EFFICIENT HARDWARE PRIMITIVES FOR SECURING LIGHTWEIGHT SYSTEMS

In the era of IoT and ubiquitous computing, the collection and communication of sensitive data is increasingly being handled by lightweight Integrated Circuits. Efficient hardware implementations of crytographic primitives for resource constrained applications have become critical, especially block ciphers which perform fundamental operations such as encryption, decryption, and even hashing. We study the efficiency of block ciphers under different implementation styles. For low latency applications that use unrolled block cipher implementations, we design a glitch filter to reduce energy consumption. For lightweight applications, we design a novel architecture for the widely used AES cipher. The design eliminates inefficiencies in data movement and clock activity, thereby significantly improving energy efficiency over state-of-the-art architectures. Apart from efficiency, vulnerability to implementation attacks are a concern, which we mitigate by our randomization capable lightweight AES architecture. We fabricate our designs in a commercial 16nm FinFET technology and present measured testchip data on energy consumption and side channel resistance. Finally, we address the problem of supply chain security by using image processing techniques to extract fingerprints from surface texture of plastic IC packages for IC authentication and counterfeit prevention. Collectively these works present efficient and cost effective solutions to secure lightweight systems

CURRENCY AUTHENTICATION USING MATLAB

Today the ubiquitous distribution of high technology scanning and printing equipment enables the "home" user to make counterfeits of high value documents like checks, tickets, licenses, identification cards and other secure documents. High value documents have been and will continue to be forged as long as the value realized from the counterfeiting is higher than the cost of duplicating the original. There are no perfect counterfeits, and there are no p erfect d esigns fully immune to counterfeiting. In the past, the hands of craftsman and a perfect eye were required to make a high quality counterfeit. Today, highly sophisticated, state-of-the-art reprographic systems do not require skilled professionals to operate them. They are widely available to the general public. These devices are generally simple to use and create an "opportunity" for the "home counterfeiter". It is becoming i ncreasingly difficult to spot alterations or counterfeits using only human sensory evaluation. There is an ever-increasing demand for new technologies and methods of counterfeit detection and forensic analysis to safeguard the integrity of high value documents. This is where process of authentication comes in. The aim of the project is to produce a reliable system that offers an easy and effective authentication technique of a currency. The objectives of Currency Authentication are to design a system that will be able to evaluate the integrity of currency contents relative to the original and of being able to detect, in an automatic way, malevolent currency modifications. For these purposes system software must be developed based on current available techniques and mechanisms

Digital watermarking and novel security devices

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Robust and Effective Banknote Recognition Model for Aiding Visual Impaired People

Visual disabled Ethiopians find great difficulty in recognizing banknotes. Each Ethiopian banknote has an identical feel, with no Braille markings, irregular edges, or other tangible features that make it easily recognizable by blind persons. In Ethiopia, there's only one device available that will assist blind people to acknowledge their notes. Internationally, there are devices available; however, they're expensive, complex, and haven't been developed to cater to Ethiopian currency. Because of these facts, visually impaired people may suffer from recognizing each folding money. This fact necessitates a higher authentication and verification system that will help visually disabled people to simply identify and recognize the banknotes. This paper presents a denomination-specific component-based framework for a banknote recognition system. Within the study, the dominant color of the banknotes was first identified and so the exclusive feature for every denomination-specific ROI was calculated. Finally, the Colour-Momentum, dominant color, and GLCM features were calculated from each denomination-specific ROI. Designing the recognition system by thereby considering the denomination-specific ROI is simpler as compared to considering the entire note in collecting more class-specific information and robust in copying with partial occlusion and viewpoint changes. The performance of the proposed model was verified by using a larger dataset of which containing banknotes in several conditions including occlusion, cluttered background, rotation, and changes of illumination, scaling, and viewpoints. The proposed algorithm achieves a 98% recognition rate on our challenging datasets

A Non-invasive Technique to Detect Authentic/Counterfeit SRAM Chips

Many commercially available memory chips are fabricated worldwide in untrusted facilities. Therefore, a counterfeit memory chip can easily enter into the supply chain in different formats. Deploying these counterfeit memory chips into an electronic system can severely affect security and reliability domains because of their sub-standard quality, poor performance, and shorter lifespan. Therefore, a proper solution is required to identify counterfeit memory chips before deploying them in mission-, safety-, and security-critical systems. However, a single solution to prevent counterfeiting is challenging due to the diversity of counterfeit types, sources, and refinement techniques. Besides, the chips can pass initial testing and still fail while being used in the system. Furthermore, existing solutions focus on detecting a single counterfeit type (e.g., detecting recycled memory chips). This work proposes a framework that detects major counterfeit static random-access memory (SRAM) types by attesting/identifying the origin of the manufacturer. The proposed technique generates a single signature for a manufacturer and does not require any exhaustive registration/authentication process. We validate our proposed technique using 345 SRAM chips produced by major manufacturers. The silicon results show that the test scores ($F_{1}$ score) of our proposed technique of identifying memory manufacturer and part-number are 93% and 71%, respectively.Comment: This manuscript has been submitted for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Multipoint Spectroscopy and Stereoscopic Imaging of Pharmaceutical Particles

Particle and granule properties play a key role in the final product quality of pharmaceuticals. Thus the identification and monitoring of key chemical and physical parameters is essential in the production of pharmaceuticals. The existing off-line methods are generally slow and labour intensive. Near infra-red (NIR) multipoint spectroscopy and image analysis are an attractive alternative compared to the traditional methods because they are both nondestructive and non-interfering allowing the analysis in real time of particles physical and chemical properties. This research is a preliminary study performed at laboratory scale and aims at developing chemometric and imaging algorithms for real time measuring of pharmaceutical chemical and physical properties. These algorithms utilised real time NIR multipoint spectroscopy and a novel imaging system. NIR multipoint spectroscopy followed by a regression technique (such as PLS) was used to build calibration models to quantify a compound in a small size binary granule mixture under both static and dynamic conditions. The imaging technology provided key physical properties such as size, shape and texture. The Haralick correlation property and the variogram were used to analyse the surface texture of particles. These algorithms allowed the classification of particles by their morphological nature under both static and dynamic conditions

The Journal of Undergraduate Research: Volume 06

This is the complete issue of the South Dakota State University Journal of Undergraduate Research, Volume 6

Non-invasive Techniques Towards Recovering Highly Secure Unclonable Cryptographic Keys and Detecting Counterfeit Memory Chips

Due to the ubiquitous presence of memory components in all electronic computing systems, memory-based signatures are considered low-cost alternatives to generate unique device identifiers (IDs) and cryptographic keys. On the one hand, this unique device ID can potentially be used to identify major types of device counterfeitings such as remarked, overproduced, and cloned. On the other hand, memory-based cryptographic keys are commercially used in many cryptographic applications such as securing software IP, encrypting key vault, anchoring device root of trust, and device authentication for could services. As memory components generate this signature in runtime rather than storing them in memory, an attacker cannot clone/copy the signature and reuse them in malicious activity. However, to ensure the desired level of security, signatures generated from two different memory chips should be completely random and uncorrelated from each other. Traditionally, memory-based signatures are considered unique and uncorrelated due to the random variation in the manufacturing process. Unfortunately, in previous studies, many deterministic components of the manufacturing process, such as memory architecture, layout, systematic process variation, device package, are ignored. This dissertation shows that these deterministic factors can significantly correlate two memory signatures if those two memory chips share the same manufacturing resources (i.e., manufacturing facility, specification set, design file, etc.). We demonstrate that this signature correlation can be used to detect major counterfeit types in a non-invasive and low-cost manner. Furthermore, we use this signature correlation as side-channel information to attack memory-based cryptographic keys. We validate our contribution by collecting data from several commercially available off-the-shelf (COTS) memory chips/modules and considering different usage-case scenarios