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Most existing security decisions for both defending and attacking are made based on some deterministic approaches that only give binary answers. Even though these approaches can achieve low false positive rate for decision making, they have high false negative rates due to the lack of accommodations to new attack methods

Most existing security decisions for both defending and attacking are made based on some deterministic approaches that only give binary answers. Even though these approaches can achieve low false positive rate for decision making, they have high false negative rates due to the lack of accommodations to new attack methods and defense techniques. In this dissertation, I study how to discover and use patterns with uncertainty and randomness to counter security challenges. By extracting and modeling patterns in security events, I am able to handle previously unknown security events with quantified confidence, rather than simply making binary decisions. In particular, I cope with the following four real-world security challenges by modeling and analyzing with pattern-based approaches: 1) How to detect and attribute previously unknown shellcode? I propose instruction sequence abstraction that extracts coarse-grained patterns from an instruction sequence and use Markov chain-based model and support vector machines to detect and attribute shellcode; 2) How to safely mitigate routing attacks in mobile ad hoc networks? I identify routing table change patterns caused by attacks, propose an extended Dempster-Shafer theory to measure the risk of such changes, and use a risk-aware response mechanism to mitigate routing attacks; 3) How to model, understand, and guess human-chosen picture passwords? I analyze collected human-chosen picture passwords, propose selection function that models patterns in password selection, and design two algorithms to optimize password guessing paths; and 4) How to identify influential figures and events in underground social networks? I analyze collected underground social network data, identify user interaction patterns, and propose a suite of measures for systematically discovering and mining adversarial evidence. By solving these four problems, I demonstrate that discovering and using patterns could help deal with challenges in computer security, network security, human-computer interaction security, and social network security.
ContributorsZhao, Ziming (Author) / Ahn, Gail-Joon (Thesis advisor) / Yau, Stephen S. (Committee member) / Huang, Dijiang (Committee member) / Santanam, Raghu (Committee member) / Arizona State University (Publisher)
Created2014
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Description
In modern healthcare environments, there is a strong need to create an infrastructure that reduces time-consuming efforts and costly operations to obtain a patient's complete medical record and uniformly integrates this heterogeneous collection of medical data to deliver it to the healthcare professionals. As a result, healthcare providers are more

In modern healthcare environments, there is a strong need to create an infrastructure that reduces time-consuming efforts and costly operations to obtain a patient's complete medical record and uniformly integrates this heterogeneous collection of medical data to deliver it to the healthcare professionals. As a result, healthcare providers are more willing to shift their electronic medical record (EMR) systems to clouds that can remove the geographical distance barriers among providers and patient. Even though cloud-based EMRs have received considerable attention since it would help achieve lower operational cost and better interoperability with other healthcare providers, the adoption of security-aware cloud systems has become an extremely important prerequisite for bringing interoperability and efficient management to the healthcare industry. Since a shared electronic health record (EHR) essentially represents a virtualized aggregation of distributed clinical records from multiple healthcare providers, sharing of such integrated EHRs may comply with various authorization policies from these data providers. In this work, we focus on the authorized and selective sharing of EHRs among several parties with different duties and objectives that satisfies access control and compliance issues in healthcare cloud computing environments. We present a secure medical data sharing framework to support selective sharing of composite EHRs aggregated from various healthcare providers and compliance of HIPAA regulations. Our approach also ensures that privacy concerns need to be accommodated for processing access requests to patients' healthcare information. To realize our proposed approach, we design and implement a cloud-based EHRs sharing system. In addition, we describe case studies and evaluation results to demonstrate the effectiveness and efficiency of our approach.
ContributorsWu, Ruoyu (Author) / Ahn, Gail-Joon (Thesis advisor) / Yau, Stephen S. (Committee member) / Huang, Dijiang (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Access control is one of the most fundamental security mechanisms used in the design and management of modern information systems. However, there still exists an open question on how formal access control models can be automatically analyzed and fully realized in secure system development. Furthermore, specifying and managing access control

Access control is one of the most fundamental security mechanisms used in the design and management of modern information systems. However, there still exists an open question on how formal access control models can be automatically analyzed and fully realized in secure system development. Furthermore, specifying and managing access control policies are often error-prone due to the lack of effective analysis mechanisms and tools. In this dissertation, I present an Assurance Management Framework (AMF) that is designed to cope with various assurance management requirements from both access control system development and policy-based computing. On one hand, the AMF framework facilitates comprehensive analysis and thorough realization of formal access control models in secure system development. I demonstrate how this method can be applied to build role-based access control systems by adopting the NIST/ANSI RBAC standard as an underlying security model. On the other hand, the AMF framework ensures the correctness of access control policies in policy-based computing through automated reasoning techniques and anomaly management mechanisms. A systematic method is presented to formulate XACML in Answer Set Programming (ASP) that allows users to leverage off-the-shelf ASP solvers for a variety of analysis services. In addition, I introduce a novel anomaly management mechanism, along with a grid-based visualization approach, which enables systematic and effective detection and resolution of policy anomalies. I further evaluate the AMF framework through modeling and analyzing multiparty access control in Online Social Networks (OSNs). A MultiParty Access Control (MPAC) model is formulated to capture the essence of multiparty authorization requirements in OSNs. In particular, I show how AMF can be applied to OSNs for identifying and resolving privacy conflicts, and representing and reasoning about MPAC model and policy. To demonstrate the feasibility of the proposed methodology, a suite of proof-of-concept prototype systems is implemented as well.
ContributorsHu, Hongxin (Author) / Ahn, Gail-Joon (Thesis advisor) / Yau, Stephen S. (Committee member) / Dasgupta, Partha (Committee member) / Ye, Nong (Committee member) / Arizona State University (Publisher)
Created2012
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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
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Description
Security requirements are at the heart of developing secure, invulnerable software. Without embedding security principles in the software development life cycle, the likelihood of producing insecure software increases, putting the consumers of that software at great risk. For large-scale software development, this problem is complicated as there may be hundreds

Security requirements are at the heart of developing secure, invulnerable software. Without embedding security principles in the software development life cycle, the likelihood of producing insecure software increases, putting the consumers of that software at great risk. For large-scale software development, this problem is complicated as there may be hundreds or thousands of security requirements that need to be met, and it only worsens if the software development project is developed by a distributed development team. In this thesis, an approach is provided for software security requirement traceability for large-scale and complex software development projects being developed by distributed development teams. The approach utilizes blockchain technology to improve the automation of security requirement satisfaction and create a more transparent and trustworthy development environment for distributed development teams. The approach also introduces immutability, auditability, and non-repudiation into the security requirement traceability process. The approach is evaluated against existing software security requirement solutions.
ContributorsKulkarni, Adi Deepak (Author) / Yau, Stephen S. (Thesis advisor) / Banerjee, Ayan (Committee member) / Wang, Ruoyu (Committee member) / Baek, Jaejong (Committee member) / Arizona State University (Publisher)
Created2022