Date of Award
2018
Publisher
North Dakota State University
Document Type
Dissertation
Degree Awarded
Doctor of Philosophy (PhD)
Department
Computer Science
College
Engineering
Faculty Advisor
Nygard, Kendall
Description
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 cloud-service 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 growth-function-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.
Recommended Citation
Chowdhury, Md. Minhaz, "Deception in Cyberspace: Con-Man Attack in Cloud Services" (2018). Computer Science. 365.
https://digitalcommons.ndsu.edu/computer-sci/365
Rights
NDSU Policy 190.6.2
Rights Link
https://www.ndsu.edu/fileadmin/policy/190.pdf
Handle Identifier
https://hdl.handle.net/10365/28761