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Description
Cravingz is a web-based application that allows users to learn the maximum number of food items that they can purchase at a restaurant within a defined personal budget. We created two versions of this web-based application and asked 40 users to perform an A/B test to determine which version provides the best user experience in terms of efficiency and performance. Users who participated in this study completed a set of tasks to test these applications. Our findings demonstrate that users prefer a web application that does not require them to input data repeatedly to view combinations for multiple restaurants. Although the version which required reentry of data was more visually-pleasing, users preferred the version in which inputting data was a one-time task.
ContributorsPandarinath, Agastya (Co-author) / Jain, Ayushi (Co-author) / Atkinson, Robert (Thesis director) / Chavez-Echeagaray, Maria Elena (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
In the area of hardware, reverse engineering was traditionally focused on developing clones—duplicated components that performed the same functionality of the original component. While reverse engineering techniques have been applied to software, these techniques have instead focused on understanding high-level software designs to ease the software maintenance burden. This approach works well for traditional applications that contain source code, however, there are circumstances, particularly regarding web applications, where it would be very beneficial to clone a web application and no source code is present, e.g., for security testing of the application or for offline mock testing of a third-party web service. We call this the web application cloning problem.
This thesis presents a possible solution to the problem of web application cloning. Our approach is a novel application of inductive programming, which we call inductive reverse engineering. The goal of inductive reverse engineering is to automatically reverse engineer an abstraction of the web application’s code in a completely black-box manner. We build this approach using recent advances in inductive programming, and we solve several technical challenges to scale the inductive programming techniques to realistic-sized web applications. We target the initial version of our inductive reverse engineering tool to a subset of web applications, i.e., those that do not store state and those that do not have loops. We introduce an evaluation methodology for web application cloning techniques and evaluate our approach on several real-world web applications. The results indicate that inductive reverse engineering can effectively reverse engineer specific types of web applications. In the future, we hope to extend the power of inductive reverse engineering to web applications with state and to learn loops, while still maintaining tractability.
This thesis presents a possible solution to the problem of web application cloning. Our approach is a novel application of inductive programming, which we call inductive reverse engineering. The goal of inductive reverse engineering is to automatically reverse engineer an abstraction of the web application’s code in a completely black-box manner. We build this approach using recent advances in inductive programming, and we solve several technical challenges to scale the inductive programming techniques to realistic-sized web applications. We target the initial version of our inductive reverse engineering tool to a subset of web applications, i.e., those that do not store state and those that do not have loops. We introduce an evaluation methodology for web application cloning techniques and evaluate our approach on several real-world web applications. The results indicate that inductive reverse engineering can effectively reverse engineer specific types of web applications. In the future, we hope to extend the power of inductive reverse engineering to web applications with state and to learn loops, while still maintaining tractability.
ContributorsLiao, Kevin (Author) / Doupe, Adam (Thesis director) / Ahn, Gail-Joon (Committee member) / Zhao, Ziming (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Microblogging services such as Twitter, Sina Weibo, and Tumblr have been emerging and deeply embedded into people's daily lives. Used by hundreds of millions of users to connect the people worldwide and share and access information in real-time, the microblogging service has also became the target of malicious attackers due to its massive user engagement and structural openness. Although existed, little is still known in the community about new types of vulnerabilities in current microblogging services which could be leveraged by the intelligence-evolving attackers, and more importantly, the corresponding defenses that could prevent both the users and the microblogging service providers from being attacked. This dissertation aims to uncover a number of challenging security and privacy issues in microblogging services and also propose corresponding defenses.
This dissertation makes fivefold contributions. The first part presents the social botnet, a group of collaborative social bots under the control of a single botmaster, demonstrate the effectiveness and advantages of exploiting a social botnet for spam distribution and digital-influence manipulation, and propose the corresponding countermeasures and evaluate their effectiveness. Inspired by Pagerank, the second part describes TrueTop, the first sybil-resilient system to find the top-K influential users in microblogging services with very accurate results and strong resilience to sybil attacks. TrueTop has been implemented to handle millions of nodes and 100 times more edges on commodity computers. The third and fourth part demonstrate that microblogging systems' structural openness and users' carelessness could disclose the later's sensitive information such as home city and age. LocInfer, a novel and lightweight system, is presented to uncover the majority of the users in any metropolitan area; the dissertation also proposes MAIF, a novel machine learning framework that leverages public content and interaction information in microblogging services to infer users' hidden ages. Finally, the dissertation proposes the first privacy-preserving social media publishing framework to let the microblogging service providers publish their data to any third-party without disclosing users' privacy and meanwhile meeting the data's commercial utilities. This dissertation sheds the light on the state-of-the-art security and privacy issues in the microblogging services.
This dissertation makes fivefold contributions. The first part presents the social botnet, a group of collaborative social bots under the control of a single botmaster, demonstrate the effectiveness and advantages of exploiting a social botnet for spam distribution and digital-influence manipulation, and propose the corresponding countermeasures and evaluate their effectiveness. Inspired by Pagerank, the second part describes TrueTop, the first sybil-resilient system to find the top-K influential users in microblogging services with very accurate results and strong resilience to sybil attacks. TrueTop has been implemented to handle millions of nodes and 100 times more edges on commodity computers. The third and fourth part demonstrate that microblogging systems' structural openness and users' carelessness could disclose the later's sensitive information such as home city and age. LocInfer, a novel and lightweight system, is presented to uncover the majority of the users in any metropolitan area; the dissertation also proposes MAIF, a novel machine learning framework that leverages public content and interaction information in microblogging services to infer users' hidden ages. Finally, the dissertation proposes the first privacy-preserving social media publishing framework to let the microblogging service providers publish their data to any third-party without disclosing users' privacy and meanwhile meeting the data's commercial utilities. This dissertation sheds the light on the state-of-the-art security and privacy issues in the microblogging services.
ContributorsZhang, Jinxue (Author) / Zhang, Yanchao (Thesis advisor) / Zhang, Junshan (Committee member) / Ying, Lei (Committee member) / Ahn, Gail-Joon (Committee member) / Arizona State University (Publisher)
Created2016
Description
Mobile devices are penetrating everyday life. According to a recent Cisco report [10], the number of mobile connected devices such as smartphones, tablets, laptops, eReaders, and Machine-to-Machine (M2M) modules will hit 11.6 billion by 2021, exceeding the world's projected population at that time (7.8 billion). The rapid development of mobile devices has brought a number of emerging security and privacy issues in mobile computing. This dissertation aims to address a number of challenging security and privacy issues in mobile computing.
This dissertation makes fivefold contributions. The first and second parts study the security and privacy issues in Device-to-Device communications. Specifically, the first part develops a novel scheme to enable a new way of trust relationship called spatiotemporal matching in a privacy-preserving and efficient fashion. To enhance the secure communication among mobile users, the second part proposes a game-theoretical framework to stimulate the cooperative shared secret key generation among mobile users. The third and fourth parts investigate the security and privacy issues in mobile crowdsourcing. In particular, the third part presents a secure and privacy-preserving mobile crowdsourcing system which strikes a good balance among object security, user privacy, and system efficiency. The fourth part demonstrates a differentially private distributed stream monitoring system via mobile crowdsourcing. Finally, the fifth part proposes VISIBLE, a novel video-assisted keystroke inference framework that allows an attacker to infer a tablet user's typed inputs on the touchscreen by recording and analyzing the video of the tablet backside during the user's input process. Besides, some potential countermeasures to this attack are also discussed. This dissertation sheds the light on the state-of-the-art security and privacy issues in mobile computing.
This dissertation makes fivefold contributions. The first and second parts study the security and privacy issues in Device-to-Device communications. Specifically, the first part develops a novel scheme to enable a new way of trust relationship called spatiotemporal matching in a privacy-preserving and efficient fashion. To enhance the secure communication among mobile users, the second part proposes a game-theoretical framework to stimulate the cooperative shared secret key generation among mobile users. The third and fourth parts investigate the security and privacy issues in mobile crowdsourcing. In particular, the third part presents a secure and privacy-preserving mobile crowdsourcing system which strikes a good balance among object security, user privacy, and system efficiency. The fourth part demonstrates a differentially private distributed stream monitoring system via mobile crowdsourcing. Finally, the fifth part proposes VISIBLE, a novel video-assisted keystroke inference framework that allows an attacker to infer a tablet user's typed inputs on the touchscreen by recording and analyzing the video of the tablet backside during the user's input process. Besides, some potential countermeasures to this attack are also discussed. This dissertation sheds the light on the state-of-the-art security and privacy issues in mobile computing.
ContributorsSun, Jingchao (Author) / Zhang, Yanchao (Thesis advisor) / Zhang, Junshan (Committee member) / Ying, Lei (Committee member) / Ahn, Gail-Joon (Committee member) / Arizona State University (Publisher)
Created2017
Description
Wireless sensor networks (WSN) and the communication and the security therein have been gaining further prominence in the tech-industry recently, with the emergence of the so called Internet of Things (IoT). The steps from acquiring data and making a reactive decision base on the acquired sensor measurements are complex and requires careful execution of several steps. In many of these steps there are still technological gaps to fill that are due to the fact that several primitives that are desirable in a sensor network environment are bolt on the networks as application layer functionalities, rather than built in them. For several important functionalities that are at the core of IoT architectures we have developed a solution that is analyzed and discussed in the following chapters.
The chain of steps from the acquisition of sensor samples until these samples reach a control center or the cloud where the data analytics are performed, starts with the acquisition of the sensor measurements at the correct time and, importantly, synchronously among all sensors deployed. This synchronization has to be network wide, including both the wired core network as well as the wireless edge devices. This thesis studies a decentralized and lightweight solution to synchronize and schedule IoT devices over wireless and wired networks adaptively, with very simple local signaling. Furthermore, measurement results have to be transported and aggregated over the same interface, requiring clever coordination among all nodes, as network resources are shared, keeping scalability and fail-safe operation in mind. Furthermore ensuring the integrity of measurements is a complicated task. On the one hand Cryptography can shield the network from outside attackers and therefore is the first step to take, but due to the volume of sensors must rely on an automated key distribution mechanism. On the other hand cryptography does not protect against exposed keys or inside attackers. One however can exploit statistical properties to detect and identify nodes that send false information and exclude these attacker nodes from the network to avoid data manipulation. Furthermore, if data is supplied by a third party, one can apply automated trust metric for each individual data source to define which data to accept and consider for mentioned statistical tests in the first place. Monitoring the cyber and physical activities of an IoT infrastructure in concert is another topic that is investigated in this thesis.
The chain of steps from the acquisition of sensor samples until these samples reach a control center or the cloud where the data analytics are performed, starts with the acquisition of the sensor measurements at the correct time and, importantly, synchronously among all sensors deployed. This synchronization has to be network wide, including both the wired core network as well as the wireless edge devices. This thesis studies a decentralized and lightweight solution to synchronize and schedule IoT devices over wireless and wired networks adaptively, with very simple local signaling. Furthermore, measurement results have to be transported and aggregated over the same interface, requiring clever coordination among all nodes, as network resources are shared, keeping scalability and fail-safe operation in mind. Furthermore ensuring the integrity of measurements is a complicated task. On the one hand Cryptography can shield the network from outside attackers and therefore is the first step to take, but due to the volume of sensors must rely on an automated key distribution mechanism. On the other hand cryptography does not protect against exposed keys or inside attackers. One however can exploit statistical properties to detect and identify nodes that send false information and exclude these attacker nodes from the network to avoid data manipulation. Furthermore, if data is supplied by a third party, one can apply automated trust metric for each individual data source to define which data to accept and consider for mentioned statistical tests in the first place. Monitoring the cyber and physical activities of an IoT infrastructure in concert is another topic that is investigated in this thesis.
ContributorsGentz, Reinhard Werner (Author) / Scaglione, Anna (Thesis advisor) / Zhang, Yanchao (Committee member) / Peisert, Sean (Committee member) / Ahn, Gail-Joon (Committee member) / Arizona State University (Publisher)
Created2017
Description
Data from a total of 282 online web applications was collected, and accounts for 230 of those web applications were created in order to gather data about authentication practices, multistep authentication practices, security question practices, fallback authentication practices, and other security practices for online accounts. The account creation and data collection was done between June 2016 and April 2017. The password strengths for online accounts were analyzed and password strength data was compared to existing data. Security questions used by online accounts were evaluated for security and usability, and fallback authentication practices were assessed based on their adherence to best practices. Alternative authentication schemes were examined, and other security considerations such as use of HTTPS and CAPTCHAs were explored. Based on existing data, password policies require stronger passwords in for web applications in 2017 compared to the requirements in 2010. Nevertheless, password policies for many accounts are still not adequate. About a quarter of online web applications examined use security questions, and many of the questions have usability and security concerns. Security mechanisms such as HTTPS and continuous authentication are in general not used in conjunction with security questions for most web applications, which reduces the overall security of the web application. A majority of web applications use email addresses as the login credential and the password recovery credential and do not follow best practices. About a quarter of accounts use multistep authentication and a quarter of accounts employ continuous authentication, yet most accounts fail to combine security measures for defense in depth. The overall conclusion is that some online web applications are using secure practices; however, a majority of online web applications fail to properly implement and utilize secure practices.
ContributorsGutierrez, Garrett (Author) / Bazzi, Rida (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Doupe, Adam (Committee member) / Arizona State University (Publisher)
Created2017