Computer Engineering Commons^™

Trojan Detection Expansion Of Structural Checking, Zachary Chapman

Graduate Theses and Dissertations

With the growth of the integrated circuit (IC) market, there has also been a rise in demand for third-party soft intellectual properties (IPs). However, the growing use of such Ips makes it easier for adversaries to hide malicious code, like hardware Trojans, into these designs. Unlike software Trojan detection, hardware Trojan detection is still an active research area. One proposed approach to this problem is the Structural Checking tool, which can detect hardware Trojans using two methodologies. The first method is a matching process, which takes an unknown design and attempts to determine if it might contain a Trojan by …

Adversarial Deep Learning And Security With A Hardware Perspective, Joseph Clements

All Dissertations

Adversarial deep learning is the field of study which analyzes deep learning in the presence of adversarial entities. This entails understanding the capabilities, objectives, and attack scenarios available to the adversary to develop defensive mechanisms and avenues of robustness available to the benign parties. Understanding this facet of deep learning helps us improve the safety of the deep learning systems against external threats from adversaries. However, of equal importance, this perspective also helps the industry understand and respond to critical failures in the technology. The expectation of future success has driven significant interest in developing this technology broadly. Adversarial deep …

Structural Checking Tool Restructure And Matching Improvements, Derek Taylor

Graduate Theses and Dissertations

With the rising complexity and size of hardware designs, saving development time and cost by employing third-party intellectual property (IP) into various first-party designs has become a necessity. However, using third-party IPs introduces the risk of adding malicious behavior to the design, including hardware Trojans. Different from software Trojan detection, the detection of hardware Trojans in an efficient and cost-effective manner is an ongoing area of study and has significant complexities depending on the development stage where Trojan detection is leveraged. Therefore, this thesis research proposes improvements to various components of the soft IP analysis methodology utilized by the Structural …

An Fpga-Based Hardware Accelerator For The Digital Image Correlation Engine, Keaten Stokke

Graduate Theses and Dissertations

The work presented in this thesis was aimed at the development of a hardware accelerator for the Digital Image Correlation engine (DICe) and compare two methods of data access, USB and Ethernet. The original DICe software package was created by Sandia National Laboratories and is written in C++. The software runs on any typical workstation PC and performs image correlation on available frame data produced by a camera. When DICe is introduced to a high volume of frames, the correlation time is on the order of days. The time to process and analyze data with DICe becomes a concern when …

A Comprehensive And Modular Robotic Control Framework For Model-Less Control Law Development Using Reinforcement Learning For Soft Robotics, Charles Sullivan

Open Access Theses & Dissertations

Soft robotics is a growing field in robotics research. Heavily inspired by biological systems, these robots are made of softer, non-linear, materials such as elastomers and are actuated using several novel methods, from fluidic actuation channels to shape changing materials such as electro-active polymers. Highly non-linear materials make modeling difficult, and sensors are still an area of active research. These issues have rendered typical control and modeling techniques often inadequate for soft robotics. Reinforcement learning is a branch of machine learning that focuses on model-less control by mapping states to actions that maximize a specific reward signal. Reinforcement learning has …

Hardware Ip Classification Through Weighted Characteristics, Brendan Mcgeehan

Graduate Theses and Dissertations

Today’s business model for hardware designs frequently incorporates third-party Intellectual Property (IP) due to the many benefits it can bring to a company. For instance, outsourcing certain components of an overall design can reduce time-to-market by allowing each party to specialize and perfect a specific part of the overall design. However, allowing third-party involvement also increases the possibility of malicious attacks, such as hardware Trojan insertion. Trojan insertion is a particularly dangerous security threat because testing the functionality of an IP can often leave the Trojan undetected. Therefore, this thesis work provides an improvement on a Trojan detection method known …

Roborodentia Final Report, Trevor James Gesell, Zeph Colby Nord, Mitchell Tyler Myjak

Computer Engineering

The Senior Project consisted of competing in Roborodentia, a competition in which groups build robots to complete a particular task. This event took place at the Cal Poly Open House on Saturday, April 12th, 2018. For the competition, the robot was to collect Nerf balls from supply tubes raised approximately 7” from the board and shoot them into nets placed along the opposite side of the course. The design, manufacture, and testing of the robot began the first week of Cal Poly winter quarter and lasted until the day of the competition.

Oracle Guided Incremental Sat Solving To Reverse Engineer Camouflaged Circuits, Xiangyu Zhang

Masters Theses

This study comprises two tasks. The first is to implement gate-level circuit camouflage techniques. The second is to implement the Oracle-guided incremental de-camouflage algorithm and apply it to the camouflaged designs.

The circuit camouflage algorithms are implemented in Python, and the Oracle- guided incremental de-camouflage algorithm is implemented in C++. During this study, I evaluate the Oracle-guided de-camouflage tool (Solver, in short) performance by de-obfuscating the ISCAS-85 combinational benchmarks, which are camouflaged by the camouflage algorithms. The results show that Solver is able to efficiently de-obfuscate the ISCAS-85 benchmarks regardless of camouflaging style, and is able to do so 10.5x …

Solid State Drive, Shaun A. Steele

Electrical Engineering

This project documents the design and implementation of a solid state drive (SSD). SSDs are a non-volatile memory storage device that competes with hard disk drives. SSDs rely on flash memory, a type of non-volatile memory that is electrically erased and programmed. The appeal of SSDs lies in the fact that they allow a fast, reliable, and durable memory storage device. The goal of this project is to have a working external SSD built from scratch.

Roborodentia Robot, Jordan Dykstra, Anibal Hernandez, Robert Prosser

Computer Engineering

This report provides details on the design and implementation of a robot for the Spring 2015 Roborodentia competition. The system is described from a software perspective, a hardware perspective, and a mechanical design perspective.

Spirit: A Home Automation System, Andrew Choi

Computer Engineering

Spirit is a multi device home automation system. Designed and implemented for California Polytechnic State University’s Senior Project program, this project was worked on during the duration of two school quarters from January 7, 2014 to June 13, 2014. The system consists of monitor/controllers designed to carry out everyday tasks in the average American household and an accompanying mobile application designed to receive information and control the devices. The monitor/controllers, or “Spirits”, are primarily developed using Arduino development tools and Arduino microcontroller boards. The spirits include a thermostat, named Tempus, an electrical outlet, Electrus, and a wall light switch, Luxos.

Investigation Of The Divcon Neuron To Increase The Performance Of A Traditional Feed Forward Multi-Layer Perceptron And Its Hardware Implementation, Jovan Saenz

Open Access Theses & Dissertations

ABSTRACT

Artificial Neural Networks (ANNs) have been developed in an attempt to emulate the information processing capabilities of the biological brain. They offer an alternate computing approach to problems in which mathematical modeling is complicated, such as pattern recognition and pattern classification.

Since ANNs were proposed in the early 1940s, there has been a great amount of research effort dedicated to the development of new models that improve performance. Consequently, different architectures, a variety of activation functions, and distinct learning algorithms have been developed and implemented in different disciplines such as medicine, engineering, and science. In addition, ANNs have been …

On Co-Optimization Of Constrained Satisfiability Problems For Hardware Software Applications, Kunal Ganeshpure

Doctoral Dissertations 1896 - February 2014

Manufacturing technology has permitted an exponential growth in transistor count and density. However, making efficient use of the available transistors in the design has become exceedingly difficult. Standard design flow involves synthesis, verification, placement and routing followed by final tape out of the design. Due to the presence of various undesirable effects like capacitive crosstalk, supply noise, high temperatures, etc., verification/validation of the design has become a challenging problem. Therefore, having a good design convergence may not be possible within the target time, due to a need for a large number of design iterations.

Capacitive crosstalk is one of the …

Reconode: Towards An Autonomous Multi-Robot Team Agent For Usar, Kang Li

Electronic Theses and Dissertations

Urban search and rescue (USAR) robots can benefit from small size as it facilitates movement in cramped quarters. Yet, small size limits actuator power, sensor payloads, computational capacity and battery life. We are alleviating these issues by developing the hardware and software infrastructure for high performance, heterogeneous, dynamically-reconfigurable miniature USAR robots, as well as a host of other relevant applications. In this thesis, a generic modular embedded system architecture based on the RecoNode multiprocessor is proposed, which consists of a set of hardware and software modules that can be configured to construct various types of robot systems for dynamic and …