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- All Subjects: Computer Science
- Creators: Sen, Arunabha
- Member of: Theses and Dissertations
- Status: Published
Description
While network problems have been addressed using a central administrative domain with a single objective, the devices in most networks are actually not owned by a single entity but by many individual entities. These entities make their decisions independently and selfishly, and maybe cooperate with a small group of other entities only when this form of coalition yields a better return. The interaction among multiple independent decision-makers necessitates the use of game theory, including economic notions related to markets and incentives. In this dissertation, we are interested in modeling, analyzing, addressing network problems caused by the selfish behavior of network entities. First, we study how the selfish behavior of network entities affects the system performance while users are competing for limited resource. For this resource allocation domain, we aim to study the selfish routing problem in networks with fair queuing on links, the relay assignment problem in cooperative networks, and the channel allocation problem in wireless networks. Another important aspect of this dissertation is the study of designing efficient mechanisms to incentivize network entities to achieve certain system objective. For this incentive mechanism domain, we aim to motivate wireless devices to serve as relays for cooperative communication, and to recruit smartphones for crowdsourcing. In addition, we apply different game theoretic approaches to problems in security and privacy domain. For this domain, we aim to analyze how a user could defend against a smart jammer, who can quickly learn about the user's transmission power. We also design mechanisms to encourage mobile phone users to participate in location privacy protection, in order to achieve k-anonymity.
ContributorsYang, Dejun (Author) / Xue, Guoliang (Thesis advisor) / Richa, Andrea (Committee member) / Sen, Arunabha (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2013
Description
Peer-to-peer systems are known to be vulnerable to the Sybil attack. The lack of a central authority allows a malicious user to create many fake identities (called Sybil nodes) pretending to be independent honest nodes. The goal of the malicious user is to influence the system on his/her behalf. In order to detect the Sybil nodes and prevent the attack, a reputation system is used for the nodes, built through observing its interactions with its peers. The construction makes every node a part of a distributed authority that keeps records on the reputation and behavior of the nodes. Records of interactions between nodes are broadcast by the interacting nodes and honest reporting proves to be a Nash Equilibrium for correct (non-Sybil) nodes. In this research is argued that in realistic communication schedule scenarios, simple graph-theoretic queries such as the computation of Strongly Connected Components and Densest Subgraphs, help in exposing those nodes most likely to be Sybil, which are then proved to be Sybil or not through a direct test executed by some peers.
ContributorsCárdenas-Haro, José Antonio (Author) / Konjevod, Goran (Thesis advisor) / Richa, Andréa W. (Thesis advisor) / Sen, Arunabha (Committee member) / Xue, Guoliang (Committee member) / Arizona State University (Publisher)
Created2010
Description
Text search is a very useful way of retrieving document information from a particular website. The public generally use internet search engines over the local enterprise search engines, because the enterprise content is not cross linked and does not follow a page rank algorithm. On the other hand the enterprise search engine uses metadata information, which allows the user to specify the conditions that any retrieved document should meet. Therefore, using metadata information for searching will also be very useful. My thesis aims on developing an enterprise search engine using metadata information by providing advanced features like faceted navigation. The search engine data was extracted from various Indonesian web sources. Metadata information like person, organization, location, and sentiment analytic keyword entities should be tagged in each document to provide facet search capability. A shallow parsing technique like named entity recognizer is used for this purpose. There are more than 1500 entities that have been tagged in this process. These documents have been successfully converted into XML format and are indexed with "Apache Solr". It is an open source enterprise search engine with full text search and faceted search capabilities. The entities will be helpful for users to specify conditions and search faster through the large collection of documents. The user is assured results by clicking on a metadata condition. Since the sentiment analytic keywords are tagged with positive and negative values, social scientists can use these results to check for overlapping or conflicting organizations and ideologies. In addition, this tool is the first of its kind for the Indonesian language. The results are fetched much faster and with better accuracy.
ContributorsSanaka, Srinivasa Raviteja (Author) / Davulcu, Hasan (Thesis advisor) / Sen, Arunabha (Committee member) / Taylor, Thomas (Committee member) / Arizona State University (Publisher)
Created2010
Description
Today, many wireless networks are single-channel systems. However, as the interest in wireless services increases, the contention by nodes to occupy the medium is more intense and interference worsens. One direction with the potential to increase system throughput is multi-channel systems. Multi-channel systems have been shown to reduce collisions and increase concurrency thus producing better bandwidth usage. However, the well-known hidden- and exposed-terminal problems inherited from single-channel systems remain, and a new channel selection problem is introduced. In this dissertation, Multi-channel medium access control (MAC) protocols are proposed for mobile ad hoc networks (MANETs) for nodes equipped with a single half-duplex transceiver, using more sophisticated physical layer technologies. These include code division multiple access (CDMA), orthogonal frequency division multiple access (OFDMA), and diversity. CDMA increases channel reuse, while OFDMA enables communication by multiple users in parallel. There is a challenge to using each technology in MANETs, where there is no fixed infrastructure or centralized control. CDMA suffers from the near-far problem, while OFDMA requires channel synchronization to decode the signal. As a result CDMA and OFDMA are not yet widely used. Cooperative (diversity) mechanisms provide vital information to facilitate communication set-up between source-destination node pairs and help overcome limitations of physical layer technologies in MANETs. In this dissertation, the Cooperative CDMA-based Multi-channel MAC (CCM-MAC) protocol uses CDMA to enable concurrent transmissions on each channel. The Power-controlled CDMA-based Multi-channel MAC (PCC-MAC) protocol uses transmission power control at each node and mitigates collisions of control packets on the control channel by using different sizes of the spreading factor to have different processing gains for the control signals. The Cooperative Dual-access Multi-channel MAC (CDM-MAC) protocol combines the use of OFDMA and CDMA and minimizes channel interference by a resolvable balanced incomplete block design (BIBD). In each protocol, cooperating nodes help reduce the incidence of the multi-channel hidden- and exposed-terminal and help address the near-far problem of CDMA by supplying information. Simulation results show that each of the proposed protocols achieve significantly better system performance when compared to IEEE 802.11, other multi-channel protocols, and another protocol CDMA-based.
ContributorsMoon, Yuhan (Author) / Syrotiuk, Violet R. (Thesis advisor) / Huang, Dijiang (Committee member) / Reisslein, Martin (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2010
Description
For systems having computers as a significant component, it becomes a critical task to identify the potential threats that the users of the system can present, while being both inside and outside the system. One of the most important factors that differentiate an insider from an outsider is the fact that the insider being a part of the system, owns privileges that enable him/her access to the resources and processes of the system through valid capabilities. An insider with malicious intent can potentially be more damaging compared to outsiders. The above differences help to understand the notion and scope of an insider.
The significant loss to organizations due to the failure to detect and mitigate the insider threat has resulted in an increased interest in insider threat detection. The well-studied effective techniques proposed for defending against attacks by outsiders have not been proven successful against insider attacks. Although a number of security policies and models to deal with the insider threat have been developed, the approach taken by most organizations is the use of audit logs after the attack has taken place. Such approaches are inspired by academic research proposals to address the problem by tracking activities of the insider in the system. Although tracking and logging are important, it is argued that they are not sufficient. Thus, the necessity to predict the potential damage of an insider is considered to help build a stronger evaluation and mitigation strategy for the insider attack. In this thesis, the question that seeks to be answered is the following: `Considering the relationships that exist between the insiders and their role, their access to the resources and the resource set, what is the potential damage that an insider can cause?'
A general system model is introduced that can capture general insider attacks including those documented by Computer Emergency Response Team (CERT) for the Software Engineering Institute (SEI). Further, initial formulations of the damage potential for leakage and availability in the model is introduced. The model usefulness is shown by expressing 14 of actual attacks in the model and show how for each case the attack could have been mitigated.
The significant loss to organizations due to the failure to detect and mitigate the insider threat has resulted in an increased interest in insider threat detection. The well-studied effective techniques proposed for defending against attacks by outsiders have not been proven successful against insider attacks. Although a number of security policies and models to deal with the insider threat have been developed, the approach taken by most organizations is the use of audit logs after the attack has taken place. Such approaches are inspired by academic research proposals to address the problem by tracking activities of the insider in the system. Although tracking and logging are important, it is argued that they are not sufficient. Thus, the necessity to predict the potential damage of an insider is considered to help build a stronger evaluation and mitigation strategy for the insider attack. In this thesis, the question that seeks to be answered is the following: `Considering the relationships that exist between the insiders and their role, their access to the resources and the resource set, what is the potential damage that an insider can cause?'
A general system model is introduced that can capture general insider attacks including those documented by Computer Emergency Response Team (CERT) for the Software Engineering Institute (SEI). Further, initial formulations of the damage potential for leakage and availability in the model is introduced. The model usefulness is shown by expressing 14 of actual attacks in the model and show how for each case the attack could have been mitigated.
ContributorsNolastname, Sharad (Author) / Bazzi, Rida (Thesis advisor) / Sen, Arunabha (Committee member) / Doupe, Adam (Committee member) / Arizona State University (Publisher)
Created2019
Description
Distributed systems are prone to attacks, called Sybil attacks, wherein an adversary may generate an unbounded number of bogus identities to gain control over the system. In this thesis, an algorithm, DownhillFlow, for mitigating such attacks is presented and
tested experimentally. The trust rankings produced by the algorithm are significantly better than those of the distributed SybilGuard protocol and only slightly worse than those of the best-known Sybil defense algorithm, ACL. The results obtained for ACL are
consistent with those obtained in previous studies. The running times of the algorithms are also tested and two results are obtained: first, DownhillFlow’s running time is found to be significantly faster than any existing algorithm including ACL, terminating in
slightly over one second on the 300,000-node DBLP graph. This allows it to be used in settings such as dynamic networks as-is with no additional functionality needed. Second, when ACL is configured such that it matches DownhillFlow’s speed, it fails to recognize
large portions of the input graphs and its accuracy among the portion of the graphs it does recognize becomes lower than that of DownhillFlow.
tested experimentally. The trust rankings produced by the algorithm are significantly better than those of the distributed SybilGuard protocol and only slightly worse than those of the best-known Sybil defense algorithm, ACL. The results obtained for ACL are
consistent with those obtained in previous studies. The running times of the algorithms are also tested and two results are obtained: first, DownhillFlow’s running time is found to be significantly faster than any existing algorithm including ACL, terminating in
slightly over one second on the 300,000-node DBLP graph. This allows it to be used in settings such as dynamic networks as-is with no additional functionality needed. Second, when ACL is configured such that it matches DownhillFlow’s speed, it fails to recognize
large portions of the input graphs and its accuracy among the portion of the graphs it does recognize becomes lower than that of DownhillFlow.
ContributorsBradley, Michael (Author) / Bazzi, Rida (Thesis advisor) / Richa, Andrea (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2018
Description
Realizing the applications of Internet of Things (IoT) with the goal of achieving a more efficient and automated world requires billions of connected smart devices and the minimization of hardware cost in these devices. As a result, many IoT devices do not have sufficient resources to support various protocols required in many IoT applications. Because of this, new protocols have been introduced to support the integration of these devices. One of these protocols is the increasingly popular routing protocol for low-power and lossy networks (RPL). However, this protocol is well known to attract blackhole and sinkhole attacks and cause serious difficulties when using more computationally intensive techniques to protect against these attacks, such as intrusion detection systems and rank authentication schemes. In this paper, an effective approach is presented to protect RPL networks against blackhole attacks. The approach does not address sinkhole attacks because they cause low damage and are often used along blackhole attacks and can be detected when blackhole attaches are detected. This approach uses the feature of multiple parents per node and a parent evaluation system enabling nodes to select more reliable routes. Simulations have been conducted, compared to existing approaches this approach would provide better protection against blackhole attacks with much lower overheads for small RPL networks.
ContributorsSanders, Kent (Author) / Yau, Stephen S (Thesis advisor) / Huang, Dijiang (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2021
Description
Social media is a medium that contains rich information which has been shared by many users every second every day. This information can be utilized for various outcomes such as understanding user behaviors, learning the effect of social media on a community, and developing a decision-making system based on the information available. With the growing popularity of social networking sites, people can freely express their opinions and feelings which results in a tremendous amount of user-generated data. The rich amount of social media data has opened the path for researchers to study and understand the users’ behaviors and mental health conditions. Several studies have shown that social media provides a means to capture an individual state of mind. Given the social media data and related work in this field, this work studies the scope of users’ discussion among online mental health communities. In the first part of this dissertation, this work focuses on the role of social media on mental health among sexual abuse community. It employs natural language processing techniques to extract topics of responses, examine how diverse these topics are to answer research questions such as whether responses are limited to emotional support; if not, what other topics are; what the diversity of topics manifests; how online response differs from traditional response found in a physical world. To answer these questions, this work extracts Reddit posts on rape to understand the nature of user responses for this stigmatized topic. In the second part of this dissertation, this work expands to a broader range of online communities. In particular, it investigates the potential roles of social media on mental health among five major communities, i.e., trauma and abuse community, psychosis and anxiety community, compulsive disorders community, coping and therapy community, and mood disorders community. This work studies how people interact with each other in each of these communities and what these online forums provide a resource to users who seek help. To understand users’ behaviors, this work extracts Reddit posts on 52 related subcommunities and analyzes the linguistic behavior of each community. Experiments in this dissertation show that Reddit is a good medium for users with mental health issues to find related helpful resources. Another interesting observation is an interesting topic cluster from users’ posts which shows that discussion and communication among users help individuals to find proper resources for their problem. Moreover, results show that the anonymity of users in Reddit allows them to have discussions about different topics beyond social support such as financial and religious support.
ContributorsKamarudin, Nur Shazwani (Author) / Liu, Huan (Thesis advisor) / Davulcu, Hasan (Committee member) / Sen, Arunabha (Committee member) / Hu, Xia (Committee member) / Arizona State University (Publisher)
Created2019
Description
Quantum computing holds the potential to revolutionize various industries by solving problems that classical computers cannot solve efficiently. However, building quantum computers is still in its infancy, and simulators are currently the best available option to explore the potential of quantum computing. Therefore, developing comprehensive benchmarking suites for quantum computing simulators is essential to evaluate their performance and guide the development of future quantum algorithms and hardware. This study presents a systematic evaluation of quantum computing simulators’ performance using a benchmarking suite. The benchmarking suite is designed to meet the industry-standard performance benchmarks established by the Defense Advanced Research Projects Agency (DARPA) and includes standardized test data and comparison metrics that encompass a wide range of applications, deep neural network models, and optimization techniques. The thesis is divided into two parts to cover basic quantum algorithms and variational quantum algorithms for practical machine-learning tasks. In the first part, the run time and memory performance of quantum computing simulators are analyzed using basic quantum algorithms. The performance is evaluated using standardized test data and comparison metrics that cover fundamental quantum algorithms, including Quantum Fourier Transform (QFT), Inverse Quantum Fourier Transform (IQFT), Quantum Adder, and Variational Quantum Eigensolver (VQE). The analysis provides valuable insights into the simulators’ strengths and weaknesses and highlights the need for further development to enhance their performance. In the second part, benchmarks are developed using variational quantum algorithms for practical machine learning tasks such as image classification, natural language processing, and recommendation. The benchmarks address several unique challenges posed by benchmarking quantum machine learning (QML), including the effect of optimizations on time-to-solution, the stochastic nature of training, the inclusion of hybrid quantum-classical layers, and the diversity of software and hardware systems. The findings offer valuable insights into the simulators’ ability to solve practical machine-learning tasks and pinpoint areas for future research and enhancement. In conclusion, this study provides a rigorous evaluation of quantum computing simulators’ performance using a benchmarking suite that meets industry-standard performance benchmarks.
ContributorsSathyakumar, Rajesh (Author) / Spanias, Andreas (Thesis advisor) / Sen, Arunabha (Thesis advisor) / Dasarathy, Gautam (Committee member) / Arizona State University (Publisher)
Created2023
Description
Water, energy, and food are essential resources to sustain the development of the society. The Food-Energy-Water Nexus (FEW-Nexus) must account for synergies and trade-offs among these resources. The nexus concept highlights the importance of integrative solutions that secure supplies to meet demands sustainably. The existing frameworks and tools do not focus on formal model composability, a key capability for creating simulations created from separately developed models. The Knowledge Interchange Broker (KIB) approach is used to model the interactions among models to achieve composition flexibility for the FEW-Nexus.Domain experts generally use the Water Evaluation and Planning (WEAP) and Low Emissions Analysis Platform (LEAP) systems to study water and energy systems, respectively. The food part of FEW systems can be modeled inside the WEAP system. An internal linkage mechanism is available for combining and simulating WEAP and LEAP models. This mechanism is used for the validation and performance evaluation of independent modeling and simulation proposed in this research. The Componentized WEAP and LEAP RESTful frameworks are component-based representations for the legacy and closed-source WEAP and LEAP systems. These modularized systems simplify their use with other simulation frameworks.
This research proposes two interaction model frameworks based on the Knowledge Interchange Broker approach. First, an Algorithmic Interaction Model (Algorithmic-IM) was developed to integrate the WEAP and LEAP models. The Algorithmic-IM model can be defined via programming language and has a fixed cyclic execution protocol. However, this approach has tightly interwoven the interaction model with its execution and has limited support for flexibly creating model hierarchies. To overcome these restrictions, the system-theoretic Parallel DEVS formalism is used to develop a DEVS-Based Interaction Model (DEVS-IM). As in the Algorithmic-IM, the DEVS-IM is implemented as a RESTful framework, uses MongoDB for defining structural DEVS models, and supports automatic code generation for the DEVSSuite
simulator. The DEVS-IM offers modular, hierarchical structural modeling, reusability, flexibility, and maintainability for integrating disparate systems.
The Phoenix Active Management Area (AMA) is used to demonstrate the real-world application of the proposed research. Furthermore, the correctness and performance of the presented frameworks in this research are evaluated using the Phoenix-AMA model.
ContributorsFard, Mostafa D (Author) / Sarjoughian, Hessam S (Thesis advisor) / Barton, Michael (Committee member) / Sen, Arunabha (Committee member) / Zhao, Ming (Committee member) / Arizona State University (Publisher)
Created2023