DECEPTION IN CYBERSPACE: CON-MAN ATTACK IN ...
DECEPTION IN CYBERSPACE: CON-MAN ATTACK IN CLOUD SERVICES
A Dissertation Submitted to the Graduate Faculty
of the North Dakota State University of Agriculture and Applied Science
By Md. Minhaz Chowdhury
In Partial Fulfillment of the Requirements for the Degree of
DOCTOR OF PHILOSOPHY
Major Department: Computer Science
June 2018
Fargo, North Dakota
North Dakota State University
Graduate School
Title
DECEPTION IN CYBERSPACE: CON-MAN ATTACK IN CLOUD SERVICES
By
MD. MINHAZ CHOWDHURY
The Supervisory Committee certifies that this disquisition complies with North Dakota State University's regulations and meets the accepted standards for the degree of
DOCTOR OF PHILOSOPHY
SUPERVISORY COMMITTEE:
Dr. Kendall E. Nygard
Chair
Dr. Saeed Salem Dr. Oksana Myronovych Dr. Jacob Glower
Approved:
6/22/2018
Date
Dr. Kendall E. Nygard
Department Chair
ABSTRACT A con-man deception appears in services from cyberspace, e.g., in cloud services. A cloud-service provider deceives by repeatedly providing less service than promised and deliberately avoids service monitoring. Such a repeated shortfall is beneficial for the cloudservice provider but victimizes the service's legitimate consumers. This deception is called a con-man deception. A con-man-resistant trust algorithm is used as a proactive measure against such deception, reducing the deception's severity on the victim's end. This trust algorithm detects a con-man deception by evaluating a cloud service's expected versus actual behavior. This detection application reveals the con-man-resistant trust algorithm's previously veiled properties. With this dissertation, a study of these properties reveals some necessary enhancements for this algorithm. The previous con-man-resistant trust-algorithm applications only considered the pattern of service-shortfall repetition. However, for cloud applications, the service-shortfall magnitude at each repetition is also important. Hence, an exponential growthfunction-based extension of this algorithm is proposed and implemented. The algorithm's initial parameter configuration has a significant influence on the con-deception detection pace. Some consumers tolerate intense repetition of service shortfall, and some consumers can tolerate mild repetition. Hence, the deception-detection pace has a correlation with the consumer's perspective. A machine-learning extension of the con-man-resistant trust algorithm can ascertain a consumer's perspective by analyzing that consumer's historical usage of the same cloud service. The result of this learning is a parameter configuration that reflects the consumer's perspective. The loss associated with a con deception is significant on the consumer's side. Hence, the work presented in this dissertation contributes to cybersecurity by attempting to minimize such deception in cyberspace.
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ACKNOWLEDGEMENTS I would, first, like to thank my immediate family members, my parents, my brother, and my sisters, for supporting me while I pursued this degree. I would also like to thank Dr. Kendall E. Nygard for his support and advice while completing my research. In 2009, I started my M.S. under Dr. Nygard as a graduate research assistant. In 2012, I went to the software industry and completed my M.S. degree in 2013. At the end of 2013, I enrolled as a part-time Ph.D. student with Dr. Nygard as my academic adviser. In 2015, I left the software industry and became a full-time student. Dr. Nygard helped me arrange an assistantship for my Ph.D. program. His involvement with cybersecurity motivated me to continue research in cybersecurity, and as result, my Ph.D. dissertation topic falls under the cybersecurity umbrella. I would also like to thank my dissertation committee's members: Dr. Saeed Salem, Dr. Oksana Myronovych, and Dr. Jacob Glower. Finally, I would like to thank the Computer Science Department at North Dakota State University and Joseph Latimer for providing the funding for my graduate study.
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DEDICATION When I was very young, I listened to the villagers' stories about my grandfather. Some of the stories are local tales now. I used to read his books about the physics of "light" from the early 1900s and felt wonder at his chemistry lab. I was born about 100 years after him. I went to the
same high school that he did, except that the timeline was about 100 years apart. His B.S. degree and my Ph.D. degree awarding time are also a little more than 100 years apart. His legends motivated me to come to the USA, to know the USA's industry culture, and to achieve
a Ph.D. This doctoral disquisition is dedicated to my grandfather, the late Alfazuddin Chowdhury, and
my grandmother, the late Mehrun Nissa Chowdhury.
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