Matching Items (6)
Filtering by

Clear all filters

133137-Thumbnail Image.png
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
133050-Thumbnail Image.png
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
134266-Thumbnail Image.png
Description
Node.js is an extremely popular development framework for web applications. The appeal of its event-driven, asynchronous flow and the convenience of JavaScript as its programming language have driven its rapid growth, and it is currently deployed by leading companies in retail, finance, and other important sectors. However, the tools currently

Node.js is an extremely popular development framework for web applications. The appeal of its event-driven, asynchronous flow and the convenience of JavaScript as its programming language have driven its rapid growth, and it is currently deployed by leading companies in retail, finance, and other important sectors. However, the tools currently available for Node.js developers to secure their applications against malicious attackers are notably scarce. While there has been a substantial amount of security tools created for web applications in many other languages such as PHP and Java, very little exists for Node.js applications. This could compromise private information belonging to companies such as PayPal and WalMart. We propose a tool to statically analyze Node.js web applications for five popular vulnerabilites: cross-site scripting, SQL injection, server-side request forgery, command injection, and code injection. We base our tool off of JSAI, a platform created to parse client-side JavaScript for security risks. JSAI is novel because of its configuration capabilities, which allow a user to choose between various analysis options at runtime in order to select the most thorough analysis with the least amount of processing time. We contribute to the development of our tool by rigorously analyzing and documenting vulnerable functions and objects in Node.js that are relevant to the vulnerabilities we have selected. We intend to use this documentation to build a robust Node.js static analysis tool and we hope that other developers will also incorporate this analysis into their Node.js security projects.
ContributorsWasserman, Jonathan Kanter (Author) / Doupe, Adam (Thesis director) / Ahn, Gail-Joon (Committee member) / Zhao, Ziming (Committee member) / School of Historical, Philosophical and Religious Studies (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
133206-Thumbnail Image.png
Description
Ethereum smart contracts are susceptible not only to those vulnerabilities common to all software development domains, but also to those arising from the peculiar execution model of the Ethereum Virtual Machine. One of these vulnerabilities, a susceptibility to re-entrancy attacks, has been at the center of several high-profile contract exploits.

Ethereum smart contracts are susceptible not only to those vulnerabilities common to all software development domains, but also to those arising from the peculiar execution model of the Ethereum Virtual Machine. One of these vulnerabilities, a susceptibility to re-entrancy attacks, has been at the center of several high-profile contract exploits. Currently, there exist many tools to detect these vulnerabilties, as well as languages which preempt the creation of contracts exhibiting these issues, but no mechanism to address them in an automated fashion. One possible approach to filling this gap is direct patching of source files. The process of applying these patches to contracts written in Solidity, the primary Ethereum contract language, is discussed. Toward this end, a survey of deployed contracts is conducted, focusing on prevalence of language features and compiler versions. A heuristic approach to mitigating a particular class of re-entrancy vulnerability is developed, implemented as the SolPatch tool, and examined with respect to its limitations. As a proof of concept and illustrative example, a simplified version of the contract featured in a high-profile exploit is patched in this manner.
ContributorsLehman, Maxfield Chance Christian (Author) / Bazzi, Rida (Thesis director) / Doupe, Adam (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
135099-Thumbnail Image.png
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
131337-Thumbnail Image.png
Description
Apple’s HomeKit framework centralizes control of smart home devices and allows users to create home automations based on predefined rules. For example, a user can add a rule to turn off all the lights in their house whenever they leave. Currently, these rules must be added through a graphical user

Apple’s HomeKit framework centralizes control of smart home devices and allows users to create home automations based on predefined rules. For example, a user can add a rule to turn off all the lights in their house whenever they leave. Currently, these rules must be added through a graphical user interface provided by Apple or a third-party app on iOS. This thesis describes how a text-based language provides users with a more expressive means of creating complex home automations and successfully implements such a language. Rules created using this text-based format are parsed and interpreted into rules that can be added directly into HomeKit. This thesis also explores how security features should be implemented with this text-based approach. Since automations are run by the system without user interaction, it is important to consider how the system itself can provide functionality to address the unintended consequences that may result from running an automation. This is especially important for the text-based approach since its increase in expressiveness makes it easier for a user to make a mistake in programming that leads to a security concern. The proposed method for preventing unintended side effects is using a simulation to run every automation prior to actually running the automation on real-world devices. This approach allows users to code some conditions that must be satisfied in order for the automation to run on devices in the home. This thesis describes the creation of such a program that successfully simulates every device in the home. There were limitations, however, with Apple's HomeKit framework, which made it impractical to match the state of simulated devices to real devices in the home. Without being able to match the current state of the home to the current state of the simulation, this method cannot satisfy the goal of ensuring that certain adverse effects will not occur as a result of automations. Other smart home control platforms that provide more extensibility could be used to create this simulation-based security approach. Perhaps as Apple continues to open up their HomeKit platform to developers, this approach may be feasible within Apple's ecosystem at some point in the future.
ContributorsSharp, Trevor Ryan (Co-author) / Sharp, Trevor (Co-author) / Bazzi, Rida (Thesis director) / Doupe, Adam (Committee member) / Economics Program in CLAS (Contributor) / Department of Management and Entrepreneurship (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05