Document Type

Thesis

Degree

Master of Science (MS)

Major/Program

Computer Engineering

First Advisor's Name

Dr. A. Selcuk Uluagac

First Advisor's Committee Title

Committee chair

Second Advisor's Name

Dr. Alexander Perez-Pons

Second Advisor's Committee Title

committee member

Third Advisor's Name

Dr. Alex Afanasyev

Third Advisor's Committee Title

committee member

Fourth Advisor's Name

Dr. Engin Kirda

Fourth Advisor's Committee Title

committee member

Keywords

Blockchain, Cryptocurrency, Cryptojacking, IoT, IoT Security, Malware, Ransomware, Bitcoin

Date of Defense

11-3-2021

Abstract

Cryptojacking is an act of using a victim's computation power without his/her consent. Unauthorized mining costs extra electricity consumption and decreases the victim host's computational efficiency dramatically. In this thesis, we perform an extensive research on cryptojacking malware from every aspects. First, we present a systematic overview of cryptojacking malware based on the information obtained from the combination of academic research papers, two large cryptojacking datasets of samples, and numerous major attack instances. Second, we created a dataset of 6269 websites containing cryptomining scripts in their source codes to characterize the in-browser cryptomining ecosystem by differentiating permissioned and permissionless cryptomining samples. Third, we introduce an accurate and efficient IoT cryptojacking detection mechanism based on network traffic features that achieves an accuracy of 99%. Finally, we believe this thesis will greatly expand the scope of research and facilitate other novel solutions in the cryptojacking domain.

Identifier

FIDC010472

Previously Published In

Tekiner, Ege, et al. "SoK: Cryptojacking Malware." arXiv preprint arXiv:2103.03851 (2021).

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