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Hardware security is one of the most researched areas in the field of security. It focuses on discovering and understanding attacks and countermeasures for electronic hardware that provides the "root-of-trust" for modern computing systems upon which the software stack is built. The increasing reliance on electronic devices in our everyday life has also escalated the risks of experiencing security threats on these technologies. Students today are exposed to these devices and thus require a hands-on learning experience to be aware of the threats, solutions, and future research challenges in hardware security. Currently, there are limited opportunities for students to learn and understand hardware security. A significant factor limiting exposure to these topics is the lack of an accessible, low-cost, flexible, and ready-made platform for training students on the innards of a computing system and the spectrum of security issues/solutions at the hardware-level. In this paper, we introduce the motivation and efforts behind a course named "Hands-on Hardware Security." The Department of Electrical and Computer Engineering at the University of Florida has been offering this course for the past three years in providing experiential learning of hardware security through a set of well-designed experiments performed on a custom hardware module. We also present, in detail, the idea of a custom-designed, easy-to-understand, flexible hardware module with fundamental building blocks that can emulate a computer system and create a network of connected devices. We refer to the module as "HaHa SEP" (Hardware Hacking Security Education Platform), and it encourages students to learn and exercise "ethical hacking," a critical concept in the hardware security field. It is the first and only known lab course offered online, where students can perform ethical hacking of a computing system using a dedicated hardware module. This paper also provides a brief introduction to the experiments performed using this module, highlighting their significance in the field of Hardware Security. Finally, it concludes with a compilation of course evaluation survey results discussing the success of this course in engaging students' interest in the subject matter and determining the accomplishment of maintaining a balance between their expectation and the effort required towards the course.

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/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 .

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.

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