Engineering Commons^™

Challenges In Large-Scale Machine Learning Systems: Security And Correctness, Emad Alsuwat

Theses and Dissertations

In this research, we address the impact of data integrity on machine learning algorithms. We study how an adversary could corrupt Bayesian network structure learning algorithms by inserting contaminated data items. We investigate the resilience of two commonly used Bayesian network structure learning algorithms, namely the PC and LCD algorithms, against data poisoning attacks that aim to corrupt the learned Bayesian network model.

Data poisoning attacks are one of the most important emerging security threats against machine learning systems. These attacks aim to corrupt machine learning models by con- taminating datasets in the training phase. The lack of resilience of …

On The Security And Quality Of Wireless Communications In Outdoor Mobile Environment, Sharaf J. Malebary

Theses and Dissertations

The rapid advancement in wireless technology along with their low cost and ease of deployment have been attracting researchers academically and commercially. Researchers from private and public sectors are investing into enhancing the reliability, robustness, and security of radio frequency (RF) communications to accommodate the demand and enhance lifestyle. RF base communications -by nature- are slower and more exposed to attacks than a wired base (LAN). Deploying such networks in various cutting-edge mobile platforms (e.g. VANET, IoT, Autonomous robots) adds new challenges that impact the quality directly. Moreover, adopting such networks in public outdoor areas make them vulnerable to various …

Social Engineering Knowledge Measured As A Security Countermeasure, Christopher Artejus Sanders

Theses and Dissertations

Social Engineering has become a significant threat to the security of business, government, and academic institutions. As vulnerabilities to social engineering attacks increase, organizations must incorporate risk mitigation strategies to their portfolios of Information Systems Security Countermeasures (ISSC). The goal is to implement mitigation strategies that balance the cost of implementation, the privacy of employees, and the resulting expected costs of social engineering attacks. In this paper we develop an analytical model that calculates the total cost of protection, including the trade-off between the cost of implementing protection strategies and the resulting expected cost of social engineering attacks. We use …