Matching Items (6)
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- All Subjects: blockchain
- Creators: Huang, Dijiang
Description
The explosive Web growth in the last decade has drastically changed the way billions of people all around the globe conduct numerous activities including creating, sharing, and consuming information. The massive amount of user-generated information encourages companies and service providers to collect users' information and use it in order to better their own goals and then further provide personalized services to users as well. However, the users' information contains their private and sensitive information and can lead to breach of users' privacy. Anonymizing users' information before publishing and using such data is vital in securing their privacy. Due to the many forms of user information (e.g., structural, interactions, etc), different techniques are required for anonymization of users' data. In this thesis, first we discuss different anonymization techniques for various types of user-generated data, i.e., network graphs, web browsing history, and user-item interactions. Our experimental results show the effectiveness of such techniques for data anonymization. Then, we briefly touch on securely and privately sharing information through blockchains.
ContributorsNou, Alex Sheavin (Author) / Liu, Huan (Thesis director) / Beigi, Ghazaleh (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Smart cities are the next wave of rapid expansion of Internet of Things (IoT). A smart city is a designation given to a city that incorporates information and communication technologies (ICT) to enhance the quality and performance of urban services, such as energy, transportation, healthcare, communications, entertainments, education, e-commerce, businesses, city management, and utilities, to reduce resource consumption, wastage and overall costs. The overarching aim of a smart city is to enhance the quality of living for its residents and businesses, through technology. In a large ecosystem, like a smart city, many organizations and companies collaborate with the smart city government to improve the smart city. These entities may need to store and share critical data with each other. A smart city has several thousands of smart devices and sensors deployed across the city. Storing critical data in a secure and scalable manner is an important issue in a smart city. While current cloud-based services, like Splunk and ELK (Elasticsearch-Logstash-Kibana), offer a centralized view and control over the IT operations of these smart devices, it is still prone to insider attacks, data tampering, and rogue administrator problems. In this thesis, we present an approach using blockchain to recovering critical data from unauthorized modifications. We use extensive simulations based on complex adaptive system theory, for evaluation of our approach. Through mathematical proof we proved that the approach always detects an unauthorized modification of critical data.
ContributorsMishra, Vineeta (Author) / Yau, Sik-Sang (Thesis advisor) / Goul, Michael K (Committee member) / Huang, Dijiang (Committee member) / Arizona State University (Publisher)
Created2017
Description
The purpose of an election is for the voice of the voters to be heard. All the participants in an election must be able to trust that the result of an election is actually the opinion of the people, unaltered by anything or anyone that may be trying to sway the vote. In the voting process, any "black boxes" or secrets can lead to mistrust in the system. In this thesis, an approach is developed for an electronic voting framework that is transparent, auditable, and scalable, making it trustworthy and usable for a wide-scale election. Based on my analysis, linkable ring signatures are utilized in order to preserve voter privacy while ensuring that a corrupt authenticating authority could not sway the vote. A hierarchical blockchain framework is presented to make ring signatures a viable signature scheme even when working with large populations. The solution is evaluated for compliance with secure voting requirements and scalability.
ContributorsMarple, Sam (Author) / Yau, Sik-Sang (Thesis advisor) / Huang, Dijiang (Committee member) / Trieu, Ni (Committee member) / Arizona State University (Publisher)
Created2021
Description
Emerging from years of research and development, the Internet-of-Things (IoT) has finally paved its way into our daily lives. From smart home to Industry 4.0, IoT has been fundamentally transforming numerous domains with its unique superpower of interconnecting world-wide devices. However, the capability of IoT is largely constrained by the limited resources it can employ in various application scenarios, including computing power, network resource, dedicated hardware, etc. The situation is further exacerbated by the stringent quality-of-service (QoS) requirements of many IoT applications, such as delay, bandwidth, security, reliability, and more. This mismatch in resources and demands has greatly hindered the deployment and utilization of IoT services in many resource-intense and QoS-sensitive scenarios like autonomous driving and virtual reality.
I believe that the resource issue in IoT will persist in the near future due to technological, economic and environmental factors. In this dissertation, I seek to address this issue by means of smart resource allocation. I propose mathematical models to formally describe various resource constraints and application scenarios in IoT. Based on these, I design smart resource allocation algorithms and protocols to maximize the system performance in face of resource restrictions. Different aspects are tackled, including networking, security, and economics of the entire IoT ecosystem. For different problems, different algorithmic solutions are devised, including optimal algorithms, provable approximation algorithms, and distributed protocols. The solutions are validated with rigorous theoretical analysis and/or extensive simulation experiments.
I believe that the resource issue in IoT will persist in the near future due to technological, economic and environmental factors. In this dissertation, I seek to address this issue by means of smart resource allocation. I propose mathematical models to formally describe various resource constraints and application scenarios in IoT. Based on these, I design smart resource allocation algorithms and protocols to maximize the system performance in face of resource restrictions. Different aspects are tackled, including networking, security, and economics of the entire IoT ecosystem. For different problems, different algorithmic solutions are devised, including optimal algorithms, provable approximation algorithms, and distributed protocols. The solutions are validated with rigorous theoretical analysis and/or extensive simulation experiments.
ContributorsYu, Ruozhou, Ph.D (Author) / Xue, Guoliang (Thesis advisor) / Huang, Dijiang (Committee member) / Sen, Arunabha (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)
Created2019
Description
The traditional access control system suffers from the problem of separation of data ownership and management. It poses data security issues in application scenarios such as cloud computing and blockchain where the data owners either do not trust the data storage provider or even do not know who would have access to their data once they are appended to the chain. In these scenarios, the data owner actually loses control of the data once they are uploaded to the outside storage. Encryption-before-uploading is the way to solve this issue, however traditional encryption schemes such as AES, RSA, ECC, bring about great overheads in key management on the data owner end and could not provide fine-grained access control as well.
Attribute-Based Encryption (ABE) is a cryptographic way to implement attribute-based access control, which is a fine-grained access control model, thus solving all aforementioned issues. With ABE, the data owner would encrypt the data by a self-defined access control policy before uploading the data. The access control policy is an AND-OR boolean formula over attributes. Only users with attributes that satisfy the access control policy could decrypt the ciphertext. However the existing ABE schemes do not provide some important features in practical applications, e.g., user revocation and attribute expiration. Furthermore, most existing work focus on how to use ABE to protect cloud stored data, while not the blockchain applications.
The main objective of this thesis is to provide solutions to add two important features of the ABE schemes, i.e., user revocation and attribute expiration, and also provide a practical trust framework for using ABE to protect blockchain data. To add the feature of user revocation, I propose to add user's hierarchical identity into the private attribute key. In this way, only users whose identity is not revoked and attributes satisfy the access control policy could decrypt the ciphertext. To add the feature of attribute expiration, I propose to add the attribute valid time period into the private attribute key. The data would be encrypted by access control policy where all attributes have a temporal value. In this way, only users whose attributes both satisfy the access policy and at the same time these attributes do not expire,
are allowed to decrypt the ciphertext. To use ABE in the blockchain applications, I propose an ABE-enabled trust framework in a very popular blockchain platform, Hyperledger Fabric. Based on the design, I implement a light-weight attribute certificate authority for attribute distribution and validation; I implement the proposed ABE schemes and provide a toolkit which supports system setup, key generation,
data encryption and data decryption. All these modules were integrated into a demo system for protecting sensitive les in a blockchain application.
Attribute-Based Encryption (ABE) is a cryptographic way to implement attribute-based access control, which is a fine-grained access control model, thus solving all aforementioned issues. With ABE, the data owner would encrypt the data by a self-defined access control policy before uploading the data. The access control policy is an AND-OR boolean formula over attributes. Only users with attributes that satisfy the access control policy could decrypt the ciphertext. However the existing ABE schemes do not provide some important features in practical applications, e.g., user revocation and attribute expiration. Furthermore, most existing work focus on how to use ABE to protect cloud stored data, while not the blockchain applications.
The main objective of this thesis is to provide solutions to add two important features of the ABE schemes, i.e., user revocation and attribute expiration, and also provide a practical trust framework for using ABE to protect blockchain data. To add the feature of user revocation, I propose to add user's hierarchical identity into the private attribute key. In this way, only users whose identity is not revoked and attributes satisfy the access control policy could decrypt the ciphertext. To add the feature of attribute expiration, I propose to add the attribute valid time period into the private attribute key. The data would be encrypted by access control policy where all attributes have a temporal value. In this way, only users whose attributes both satisfy the access policy and at the same time these attributes do not expire,
are allowed to decrypt the ciphertext. To use ABE in the blockchain applications, I propose an ABE-enabled trust framework in a very popular blockchain platform, Hyperledger Fabric. Based on the design, I implement a light-weight attribute certificate authority for attribute distribution and validation; I implement the proposed ABE schemes and provide a toolkit which supports system setup, key generation,
data encryption and data decryption. All these modules were integrated into a demo system for protecting sensitive les in a blockchain application.
ContributorsDong, Qiuxiang (Author) / Huang, Dijiang (Thesis advisor) / Sen, Arunabha (Committee member) / Doupe, Adam (Committee member) / Arizona State University (Publisher)
Created2020
Description
Computer science education is an increasingly vital area of study with various challenges that increase the difficulty level for new students resulting in higher attrition rates. As part of an effort to resolve this issue, a new visual programming language environment was developed for this research, the Visual IoT and Robotics Programming Language Environment (VIPLE). VIPLE is based on computational thinking and flowchart, which reduces the needs of memorization of detailed syntax in text-based programming languages. VIPLE has been used at Arizona State University (ASU) in multiple years and sections of FSE100 as well as in universities worldwide. Another major issue with teaching large programming classes is the potential lack of qualified teaching assistants to grade and offer insight to a student’s programs at a level beyond output analysis.
In this dissertation, I propose a novel framework for performing semantic autograding, which analyzes student programs at a semantic level to help students learn with additional and systematic help. A general autograder is not practical for general programming languages, due to the flexibility of semantics. A practical autograder is possible in VIPLE, because of its simplified syntax and restricted options of semantics. The design of this autograder is based on the concept of theorem provers. To achieve this goal, I employ a modified version of Pi-Calculus to represent VIPLE programs and Hoare Logic to formalize program requirements. By building on the inference rules of Pi-Calculus and Hoare Logic, I am able to construct a theorem prover that can perform automated semantic analysis. Furthermore, building on this theorem prover enables me to develop a self-learning algorithm that can learn the conditions for a program’s correctness according to a given solution program.
In this dissertation, I propose a novel framework for performing semantic autograding, which analyzes student programs at a semantic level to help students learn with additional and systematic help. A general autograder is not practical for general programming languages, due to the flexibility of semantics. A practical autograder is possible in VIPLE, because of its simplified syntax and restricted options of semantics. The design of this autograder is based on the concept of theorem provers. To achieve this goal, I employ a modified version of Pi-Calculus to represent VIPLE programs and Hoare Logic to formalize program requirements. By building on the inference rules of Pi-Calculus and Hoare Logic, I am able to construct a theorem prover that can perform automated semantic analysis. Furthermore, building on this theorem prover enables me to develop a self-learning algorithm that can learn the conditions for a program’s correctness according to a given solution program.
ContributorsDe Luca, Gennaro (Author) / Chen, Yinong (Thesis advisor) / Liu, Huan (Thesis advisor) / Hsiao, Sharon (Committee member) / Huang, Dijiang (Committee member) / Arizona State University (Publisher)
Created2020