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Description
Answer Set Programming (ASP) is one of the most prominent and successful knowledge representation paradigms. The success of ASP is due to its expressive non-monotonic modeling language and its efficient computational methods originating from building propositional satisfiability solvers. The wide adoption of ASP has motivated several extensions to its modeling

Answer Set Programming (ASP) is one of the most prominent and successful knowledge representation paradigms. The success of ASP is due to its expressive non-monotonic modeling language and its efficient computational methods originating from building propositional satisfiability solvers. The wide adoption of ASP has motivated several extensions to its modeling language in order to enhance expressivity, such as incorporating aggregates and interfaces with ontologies. Also, in order to overcome the grounding bottleneck of computation in ASP, there are increasing interests in integrating ASP with other computing paradigms, such as Constraint Programming (CP) and Satisfiability Modulo Theories (SMT). Due to the non-monotonic nature of the ASP semantics, such enhancements turned out to be non-trivial and the existing extensions are not fully satisfactory. We observe that one main reason for the difficulties rooted in the propositional semantics of ASP, which is limited in handling first-order constructs (such as aggregates and ontologies) and functions (such as constraint variables in CP and SMT) in natural ways. This dissertation presents a unifying view on these extensions by viewing them as instances of formulas with generalized quantifiers and intensional functions. We extend the first-order stable model semantics by by Ferraris, Lee, and Lifschitz to allow generalized quantifiers, which cover aggregate, DL-atoms, constraints and SMT theory atoms as special cases. Using this unifying framework, we study and relate different extensions of ASP. We also present a tight integration of ASP with SMT, based on which we enhance action language C+ to handle reasoning about continuous changes. Our framework yields a systematic approach to study and extend non-monotonic languages.
ContributorsMeng, Yunsong (Author) / Lee, Joohyung (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Baral, Chitta (Committee member) / Fainekos, Georgios (Committee member) / Lifschitz, Vladimir (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Action language C+ is a formalism for describing properties of actions, which is based on nonmonotonic causal logic. The definite fragment of C+ is implemented in the Causal Calculator (CCalc), which is based on the reduction of nonmonotonic causal logic to propositional logic. This thesis describes the language

Action language C+ is a formalism for describing properties of actions, which is based on nonmonotonic causal logic. The definite fragment of C+ is implemented in the Causal Calculator (CCalc), which is based on the reduction of nonmonotonic causal logic to propositional logic. This thesis describes the language of CCalc in terms of answer set programming (ASP), based on the translation of nonmonotonic causal logic to formulas under the stable model semantics. I designed a standard library which describes the constructs of the input language of CCalc in terms of ASP, allowing a simple modular method to represent CCalc input programs in the language of ASP. Using the combination of system F2LP and answer set solvers, this method achieves functionality close to that of CCalc while taking advantage of answer set solvers to yield efficient computation that is orders of magnitude faster than CCalc for many benchmark examples. In support of this, I created an automated translation system Cplus2ASP that implements the translation and encoding method and automatically invokes the necessary software to solve the translated input programs.
ContributorsCasolary, Michael (Author) / Lee, Joohyung (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Baral, Chitta (Committee member) / Arizona State University (Publisher)
Created2011
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Description
Different logic-based knowledge representation formalisms have different limitations either with respect to expressivity or with respect to computational efficiency. First-order logic, which is the basis of Description Logics (DLs), is not suitable for defeasible reasoning due to its monotonic nature. The nonmonotonic formalisms that extend first-order logic, such as circumscription

Different logic-based knowledge representation formalisms have different limitations either with respect to expressivity or with respect to computational efficiency. First-order logic, which is the basis of Description Logics (DLs), is not suitable for defeasible reasoning due to its monotonic nature. The nonmonotonic formalisms that extend first-order logic, such as circumscription and default logic, are expressive but lack efficient implementations. The nonmonotonic formalisms that are based on the declarative logic programming approach, such as Answer Set Programming (ASP), have efficient implementations but are not expressive enough for representing and reasoning with open domains. This dissertation uses the first-order stable model semantics, which extends both first-order logic and ASP, to relate circumscription to ASP, and to integrate DLs and ASP, thereby partially overcoming the limitations of the formalisms. By exploiting the relationship between circumscription and ASP, well-known action formalisms, such as the situation calculus, the event calculus, and Temporal Action Logics, are reformulated in ASP. The advantages of these reformulations are shown with respect to the generality of the reasoning tasks that can be handled and with respect to the computational efficiency. The integration of DLs and ASP presented in this dissertation provides a framework for integrating rules and ontologies for the semantic web. This framework enables us to perform nonmonotonic reasoning with DL knowledge bases. Observing the need to integrate action theories and ontologies, the above results are used to reformulate the problem of integrating action theories and ontologies as a problem of integrating rules and ontologies, thus enabling us to use the computational tools developed in the context of the latter for the former.
ContributorsPalla, Ravi (Author) / Lee, Joohyung (Thesis advisor) / Baral, Chitta (Committee member) / Kambhampati, Subbarao (Committee member) / Lifschitz, Vladimir (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Reasoning about the activities of cyber threat actors is critical to defend against cyber

attacks. However, this task is difficult for a variety of reasons. In simple terms, it is difficult

to determine who the attacker is, what the desired goals are of the attacker, and how they will

carry out their attacks.

Reasoning about the activities of cyber threat actors is critical to defend against cyber

attacks. However, this task is difficult for a variety of reasons. In simple terms, it is difficult

to determine who the attacker is, what the desired goals are of the attacker, and how they will

carry out their attacks. These three questions essentially entail understanding the attacker’s

use of deception, the capabilities available, and the intent of launching the attack. These

three issues are highly inter-related. If an adversary can hide their intent, they can better

deceive a defender. If an adversary’s capabilities are not well understood, then determining

what their goals are becomes difficult as the defender is uncertain if they have the necessary

tools to accomplish them. However, the understanding of these aspects are also mutually

supportive. If we have a clear picture of capabilities, intent can better be deciphered. If we

understand intent and capabilities, a defender may be able to see through deception schemes.

In this dissertation, I present three pieces of work to tackle these questions to obtain

a better understanding of cyber threats. First, we introduce a new reasoning framework

to address deception. We evaluate the framework by building a dataset from DEFCON

capture-the-flag exercise to identify the person or group responsible for a cyber attack.

We demonstrate that the framework not only handles cases of deception but also provides

transparent decision making in identifying the threat actor. The second task uses a cognitive

learning model to determine the intent – goals of the threat actor on the target system.

The third task looks at understanding the capabilities of threat actors to target systems by

identifying at-risk systems from hacker discussions on darkweb websites. To achieve this

task we gather discussions from more than 300 darkweb websites relating to malicious

hacking.
ContributorsNunes, Eric (Author) / Shakarian, Paulo (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Baral, Chitta (Committee member) / Cooke, Nancy J. (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Smartphones are pervasive nowadays. They are supported by mobile platforms that allow users to download and run feature-rich mobile applications (apps). While mobile apps help users conveniently process personal data on mobile devices, they also pose security and privacy threats and put user's data at risk. Even though modern mobile

Smartphones are pervasive nowadays. They are supported by mobile platforms that allow users to download and run feature-rich mobile applications (apps). While mobile apps help users conveniently process personal data on mobile devices, they also pose security and privacy threats and put user's data at risk. Even though modern mobile platforms such as Android have integrated security mechanisms to protect users, most mechanisms do not easily adapt to user's security requirements and rapidly evolving threats. They either fail to provide sufficient intelligence for a user to make informed security decisions, or require great sophistication to configure the mechanisms for enforcing security decisions. These limitations lead to a situation where users are disadvantageous against emerging malware on modern mobile platforms. To remedy this situation, I propose automated and systematic approaches to address three security management tasks: monitoring, assessment, and confinement of mobile apps. In particular, monitoring apps helps a user observe and record apps' runtime behaviors as controlled under security mechanisms. Automated assessment distills intelligence from the observed behaviors and the security configurations of security mechanisms. The distilled intelligence further fuels enhanced confinement mechanisms that flexibly and accurately shape apps' behaviors. To demonstrate the feasibility of my approaches, I design and implement a suite of proof-of-concept prototypes that support the three tasks respectively.
ContributorsJing, Yiming (Author) / Ahn, Gail-Joon (Thesis advisor) / Doupe, Adam (Committee member) / Huang, Dijiang (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Detecting cyber-attacks in cyber systems is essential for protecting cyber infrastructures from cyber-attacks. It is very difficult to detect cyber-attacks in cyber systems due to their high complexity. The accuracy of the attack detection in the cyber systems

Detecting cyber-attacks in cyber systems is essential for protecting cyber infrastructures from cyber-attacks. It is very difficult to detect cyber-attacks in cyber systems due to their high complexity. The accuracy of the attack detection in the cyber systems depends heavily on the completeness of the collected sensor information. In this thesis, two approaches are presented: one to detecting attacks in completely observable cyber systems, and the other to estimating types of states in partially observable cyber systems for attack detection in cyber systems. These two approaches are illustrated using three large data sets of network traffic because the packet-level information of the network traffic data provides details about the cyber systems.

The approach to attack detection in cyber systems is based on a multimodal artificial neural network (MANN) using the collected network traffic data from completely observable cyber systems for training and testing. Since the training of MANN is computationally intensive, to reduce the computational overhead, an efficient feature selection algorithm using the genetic algorithm is developed and incorporated in this approach.

In order to detect attacks in cyber systems in partially observable environments, an approach to estimating the types of states in partially observable cyber systems, which is the first phase of attack detection in cyber systems in partially observable environments, is presented. The types of states of such cyber systems are useful to detecting cyber-attacks in such cyber systems. This approach involves the use of a convolutional neural network (CNN), and unsupervised learning with elbow method and k-means clustering algorithm.
ContributorsGuha, Sayantan (Author) / Yau, Stephen S. (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Huang, Dijiang (Committee member) / Arizona State University (Publisher)
Created2016
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Description
Access control has been historically recognized as an effective technique for ensuring that computer systems preserve important security properties. Recently, attribute-based

access control (ABAC) has emerged as a new paradigm to provide access mediation

by leveraging the concept of attributes: observable properties that become relevant under a certain security context and are

Access control has been historically recognized as an effective technique for ensuring that computer systems preserve important security properties. Recently, attribute-based

access control (ABAC) has emerged as a new paradigm to provide access mediation

by leveraging the concept of attributes: observable properties that become relevant under a certain security context and are exhibited by the entities normally involved in the mediation process, namely, end-users and protected resources. Also recently, independently-run organizations from the private and public sectors have recognized the benefits of engaging in multi-disciplinary research collaborations that involve sharing sensitive proprietary resources such as scientific data, networking capabilities and computation time and have recognized ABAC as the paradigm that suits their needs for restricting the way such resources are to be shared with each other. In such a setting, a robust yet flexible access mediation scheme is crucial to guarantee participants are granted access to such resources in a safe and secure manner.

However, no consensus exists either in the literature with respect to a formal model that clearly defines the way the components depicted in ABAC should interact with each other, so that the rigorous study of security properties to be effectively pursued. This dissertation proposes an approach tailored to provide a well-defined and formal definition of ABAC, including a description on how attributes exhibited by different independent organizations are to be leveraged for mediating access to shared resources, by allowing for collaborating parties to engage in federations for the specification, discovery, evaluation and communication of attributes, policies, and access mediation decisions. In addition, a software assurance framework is introduced to support the correct construction of enforcement mechanisms implementing our approach by leveraging validation and verification techniques based on software assertions, namely, design by contract (DBC) and behavioral interface specification languages (BISL). Finally, this dissertation also proposes a distributed trust framework that allows for exchanging recommendations on the perceived reputations of members of our proposed federations, in such a way that the level of trust of previously-unknown participants can be properly assessed for the purposes of access mediation.
ContributorsRubio Medrano, Carlos Ernesto (Author) / Ahn, Gail-Joon (Thesis advisor) / Doupe, Adam (Committee member) / Zhao, Ziming (Committee member) / Santanam, Raghu (Committee member) / Huang, Dijiang (Committee member) / Arizona State University (Publisher)
Created2016
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Description
Wireless communication technologies have been playing an important role in modern society. Due to its inherent mobility property, wireless networks are more vulnerable to passive attacks than traditional wired networks. Anonymity, as an important issue in mobile network environment, serves as the first topic that leads to all the research

Wireless communication technologies have been playing an important role in modern society. Due to its inherent mobility property, wireless networks are more vulnerable to passive attacks than traditional wired networks. Anonymity, as an important issue in mobile network environment, serves as the first topic that leads to all the research work presented in this manuscript. Specifically, anonymity issue in Mobile Ad hoc Networks (MANETs) is discussed with details as the first section of research.



To thoroughly study on this topic, the presented work approaches it from an attacker's perspective. Under a perfect scenario, all the traffic in a targeted MANET exhibits the communication relations to a passive attacker. However, localization errors pose a significant influence on the accuracy of the derived communication patterns. To handle such issue, a new scheme is proposed to generate super nodes, which represent the activities of user groups in the target MANET. This scheme also helps reduce the scale of monitoring work by grouping users based on their behaviors.



The first part of work on anonymity in MANET leads to the thought on its major cause. The link-based communication pattern is a key contributor to the success of the traffic analysis attack. A natural way to circumvent such issue is to use link-less approaches. Information Centric Networking (ICN) is a typical instance of such kind. Its communication pattern is able to overcome the anonymity issue with MANET. However, it also comes with its own shortcomings. One of them is access control enforcement. To tackle this issue, a new naming scheme for contents transmitted in ICN networks is presented. This scheme is based on a new Attribute-Based Encryption (ABE) algorithm. It enforces access control in ICN with minimum requirements on additional network components.



Following the research work on ABE, an important function, delegation, exhibits a potential security issue. In traditional ABE schemes, Ciphertext-Policy ABE (CP-ABE), a user is able to generate a subset of authentic attribute key components for other users using delegation function. This capability is not monitored or controlled by the trusted third party (TTP) in the cryptosystem. A direct threat caused from this issue is that any user may intentionally or unintentionally lower the standards for attribute assignments. Unauthorized users/attackers may be able to obtain their desired attributes through a delegation party instead of directly from the TTP. As the third part of work presented in this manuscript, a three-level delegation restriction architecture is proposed. Furthermore, a delegation restriction scheme following this architecture is also presented. This scheme allows the TTP to have full control on the delegation function of all its direct users.
ContributorsLi, Bing (Author) / Huang, Dijiang (Thesis advisor) / Xue, Guoliang (Committee member) / Ahn, Gail-Joon (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)
Created2016
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Description
Mobile Augmented Reality (MAR) is a portable, powerful, and suitable technology that integrates 3D virtual content into the physical world in real-time. It has been implemented for multiple intents as it enhances people’s interaction, e.g., shopping, entertainment, gaming, etc. Thus, MAR is expected to grow at a tremendous rate in

Mobile Augmented Reality (MAR) is a portable, powerful, and suitable technology that integrates 3D virtual content into the physical world in real-time. It has been implemented for multiple intents as it enhances people’s interaction, e.g., shopping, entertainment, gaming, etc. Thus, MAR is expected to grow at a tremendous rate in the upcoming years, as its popularity via mobile devices has increased. But, unfortunately, the applications that implement MAR, hereby referred to as MAR-Apps, bear security issues. Such are imaged in worldwide recorded incidents caused by MAR-Apps, e.g., robberies, authorities requesting banning MAR at specific locations, etc. To further explore these concerns, a case study analyzed several MAR-Apps available in the market to identify the security problems in MAR. As a result of this study, the threats found were classified into three categories. First, Space Invasion implies the intrusive modification through MAR of sensitive spaces, e.g., hospitals, memorials, etc. Then, Space Affectation means the degradation of users’ experience via interaction with undesirable MAR or malicious entities. Finally, MAR-Apps mishandling sensitive data leads to Privacy Leaks. SpaceMediator, a proof-of-concept MAR-App that imitates the well-known and successful MAR-App Pokémon GO, implements the solution approach of a Policy-Governed MAR-App, which assists in preventing the aforementioned mentioned security issues. Furthermore, its feasibility is evaluated through a user study with 40 participants. As a result, uncovering understandability over the security issues as participants recognized and prevented them with success rates as high as 92.50%. Furthermore, there is an enriched interest in Policy-Governed MAR-Apps as 87.50% of participants agreed with restricted MAR-Apps within sensitive spaces, and 82.50% would implement constraints in MAR-Apps. These promising results encourage adopting the Policy-Governed solution approach in future MAR-Apps.
ContributorsClaramunt, Luis Manuel (Author) / Ahn, Gail-Joon (Thesis advisor) / Rubio-Medrano, Carlos E (Committee member) / Baek, Jaejong (Committee member) / Arizona State University (Publisher)
Created2022