Physical Sciences and Mathematics Commons^™

Ethics And Bias In Machine Learning: A Technical Study Of What Makes Us “Good”, Ashley Nicole Shadowen

Student Theses

The topic of machine ethics is growing in recognition and energy, but bias in machine learning algorithms outpaces it to date. Bias is a complicated term with good and bad connotations in the field of algorithmic prediction making. Especially in circumstances with legal and ethical consequences, we must study the results of these machines to ensure fairness. This paper attempts to address ethics at the algorithmic level of autonomous machines. There is no one solution to solving machine bias, it depends on the context of the given system and the most reasonable way to avoid biased decisions while maintaining the …

Study Of Self-Similarity In Brain Data, Jennifer Holst

Student Theses

In the area of computer science, past research has found that the concept of self-similarity is present in local and Internet-based network traffic. This study considers the possibility that data traveling through the neuronal network in the human brain is also self-similar. By analyzing publicly available raw EEG data and estimating its Hurst parameter, we find indications that brain data traffic may in fact be self-similar.

Digital Anti-Forensics: An Implementation And Examination, Stephanie Dachs

Student Theses

The rise of computer use and technical adeptness by the general public in the last two decades are undeniable. With greater use comes a greater possibility for misuse, evidenced by today’s incredible number of crimes involving computers as well as the growth in severity from that of cyber hooliganism to cyber warfare. Although frequently utilized for privacy and security purposes, the vast range of anti-forensic techniques has contributed to the ability for hackers and criminals to obstruct computer forensic investigations.

Understanding how anti-forensics may alter important and relevant data on an electronic device will prove useful for the success and …