Engineering Commons^™

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 …

High-Performance Vlsi Architectures For Lattice-Based Cryptography, Weihang Tan

All Dissertations

Lattice-based cryptography is a cryptographic primitive built upon the hard problems on point lattices. Cryptosystems relying on lattice-based cryptography have attracted huge attention in the last decade since they have post-quantum-resistant security and the remarkable construction of the algorithm. In particular, homomorphic encryption (HE) and post-quantum cryptography (PQC) are the two main applications of lattice-based cryptography. Meanwhile, the efficient hardware implementations for these advanced cryptography schemes are demanding to achieve a high-performance implementation.

This dissertation aims to investigate the novel and high-performance very large-scale integration (VLSI) architectures for lattice-based cryptography, including the HE and PQC schemes. This dissertation first presents …

Integrating Visual Mnemonics And Input Feedback With Passphrases To Improve The Usability And Security Of Digital Authentication, Kevin Juang

All Dissertations

The need for both usable and secure authentication is more pronounced than ever before. Security researchers and professionals will need to have a deep understanding of human factors to address these issues. Due to their ubiquity, recoverability, and low barrier of entry, passwords remain the most common means of digital authentication. However, fundamental human nature dictates that it is exceedingly difficult for people to generate secure passwords on their own. System-generated random passwords can be secure but are often unusable, which is why most passwords are still created by humans. We developed a simple system for automatically generating mnemonic phrases …

A System-Generated Password And Mnemonic Approach To Optimize The Security And Usability Of Text-Based Passwords, Sanjaykumar Ranganayakulu

All Theses

In this study a novel password generation policy called the system-generated password and mnemonic was designed and implemented. The intent of this policy was to optimize both the security and usability of text-based passwords. After implementing the policy we evaluated its usability and compared it with three other existing policies: user-generated password, system-generated password and user-generated mnemonic for a system-generated password. In order to have a fair comparison among the policies we maintained a constant level of security of 30±2 entropy as dictated by NIST level 2 standards.
The study involved 64 participants, equally divided into four groups, 16 in …

Scalable Capability-Based Authorization For High-Performance Parallel File Systems, Nicholas Mills

All Theses

As the size and scale of supercomputers continues to increase at an
exponential rate the number of users on a given supercomputer will
only grow larger. A larger number of users on a supercomputer places a
greater importance on the strength of information security. Nowhere is
this requirement for security more apparent than the file system, as
users expect their data to be protected from accidental or deliberate
modification.
In spite of the ever-increasing demand for more secure file system
access the majority of parallel file systems do not implement a robust
security protocol for fear it will negatively impact …