Systems Architecture Commons^™

Privacy-Preserving Cloud-Assisted Data Analytics, Wei Bao

Graduate Theses and Dissertations

Nowadays industries are collecting a massive and exponentially growing amount of data that can be utilized to extract useful insights for improving various aspects of our life. Data analytics (e.g., via the use of machine learning) has been extensively applied to make important decisions in various real world applications. However, it is challenging for resource-limited clients to analyze their data in an efficient way when its scale is large. Additionally, the data resources are increasingly distributed among different owners. Nonetheless, users' data may contain private information that needs to be protected.

Cloud computing has become more and more popular in …

Brave New World Reboot: Technology’S Role In Consumer Manipulation And Implications For Privacy And Transparency, Allie Mertensotto

Marketing Undergraduate Honors Theses

Most consumers are aware that our data is being obtained and collected through the use of our devices we keep in our homes or even on our person throughout the day. But, it is understated how much data is being collected. Conversations you have with your peers – in a close proximity of a device – are being used to tailor advertising. The advertisements you receive on your devices are uniquely catered to your individual person, due to the fact it consistently uses our data to produce efficient and personal ads. On the flip side, our government is also tapping …

Characteristic Reassignment For Hardware Trojan Detection, Noah Waller

Graduate Theses and Dissertations

With the current business model and increasing complexity of hardware designs, third-party Intellectual Properties (IPs) are prevalently incorporated into first-party designs. However, the use of third-party IPs increases security concerns related to hardware Trojans inserted by attackers. A core threat posed by Hardware Trojans is the difficulty in detecting such malicious insertions/alternations in order to prevent the damage. This thesis work provides major improvements on a soft IP analysis methodology and tool known as the Structural Checking tool, which analyzes Register-Transfer Level (RTL) soft IPs for determining their functionalities and screening for hardware Trojans. This is done by breaking down …

Network-Based Detection And Prevention System Against Dns-Based Attacks, Yasir Faraj Mohammed

Graduate Theses and Dissertations

Individuals and organizations rely on the Internet as an essential environment for personal or business transactions. However, individuals and organizations have been primary targets for attacks that steal sensitive data. Adversaries can use different approaches to hide their activities inside the compromised network and communicate covertly between the malicious servers and the victims. The domain name system (DNS) protocol is one of these approaches that adversaries use to transfer stolen data outside the organization's network using various forms of DNS tunneling attacks. The main reason for targeting the DNS protocol is because DNS is available in almost every network, ignored, …

Development Of A Reference Design For Intrusion Detection Using Neural Networks For A Smart Inverter, Ammar Mohammad Khan

Graduate Theses and Dissertations

The purpose of this thesis is to develop a reference design for a base level implementation of an intrusion detection module using artificial neural networks that is deployed onto an inverter and runs on live data for cybersecurity purposes, leveraging the latest deep learning algorithms and tools. Cybersecurity in the smart grid industry focuses on maintaining optimal standards of security in the system and a key component of this is being able to detect cyberattacks. Although researchers and engineers aim to design such devices with embedded security, attacks can and do still occur. The foundation for eventually mitigating these attacks …