Computer Sciences Commons^™

On Static And Dynamic Partitioning Behavior Of Large-Scale Networks, Zhongmei Yao, Derek Leonard, Xiaoming Wang, Dmitri Loguinov

Computer Science Faculty Publications

In this paper, we analyze the problem of network disconnection in the context of large-scale P2P networks and understand how both static and dynamic patterns of node failure affect the resilience of such graphs. We start by applying classical results from random graph theory to show that a large variety of deterministic and random P2P graphs almost surely (i.e., with probability 1 − o(1)) remain connected under random failure if and only if they have no isolated nodes. This simple, yet powerful, result subsequently allows us to derive in closed-form the probability that a P2P network develops isolated nodes, and …

A Model Based Fault Detection And Prognostic Scheme For Uncertain Nonlinear Discrete-Time Systems, Balaje T. Thumati, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A new fault detection and prognostics (FDP) framework is introduced for uncertain nonlinear discrete time system by using a discrete-time nonlinear estimator which consists of an online approximator. A fault is detected by monitoring the deviation of the system output with that of the estimator output. Prior to the occurrence of the fault, this online approximator learns the system uncertainty. In the event of a fault, the online approximator learns both the system uncertainty and the fault dynamics. A stable parameter update law in discrete-time is developed to tune the parameters of the online approximator. This update law is also …

A Novel Technique Of Network Auditability With Managers In The Loop, Rian Shelley

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Network management requires a large amount of knowledge about the network. In particular, knowledge about used network addresses, access time, and topology is useful. In a network composed of managed devices, much of the data necessary can come from simple network management protocol (SNMP) queries. Other data can come from other databases, or analysis of existing data. In particular, layer-two network topology can be determined by analyzing the mac address forwarding tables of layer-two devices. The layer-two topology can be merged with a layer-three topology to generate a complete topology of the network. This information is useless unless it is …

Computing For The Masses: Extending The Computer Science Curriculum With Information Technology Literacy, Jorge Pérez, Meg C. Murray

Faculty Articles

Enrollments in computer science programs continue to drop as demand for workers skilled in computing increases. Information technology scholars face the ironic challenge of attracting more students into computing disciplines in the age of ubiquitous computing. This paper chronicles a decision by a department of computer science and information systems to offer an information technology literacy course as a service to its institution. Educational and curricular justifications for the course progressed in parallel with recognition of the course's strategic value to the department in the face of sharp declines in the number of students majoring in CS or IS. Following …

Neural Network Output Feedback Control Of A Quadrotor Uav, Jagannathan Sarangapani, Travis Alan Dierks

Electrical and Computer Engineering Faculty Research & Creative Works

A neural network (NN) based output feedback controller for a quadrotor unmanned aerial vehicle (UAV) is proposed. The NNs are utilized in the observer and for generating virtual and actual control inputs, respectively, where the NNs learn the nonlinear dynamics of the UAV online including uncertain nonlinear terms like aerodynamic friction and blade flapping. It is shown using Lyapunov theory that the position, orientation, and velocity tracking errors, the virtual control and observer estimation errors, and the NN weight estimation errors for each NN are all semi-globally uniformly ultimately bounded (SGUUB) in the presence of bounded disturbances and NN functional …

Neural-Network-Based State Feedback Control Of A Nonlinear Discrete-Time System In Nonstrict Feedback Form, Pingan He, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a suite of adaptive neural network (NN) controllers is designed to deliver a desired tracking performance for the control of an unknown, second-order, nonlinear discrete-time system expressed in nonstrict feedback form. In the first approach, two feedforward NNs are employed in the controller with tracking error as the feedback variable whereas in the adaptive critic NN architecture, three feedforward NNs are used. In the adaptive critic architecture, two action NNs produce virtual and actual control inputs, respectively, whereas the third critic NN approximates certain strategic utility function and its output is employed for tuning action NN weights …

Group-Aware Stream Filtering For Bandwidth-Efficient Data Dissemination, Ming Li, David Kotz

Dartmouth Scholarship

In this paper we are concerned with disseminating high-volume data streams to many simultaneous applications over a low-bandwidth wireless mesh network. For bandwidth efficiency, we propose a group-aware stream filtering approach, used in conjunction with multicasting, that exploits two overlooked, yet important, properties of these applications: 1) many applications can tolerate some degree of “slack” in their data quality requirements, and 2) there may exist multiple subsets of the source data satisfying the quality needs of an application. We can thus choose the “best alternative” subset for each application to maximize the data overlap within the group to best benefit …

Tinytermite: A Secure Routing Algorithm, Joshua Lewis Patterson

Masters Theses and Doctoral Dissertations

In this thesis, we introduce TinyTermite. TinyTermite is a novel probabilistic routing algorithm that is secure against selective forwarding and replay attacks. We use suspicion pheromone to build a flexible map of possible compromised neighbors. As suspicion builds up and decays for each neighbor, TinyTermite is able to deal with uncertain stimulus and react properly. TinyTermite is fully implemented on TinyOS based Intel Mote 2 platform and the experiments were done to compare its performance with that of the traditional Termite algorithm. The experimental results show that TinyTermite is significantly more secure against replay and sinkhole attacks by lowering the …

Animated Database Courseware: Using Animations To Extend Conceptual Understanding Of Database Concepts, Meg Murray, Mario Guimaraes

Faculty Articles

Teaching abstract concepts can be best supported with supplemental instructional materials such as software animations. Visualization and animations have been shown to increase student motivation and help students develop deeper understandings. Through an NSF funded CCLI grant, a set of animations to support the teaching of database concepts is being developed and made freely available. Current modules available cover areas such as database design, interactive SQL, stored procedures and triggers, transactions and database security. In this paper, we provide an overview of the Animated Database Courseware (ADbC) as well as provide examples of how this software might be utilized in …

Making Sense Of Technology Trends In The Information Technology Landscape, Gediminas Adomavicius, Jesse C. Bockstedt, Alok Gupta, Robert J. Kauffman

Research Collection School Of Computing and Information Systems

A major problem for firms making information technology investment decisions is predicting and understanding the effects of future technological developments on the value of present technologies. Failure to adequately address this problem can result in wasted organization resources in acquiring, developing, managing, and training employees in the use of technologies that are short-lived and fail to produce adequate return on investment. The sheer number of available technologies and the complex set of relationships among them make IT landscape analysis extremely challenging. Most IT-consuming firms rely on third parties and suppliers for strategic recommendations on IT investments, which can lead to …

A Fast Pruned‐Extreme Learning Machine For Classification Problem, Hai-Jun Rong, Yew-Soon Ong, Ah-Hwee Tan, Zexuan Zhu

Research Collection School Of Computing and Information Systems

Extreme learning machine (ELM) represents one of the recent successful approaches in machine learning, particularly for performing pattern classification. One key strength of ELM is the significantly low computational time required for training new classifiers since the weights of the hidden and output nodes are randomly chosen and analytically determined, respectively. In this paper, we address the architectural design of the ELM classifier network, since too few/many hidden nodes employed would lead to underfitting/overfitting issues in pattern classification. In particular, we describe the proposed pruned-ELM (P-ELM) algorithm as a systematic and automated approach for designing ELM classifier network. P-ELM uses …

Efficient Client-To-Client Password Authenticated Key Exchange, Yanjiang Yang, Feng Bao, Robert H. Deng

Research Collection School Of Computing and Information Systems

With the rapid proliferation of client-to-client applications, PAKE (password authenticated key exchange) protocols in the client-to-client setting become increasingly important. In this paper, we propose an efficient client-to client PAKE protocol, which has much better performance than existing generic constructions. We also show that the proposed protocol is secure under a formal security model.

Cognitive Agents Integrating Rules And Reinforcement Learning For Context-Aware Decision Support, Teck-Hou Teng, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

While context-awareness has been found to be effective for decision support in complex domains, most of such decision support systems are hard-coded, incurring significant development efforts. To ease the knowledge acquisition bottleneck, this paper presents a class of cognitive agents based on self-organizing neural model known as TD-FALCON that integrates rules and learning for supporting context-aware decision making. Besides the ability to incorporate a priori knowledge in the form of symbolic propositional rules, TD-FALCON performs reinforcement learning (RL), enabling knowledge refinement and expansion through the interaction with its environment. The efficacy of the developed Context-Aware Decision Support (CaDS) system is …

Protecting Critical Infrastructure With Games Technology, Adrian Boeing, Martin Masek, Bill Bailey

Australian Information Warfare and Security Conference

It is widely recognised that there is a considerable gap in the protection of the national infrastructure. Trying to identify what is in fact ‘critical’ is proving to be very difficult as threats constantly evolve. An interactive prototyping tool is useful in playing out scenarios and simulating the effect of change, however existing simulators in the critical infrastructure area are typically limited in the visual representation and interactivity. To remedy this we propose the use of games technology. Through its use, critical infrastructure scenarios can be rapidly constructed, tested, and refined. In this paper, we highlight the features of games …

Information Sharing: Hackers Vs Law Enforcement, David P. Biros, Mark Weiser, Jim Burkman, Jason Nichols

Australian Information Warfare and Security Conference

The fields of information assurance and digital forensics continue to grow in both importance and complexity, spurred on by rapid advancement in digital crime. Contemporary law enforcement professionals facing such issues quickly discover that they cannot be successful while operating in a vacuum and turn to colleagues for assistance. However, there is a clear need for greater IT-based knowledge sharing capabilities amongst law enforcement organizations; an environment historically typified by a silo mentality. A number of efforts have attempted to provide such capabilities, only to be met with limited enthusiasm and difficulties in sustaining continued use. Conversely, the hacker community …

Security Metrics - A Critical Analysis Of Current Methods, Manwinder Kaur, Andy Jones

Australian Information Warfare and Security Conference

This paper documents and analyses a number of security metrics currently in popular use. These will include government standards and commercial methods of measuring security on networks. It will conclude with a critical look at some of the problems and challenges faced when using the metrics available today, and also with the development of new metrics.

Forensic And Anti-Forensic Techniques For Object Linking And Embedding 2 (Ole2)-Formatted Documents, Jason M. Daniels

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Common office documents provide significant opportunity for forensic and anti-forensic work. The Object Linking and Embedding 2 (OLE2) specification used primarily by Microsoft’s Office Suite contains unused or dead space regions that can be over written to hide covert channels of communication. This thesis describes a technique to detect those covert channels and also describes a different method of encoding that lowers the probability of detection.

The algorithm developed, called OleDetection, is based on the use of kurtosis and byte frequency distribution statistics to accurately identify OLE2 documents with covert channels. OleDetection is able to correctly identify 99.97 percent of …

Application Of Web Services To A Simulation Framework, Matthew Bennink

All Theses

The Joint Semi-Automated Forces (JSAF) simulator is an excellent tool for military training and a great testbed for new SAF behaviors. However, it has the drawback that behaviors must be ported into its own Finite State Machine (FSM) language. Web Services is a growing technology that seamlessly connects service providers to service consumers. This work attempts to merge these two technologies by modeling SAF behaviors as web services. The JSAF simulator is then modeled as a web service consumer.
This approach allows new Semi-Automated Forces (SAF) behaviors to be developed independently of the simulator, which provides the developer with greater …

Two Categories Of Refutation Decision Procedures For Classical And Intuitionistic Propositional Logic, Edward Doyle

All Dissertations

An automatic theorem prover is a computer program that proves theorems without the assistance of a human being. Theorem proving is an important basic tool in proving theorems in mathematics, establishing the correctness of computer programs, proving the correctness of communication protocols, and verifying integrated circuit designs.
This dissertation introduces two new categories of theorem provers, one for classical propositional logic and another for intuitionistic propositional logic. For each logic a container property and generalized algorithm are introduced.
Many methods have been developed over the years to prove theorems in propositional logic. This dissertation describes and presents example proofs for …

Sequence Alignment With Traceback On Reconfigurable Hardware, Scott Lloyd, Quinn O. Snell

Faculty Publications

Biological sequence alignment is an essential tool used in molecular biology and biomedical applications. The growing volume of genetic data and the complexity of sequence alignment present a challenge in obtaining alignment results in a timely manner. Known methods to accelerate alignment on reconfigurable hardware only address sequence comparison, limit the sequence length, or exhibit memory and I/O bottlenecks. A space-efficient, global sequence alignment algorithm and architecture is presented that accelerates the forward scan and traceback in hardware without memory and I/O limitations. With 256 processing elements in FPGA technology, a performance gain over 300 times that of a desktop …

An Evolutionary Approach To Image Compression In The Discrete Cosine Transform Domain, Benjamin E. Banham

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

This paper examines the application of genetic programming to image compression while working in the frequency domain. Several methods utilized by JPEG encoding are applied to the image before utilizing a genetic programming system. Specifically, the discrete cosine transform (DCT) is applied to the original image, followed by the zig-zag scanning of DCT coefficients. The genetic programming system is finally applied to the one-dimensional array resulting from the zig-zag scan. The research takes an existing genetic programming system developed for the spatial domain and develops DCT domain functionality. The results from the DCT domain-based genetic programming system are compared with …

Automated Data Type Identification And Localization Using Statistical Analysis Data Identification, Sarah Jean Moody

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

This research presents a new and unique technique called SÁDI, statistical analysis data identification, for identifying the type of data on a digital device and its storage format based on data type, specifically the values of the bytes representing the data being examined. This research incorporates the automation required for specialized data identification tools to be useful and applicable in real-world applications. The SÁDI technique utilizes the byte values of the data stored on a digital storage device in such a way that the accuracy of the technique does not rely solely on the potentially misleading metadata information but rather …

Scaling Up Multi-Agent Reinforcement Learning In Complex Domains, Dan Xiao, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

TD-FALCON (Temporal Difference - Fusion Architecture for Learning, COgnition, and Navigation) is a class of self-organizing neural networks that incorporates Temporal Difference (TD) methods for real-time reinforcement learning. In this paper, we present two strategies, i.e. policy sharing and neighboring-agent mechanism, to further improve the learning efficiency of TD-FALCON in complex multi-agent domains. Through experiments on a traffic control problem domain and the herding task, we demonstrate that those strategies enable TD-FALCON to remain functional and adaptable in complex multi-agent domains

Ambiguous Optimistic Fair Exchange, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo

Research Collection School Of Computing and Information Systems

Optimistic fair exchange (OFE) is a protocol for solving the problem of exchanging items or services in a fair manner between two parties, a signer and a verifier, with the help of an arbitrator which is called in only when a dispute happens between the two parties. In almost all the previous work on OFE, after obtaining a partial signature from the signer, the verifier can present it to others and show that the signer has indeed committed itself to something corresponding to the partial signature even prior to the completion of the transaction. In some scenarios, this capability given …

Adoption Of 3-D Virtual Worlds For Education, X. Chen, Keng Siau, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

As an emerging phenomenon, virtual world education is rarely researched in MIS literature. With stiff competition among institutions using virtual worlds for education, a legitimate research question is: What factors influence students’ intention to adopt 3-D virtual world environment for their education needs? Drawing on existing technology acceptance models and studies in other IS contexts, we developed a model to predict students’ acceptance of a 3-D virtual world education environment and plan to empirically test the model using survey data collected from college students. From the academic research perspective, studies on the use of the new technology for education will …

Text Cube: Computing Ir Measures For Multidimensional Text Database Analysis, Cindy Xinde Lin, Bolin Ding, Jiawei Han, Feida Zhu, Bo Zhao

Research Collection School Of Computing and Information Systems

Since Jim Gray introduced the concept of ”data cube” in 1997, data cube, associated with online analytical processing (OLAP), has become a driving engine in data warehouse industry. Because the boom of Internet has given rise to an ever increasing amount of text data associated with other multidimensional information, it is natural to propose a data cube model that integrates the power of traditional OLAP and IR techniques for text. In this paper, we propose a Text-Cube model on multidimensional text database and study effective OLAP over such data. Two kinds of hierarchies are distinguishable inside: dimensional hierarchy and term …

Robust Regularized Kernel Regression, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Robust regression techniques are critical to fitting data with noise in real-world applications. Most previous work of robust kernel regression is usually formulated into a dual form, which is then solved by some quadratic program solver consequently. In this correspondence, we propose a new formulation for robust regularized kernel regression under the theoretical framework of regularization networks and then tackle the optimization problem directly in the primal. We show that the primal and dual approaches are equivalent to achieving similar regression performance, but the primal formulation is more efficient and easier to be implemented than the dual one. Different from …

Distributing Complementary Resources Across Multiple Periods With Stochastic Demand, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments, we show that under stochastic conditions the performance variation of the process decreases as the time frame length (time …

Mobitop: Accessing Hierarchically Organized Georeferenced Multimedia Annotations, Thi Nhu Quynh Kim, Khasfariyati Razikin, Dion Hoe-Lian Goh, Quang Minh Nguyen, Ee Peng Lim

Research Collection School Of Computing and Information Systems

We introduce MobiTOP, a map-based interface for accessing hierarchically organized georeferenced annotations. Each annotation contains multimedia content associated with a location, and users are able to annotate existing annotations, in effect creating a hierarchy.

On Visualizing Heterogeneous Semantic Networks From Multiple Data Sources, Maureen Maureen, Aixin Sun, Ee Peng Lim, Anwitaman Datta, Kuiyu Chang

Research Collection School Of Computing and Information Systems

In this paper, we focus on the visualization of heterogeneous semantic networks obtained from multiple data sources. A semantic network comprising a set of entities and relationships is often used for representing knowledge derived from textual data or database records. Although the semantic networks created for the same domain at different data sources may cover a similar set of entities, these networks could also be very different because of naming conventions, coverage, view points, and other reasons. Since digital libraries often contain data from multiple sources, we propose a visualization tool to integrate and analyze the differences among multiple social …