power-up states from multiple such memory cells, we can create a PUF signature or digital fingerprint of varying size. We evaluate the MeL-PUF signature quality with both circuit-level simulations as well as with measurements in FPGA devices. We show that MeL-PUF provides high-quality signatures in terms of uniqueness, randomness, and robustness, without incurring large overheads. We also suggest additional optimizations that can be leveraged to improve the performance of MeL-PUF.Comment: 5 pages, 16 figure

Detecting Dye-Contaminated Vegetables Using Low-Field NMR Relaxometry

Dyeing vegetables with harmful compounds has become an alarming public health issue over the past few years. Excessive consumption of these dyed vegetables can cause severe health hazards, including cancer. Copper sulfate, malachite green, and Sudan red are some of the non-food-grade dyes widely used on vegetables by untrusted entities in the food supply chain to make them look fresh and vibrant. In this study, the presence and quantity of dye-based adulteration in vegetables are determined by applying 1H-nuclear magnetic resonance (NMR) relaxometry. The proposed technique was validated by treating some vegetables in-house with different dyes and then soaking them in various solvents. The resulting solutions were collected and analyzed using NMR relaxometry. Specifically, the effective transverse relaxation time constant, T2,eff, of each solution was estimated using a Carr–Purcell–Meiboom–Gill (CPMG) pulse sequence. Finally, the estimated time constants (i.e., measured signatures) were compared with a library of existing T2,eff data to detect and quantify the presence of unwanted dyes. The latter consists of data-driven models of transverse decay times for various concentrations of each water-soluble dye. The time required to analyze each sample using the proposed approach is dye-dependent but typically no longer than a few minutes. The analysis results can be used to generate warning flags if the detected dye concentrations violate widely accepted standards for food dyes. The proposed low-cost detection approach can be used in various stages of a produce supply chain, including consumer household