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Description
Third-party mixers are used to heighten the anonymity of Bitcoin users. The mixing techniques implemented by these tools are often untraceable on the blockchain, making them appealing to money launderers. This research aims to analyze mixers currently available on the deep web. In addition, an in-depth case study is done

Third-party mixers are used to heighten the anonymity of Bitcoin users. The mixing techniques implemented by these tools are often untraceable on the blockchain, making them appealing to money launderers. This research aims to analyze mixers currently available on the deep web. In addition, an in-depth case study is done on an open-source bitcoin mixer known as Penguin Mixer. A local version of Penguin Mixer was used to visualize mixer behavior under specific scenarios. This study could lead to the identification of vulnerabilities in mixing tools and detection of these tools on the blockchain.
ContributorsPakki, Jaswant (Author) / Doupe, Adam (Thesis director) / Shoshitaishvili, Yan (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
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Description
Despite the more tightly controlled permissions and Java framework used by most programs in the Android operating system, an attacker can use the same classic vulnerabilities that exist for traditional Linux binaries on the programs in the Android operating system. Some classic vulnerabilities include stack overows, string formats, and hea

Despite the more tightly controlled permissions and Java framework used by most programs in the Android operating system, an attacker can use the same classic vulnerabilities that exist for traditional Linux binaries on the programs in the Android operating system. Some classic vulnerabilities include stack overows, string formats, and heap meta-information corruption. Through the exploitation of these vulnerabilities an attacker can hijack the execution ow of an application. After hijacking the execution ow, an attacker can then violate the con_dentiality, integrity, or availability of the operating system. Over the years, the operating systems and compliers have implemented a number of protections to prevent the exploitation of vulnerable programs. The most widely implemented protections include Non-eXecutable stack (NX Stack), Address Space Layout Randomization (ASLR), and Stack Canaries (Canaries). NX Stack protections prevent the injection and execution of arbitrary code through the use of a permissions framework within a program. Whereas, ASLR and Canaries rely on obfuscation techniques to protect control ow, which requires su_cient entropy between each execution. Early in the implementation of these protections in Linux, researchers discovered that without su_cient entropy between executions, ASLR and Canaries were easily bypassed. For example, the obfuscation techniques were useless in programs that ran continuously because the programs did not change the canaries or re-randomize the address space. Similarly, aws in the implementation of ASLR and Canaries in Android only re-randomizes the values after rebooting, which means the address space locations and canary values remain constant across the executions of an Android program. As a result, an attacker can hijack the control ow Android binaries that contain control ow vulnerabilities. The purpose of this paper is to expose these aws and the methodology used to verify their existence in Android versions 4.1 (Jelly Bean) through 8.0 (Oreo).
ContributorsGibbs, Wil (Author) / Doupe, Adam (Thesis director) / Shoshitaishvili, Yan (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2018-12
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Description
Smartphone privacy is a growing concern around the world; smartphone applications routinely take personal information from our phones and monetize it for their own profit. Worse, they're doing it legally. The Terms of Service allow companies to use this information to market, promote, and sell personal data. Most users seem

Smartphone privacy is a growing concern around the world; smartphone applications routinely take personal information from our phones and monetize it for their own profit. Worse, they're doing it legally. The Terms of Service allow companies to use this information to market, promote, and sell personal data. Most users seem to be either unaware of it, or unconcerned by it. This has negative implications for the future of privacy, particularly as the idea of smart home technology becomes a reality. If this is what privacy looks like now, with only one major type of smart device on the market, what will the future hold, when the smart home systems come into play. In order to examine this question, I investigated how much awareness/knowledge smartphone users of a specific demographic (millennials aged 18-25) knew about their smartphone's data and where it goes. I wanted three questions answered: - For what purposes do millennials use their smartphones? - What do they know about smartphone privacy and security? - How will this affect the future of privacy? To accomplish this, I gathered information using a distributed survey to millennials attending Arizona State University. Using statistical analysis, I exposed trends for this demographic, discovering that there isn't a lack of knowledge among millennials; most are aware that smartphone apps can collect and share data and many of the participants are not comfortable with the current state of smartphone privacy. However, more than half of the study participants indicated that they never read an app's Terms of Service. Due to the nature of the privacy vs. convenience argument, users will willingly agree to let apps take their personal in- formation, since they don't want to give up the convenience.
ContributorsJones, Scott Spenser (Author) / Atkinson, Robert (Thesis director) / Chavez-Echeagaray, Maria Elena (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12