Computer Sciences Commons^™

Coherent Phrase Model For Efficient Image Near-Duplicate Retrieval, Yiqun Hu, Xiangang Cheng, Liang-Tien Chia, Xing Xie, Deepu Rajan, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

This paper presents an efficient and effective solution for retrieving image near-duplicate (IND) from image database. We introduce the coherent phrase model which incorporates the coherency of local regions to reduce the quantization error of the bag-of-words (BoW) model. In this model, local regions are characterized by visual phrase of multiple descriptors instead of visual word of single descriptor. We propose two types of visual phrase to encode the coherency in feature and spatial domain, respectively. The proposed model reduces the number of false matches by using this coherency and generates sparse representations of images. Compared to other method, the …

Object Oriented Program Correctness With Oosiml, José M. Garrido

Faculty Articles

Software reliability depends on program correctness and robustness and these are extremely important in developing high-quality software. Correctness is also essential when considering aspects of software security. However, experience applying these concepts, associated methods, and supporting software with Eiffel and Java have shown that students find some diffculty learning program correctness and in learning the software tools provided. We have developed an experimental language, OOSimL, that includes an assertion notation similar to that of Eiffel but which has much more flexibility, and that provides the same semantics as Java.

The first part of this paper provides an overview of concepts …

Gpu-Accelerated Hierarchical Dense Correspondence For Real-Time Aerial Video Processing, Stephen Cluff, Bryan S. Morse, Jonathan D. Cohen, Mark Duchaineau

Faculty Publications

Video from aerial surveillance can provide a rich source of data for many applications and can be enhanced for display and analysis through such methods as mosaic construction, super-resolution, and mover detection. All of these methods require accurate frame-to-frame registration, which for live use must be performed in real time. In many situations, scene parallax may make alignment using global transformations impossible or error-prone, limiting the performance of subsequent processing and applications. For these cases, dense (per-pixel) correspondence is required, but this can be computationally prohibitive. This paper presents a hierarchical dense correspondence algorithm designed for implementation on graphics processing …

Managing Supply Uncertainty With An Information Market, Zhiling Guo, Fang Fang, Andrew B. Whinston

Research Collection School Of Computing and Information Systems

We propose a market-based information aggregation mechanism to manage the supply side uncertainty in the supply chain. In our analytical model, a simple supply chain consists of a group of retailers who order a homogeneous product from two suppliers. The two suppliers differ in their ability to fulfill orders – one always delivers orders and the other fulfills orders probabilistically. We model the supply chain decisions as a Stackelberg game where the supplier who has uncertain reliability decides a wholesale price before the retailers who independently receive signals about the supplier’s reliability determine their sourcing strategies. We then propose an …

Enabling Secure Secret Updating For Unidirectional Key Distribution In Rfid-Enabled Supply Chains, Shaoying Cai, Tieyan Li, Changshe Ma, Yingjiu Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

In USENIX Security 08, Juels, Pappu and Parno proposed a secret sharing based mechanism to alleviate the key distribution problem in RFID-enabled supply chains. Compared to existing pseudonym based RFID protocols, the secret sharing based solution is more suitable for RFID-enabled supply chains since it does not require a database of keys be distributed among supply chain parties for secure ownership transfer of RFID tags. However, this mechanism cannot resist tag tracking and tag counterfeiting attacks in supply chain systems. It is also not convenient for downstream supply chain parties to adjust the size of RFID tag collections in recovering …

On The Untraceability Of Anonymous Rfid Authentication Protocol With Constant Key-Lookup, Bing Liang, Yingjiu Li, Tieyan Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

In ASIACCS'08, Burmester, Medeiros and Motta proposed an anonymous RFID authentication protocol (BMM protocol [2]) that preserves the security and privacy properties, and achieves better scalability compared with other contemporary approaches. We analyze BMM protocol and find that some of security properties (especial untraceability) are not fulfilled as originally claimed. We consider a subtle attack, in which an adversary can manipulate the messages transmitted between a tag and a reader for several continuous protocol runs, and can successfully trace the tag after these interactions. Our attack works under a weak adversary model, in which an adversary can eavesdrop, intercept and …

To Trust Or Not To Trust? Predicting Online Trusts Using Trust Antecedent Framework, Viet-An Nguyen, Ee Peng Lim, Jing Jiang, Aixin Sun

Research Collection School Of Computing and Information Systems

This paper analyzes the trustor and trustee factors that lead to inter-personal trust using a well studied Trust Antecedent framework in management science. To apply these factors to trust ranking problem in online rating systems, we derive features that correspond to each factor and develop different trust ranking models. The advantage of this approach is that features relevant to trust can be systematically derived so as to achieve good prediction accuracy. Through a series of experiments on real data from Epinions, we show that even a simple model using the derived features yields good accuracy and outperforms MoleTrust, a trust …

Learning Bregman Distance Functions And Its Application For Semi-Supervised Clustering, Lei Wu, Rong Jin, Steven C. H. Hoi, Jianke Zhu, Nenghai Yu

Research Collection School Of Computing and Information Systems

Learning distance functions with side information plays a key role in many machine learning and data mining applications. Conventional approaches often assume a Mahalanobis distance function. These approaches are limited in two aspects: (i) they are computationally expensive (even infeasible) for high dimensional data because the size of the metric is in the square of dimensionality; (ii) they assume a fixed metric for the entire input space and therefore are unable to handle heterogeneous data. In this paper, we propose a novel scheme that learns nonlinear Bregman distance functions from side information using a nonparametric approach that is similar to …

Cyber Attacks: Does Physical Boundary Matter?, Qiu-Hong Wang, Seung-Hyun Kim

Research Collection School Of Computing and Information Systems

Information security issues are characterized with interdependence. Particularly, cyber criminals can easily cross national boundaries and exploit jurisdictional limitations between countries. Thus, whether cyber attacks are spatially autocorrelated is a strategic issue for government authorities and a tactic issue for insurance companies. Through an empirical study of cyber attacks across 62 countries during the period 2003-2007, we find little evidence on the spatial autocorrelation of cyber attacks at any week. However, after considering economic opportunity, IT infrastructure, international collaboration in enforcement and conventional crimes, we find strong evidence that cyber attacks were indeed spatially autocorrelated as they moved over time. …

Evaluating Head Gestures For Panning 2-D Spatial Information, Matthew O. Derry

Master's Theses

New, often free, spatial information applications such as mapping tools, topological imaging, and geographic information systems are becoming increasingly available to the average computer user. These systems, which were once available only to government, scholastic, and corporate institutions with highly skilled operators, are driving a need for new and innovative ways for the average user to navigate and control spatial information intuitively, accurately, and efficiently. Gestures provide a method of control that is well suited to navigating the large datasets often associated with spatial information applications. Several different types of gestures and different applications that navigate spatial data are examined. …

Duol: A Double Updating Approach For Online Learning, Peilin Zhao, Steven C. H. Hoi, Rong Jin

Research Collection School Of Computing and Information Systems

In most online learning algorithms, the weights assigned to the misclassified examples (or support vectors) remain unchanged during the entire learning process. This is clearly insufficient since when a new misclassified example is added to the pool of support vectors, we generally expect it to affect the weights for the existing support vectors. In this paper, we propose a new online learning method, termed Double Updating Online Learning, or DUOL for short. Instead of only assigning a fixed weight to the misclassified example received in current trial, the proposed online learning algorithm also tries to update the weight for one …

A Robust Damage Assessment Model For Corrupted Database Systems, Ge Fu, Hong Zhu, Yingjiu Li

Research Collection School Of Computing and Information Systems

An intrusion tolerant database uses damage assessment techniques to detect damage propagation scales in a corrupted database system. Traditional damage assessment approaches in a intrusion tolerant database system can only locate damages which are caused by reading corrupted data. In fact, there are many other damage spreading patterns that have not been considered in traditional damage assessment model. In this paper, we systematically analyze inter-transaction dependency relationships that have been neglected in the previous research and propose four different dependency relationships between transactions which may cause damage propagation. We extend existing damage assessment model based on the four novel dependency …

Wake Up Or Fall Asleep: Value Implication Of Trusted Computing, Nan Hu, Jianhui Huang, Ling Liu, Yingjiu Li, Dan Ma

Research Collection School Of Computing and Information Systems

More than 10 years have passed since trusted computing (TC) technology was introduced to the market; however, there is still no consensus about its value. The increasing importance of user and enterprise security and the security promised by TC, coupled with the increasing tension between the proponents and the opponents of TC, make it timely to investigate the value relevance of TC in terms of both capital market and accounting performance. Based on both price and volume studies, we found that news releases related to the adoption of the TC technology had no information content. All investors, regardless of whether …

Covert Botnet Design And Defense Analysis, Brandon Lyle Shirley

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Intrusion defense system (IDS) development has been largely reactionary in nature. This is especially troubling given that botnets are capable of compromising and controlling thousands of computers before security professionals develop a mitigation technique. As new exploits are created, new mitigation techniques are developed to detect infections and, where possible, remove them. This thesis breaks from this tradition of reacting to malware. Instead, it looks at possible malicious software models through analyzing existing defense systems for exploitable weaknesses.

First, this thesis presents a new specialized botnet that circumvents current network intrusion detection mechanisms. The proposed botnet coordinates external communication among …

Using Operator Teams For Supervisory Control, Jonathan M. Whetten

Theses and Dissertations

Robots and other automated systems have potential use in many different fields. As the scope of robot applications that robots are used for increases, there is a growing desire to have human operators manage multiple robots. Typical methods of enabling operators to multi-task in this way involve some combination of user interfaces that support human cognition and advanced robot autonomy. Our research explores a complementary method of managing multiple robots by utilizing operator teams. The evidence suggests that for appropriate task scenarios, two cooperating operators can be more than twice as effective as one operator working alone.

Classification, Clustering And Data-Mining Of Biological Data, Thomas Triplet

School of Computing: Dissertations, Theses, and Student Research

The proliferation of biological databases and the easy access enabled by the Internet is having a beneficial impact on biological sciences and transforming the way research is conducted. There are currently over 1,100 molecular biology databases dispersed throughout the Internet. However, very few of them integrate data from multiple sources. To assist in the functional and evolutionary analysis of the abundant number of novel proteins, we introduce the PROFESS (PROtein Function, Evolution, Structure and Sequence) database that integrates data from various biological sources. PROFESS is freely available at http://cse.unl.edu/~profess/. Our database is designed to be versatile and expandable and …

The Security Implication Of Multiple Observers In A Distributed System, Derek P. Ditch, Bruce M. Mcmillin

Computer Science Faculty Research & Creative Works

Confidentiality is an often overlooked, yet crucial point in the security analysis of a system. infrastructures take for granted that confidentiality is maintained through obfuscation by dissemination of information. This dissemination does indeed maintain the confidentiality of the system when only a small portion of the information can be obtained by an outside observer. However, when multiple observers collaboratively make observations, the confidential information can be revealed or even just partially revealed. If a team of attackers on a system can deduce enough information to successfully perform a crippling attack, the system could not be considered secure. This paper will …

Model-Checking Bndc Properties In Cyber-Physical Systems, Ravi Akella, Bruce M. Mcmillin

Computer Science Faculty Research & Creative Works

In Cyber-physical systems, which are the integrations of computational and physical processes, it is hard to realize certain security properties. Fundamentally, physically observable behavior leads to violations of confidentiality. We focus on analyzing certain non-interference-based security properties to ensure that interactions between the cyber and physical processes preserve confidentiality. a considerable barrier to this analysis is representing the physical system's interactions. in this paper, these physical system properties are encoded into a discrete event system and the combined Cyber-physical system is described using the process algebra SPA. the model checker, CoPS shows BNDC (Bisimulation based Non-Deducibility on Compositions) properties, which …

Dihomotopic Reduction Used In Deadlock Detection, David A. Cape, Bruce M. Mcmillin

Computer Science Faculty Research & Creative Works

Deadlock detection for concurrent programs has traditionally been accomplished by symbolic methods or by search of a state transition system. We examine an approach that uses geometric semantics involving the topological notion of dihomotopy to partition the state-space into components, after which the reduced state-space is exhaustively searched. Prior work partitioned the state-space inductively, but in this paper, we show that a recursive technique provides greater reduction of the size of the state transition system. as a result, we expect to see more efficient deadlock detection and eventually more efficient verification of some temporal properties for large problems if the …

Neural Network Control Of A Class Of Nonlinear Discrete Time Systems With Asymptotic Stability Guarantees, Balaje T. Thumati, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a single and multi-layer neural network (NN) controllers are developed for a class of nonlinear discrete time systems. under a mild assumption on the system uncertainties, which include unmodeled dynamics and bounded disturbances, by using novel weight update laws and a robust term, local asymptotic stability of the closed-loop system is guaranteed in contrast with all other NN controllers where a uniform ultimate boundedness is normally shown. Simulation results are presented to show the effectiveness of the controller design. © 2009 AACC.

R-Factor: A New Parameter To Enhance Location Accuracy In Rssi Based Real-Time Location Systems, Mohammed Rana Basheer, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

The fundamental cause of localization error in an indoor environment is fading and spreading of the radio signals due to scattering, diffraction, and reflection. These effects are predominant in regions where there is no-line-of-sight (NLoS) between the transmitter and the receiver. Efficient algorithms are needed to identify the subset of receivers that provide better localization accuracy. © 2009 IEEE.

Neural Network Control Of Quadrotor Uav Formations, Travis Dierks, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a novel framework for leader-follower formation control is developed for the control of multiple quadrotors unmanned aerial vehicles (UAVs) based on spherical coordinates. the control objective for the follower UAV is to track its leader at a desired- separation, angle of incidence, and a bearing by using an auxiliary velocity control. Then, a novel neural network (NN) control law for the dynamical system is introduced to learn the complete dynamics of the UAV including unmodeled dynamics like aerodynamic friction. Additionally, the interconnection dynamic errors between the leader and its followers are explicitly considered, and the stability of …

User Survey Regarding The Needs Of Network Researchers In Trace-Anonymization Tools, Jihwang Yeo, Keren Tan, David Kotz

Computer Science Technical Reports

To understand the needs of network researchers in an anonymization tool, we conducted a survey on the network researchers. We invited network researchers world-wide to the survey by sending invitation emails to well-known mailing lists whose subscribers may be interested in network research with collecting, sharing and sanitizing network traces.

A Model Based Fault Detection And Accommodation Scheme For Nonlinear Discrete-Time Systems With Asymptotic Stability Guarantee, Balaje T. Thumati, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a fault detection and accommodation (FDA) framework is developed for unknown nonlinear discrete-time systems. the changes in the system dynamics due to the faults are modeled as a nonlinear function of state and input variables while the time profile of the fault is assumed to be exponentially developing. a fault is detected by monitoring the system states and reconstructing the fault dynamics using online approximators. the online approximator output is used first for fault detection and later reconfigured for accommodation. a stable adaptation law in discrete time is developed not only to characterize the faults but also …

Towards Robot Theatre, Marek Perkowski

Systems Science Friday Noon Seminar Series

The talk will present the idea of futuristic robot theatre and work done towards it at the Intelligent Robotics Laboratory, Department of Electrical and Computer Engineering at PSU. After a short history of robot theatre from antiquity until 2008 we will present recent work on robot theatre in the world and at PSU, including two plays: ancient Korean folk tale "Hahoe Pylyshin" and "What's that? A Schroedinger Cat" or a debate between Einstein and Schroedinger Cat about quantum mechanics - an educational theatre. Several models of robot theatre will be discussed: animatronic theatre, interactive theatre and improvisational theatre. We will …

An Empirical Study Of Instance Hardness, Michael Reed Smith

Theses and Dissertations

Most widely accepted measures of performance for learning algorithms, such as accuracy and area under the ROC curve, provide information about behavior at the data set level. They say nothing about which instances are misclassified, whether two learning algorithms with the same classification accuracy on a data set misclassify the same instances, or whether there are instances misclassified by all learning algorithms. These questions about behavior at the instance level motivate our empirical analysis of instance hardness, a measure of expected classification accuracy for an instance. We analyze the classification of 57 data sets using 9 learning algorithms. Of …

Design Of Soa Based Web Service Systems Using Qfd For Satisfaction Of Quality Of Service Requirements, Xiaoqing Frank Liu, Lianzhang Zhu

Computer Science Faculty Research & Creative Works

Service-Oriented Architecture (SOA) is a loosely coupled architecture designed to meet business needs of an organization. It is becoming a trend for system development and integration where systems group functionality around business processes. Although SOA does not require Web services, Web services are based on accepted standards and drive SOA to the mainstream. There are at least two challenges with quality management of SOA based Web service systems. One of them is how to link explicitly its technical capability with customers' needs to satisfy customers' functional and nonfunctional requirements. the second is how to determine targets of Web service technical …

An Online Credential Repository For Role-Based Delegation, Guangxu Zhou Zhou

Theses and Dissertations

In large scaled organizations deployed with Role-based Access Control, it is desired to have role delegation services within the domain of the corporation. But there is no widely accepted delegation model yet due to the complicated properties of authorization. The delegation model needs to bridge resources, policies, owners and users perfectly which demands more dimensions to be managed than the authentication process conducts. In this research work, we are proposing a prototype that enables delegation service for group users communicating with multicasting channels, the Role-based Access Control applied for both the communications and the user credentials of authorization. We combined …

Adaptive Dynamic Programming-Based Optimal Control Of Unknown Affine Nonlinear Discrete-Time Systems, Travis Dierks, Balaje T. Thumati, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Discrete time approximate dynamic programming (ADP) techniques have been widely used in the recent literature to determine the optimal or near optimal control policies for nonlinear systems. However, an inherent assumption of ADP requires at least partial knowledge of the system dynamics as well as the value of the controlled plant one step ahead. in this work, a novel approach to ADP is attempted while relaxing the need of the partial knowledge of the nonlinear system. the proposed methodology entails a two-part process: online system identification and offline optimal control training. First, in the identification process, a neural network (NN) …

Decentralized Control Of Large Scale Interconnected Systems Using Adaptive Neural Network-Based Dynamic Surface Control, Shahab Mehraeen, Sarangapani Jagannathan, Mariesa L. Crow

Electrical and Computer Engineering Faculty Research & Creative Works

A novel decentralized controller using the dynamic surface control (DSC) is proposed for a class of uncertain large scale interconnected nonlinear systems in strict feedback form while relaxing the "explosion of complexity" problem which is observed in the typical backstepping approach. the matching condition is not assumed when dealing with the interconnection terms. Neural networks (NNs) are utilized to approximate the uncertainties in both subsystem and interconnected terms. by using novel NN weight update laws, it is demonstrated using Lyapunov stability that the closed-loop signals are asymptotically stable in the presence of NN approximation errors in contrast with the uniform …