Computer Sciences Commons^™

Tool Support For Reasoning In Display Calculi, Samuel Balco, Sabine Frittella, Giuseppe Greco, Alexander Kurz, Alessandra Palmigiano

Engineering Faculty Articles and Research

We present a tool for reasoning in and about propositional sequent calculi. One aim is to support reasoning in calculi that contain a hundred rules or more, so that even relatively small pen and paper derivations become tedious and error prone. As an example, we implement the display calculus D.EAK of dynamic epistemic logic. Second, we provide embeddings of the calculus in the theorem prover Isabelle for formalising proofs about D.EAK. As a case study we show that the solution of the muddy children puzzle is derivable for any number of muddy children. Third, there is a set of meta-tools, …

Models Of Leader Elections And Their Applications, Stephen Curtis Jackson

Doctoral Dissertations

"New research about cyber-physical systems is rapidly changing the way we think about critical infrastructures such as the power grid. Changing requirements for the generation, storage, and availability of power are all driving the development of the smart-grid. Many smart-grid projects disperse power generation across a wide area and control devices with a distributed system. However, in a distributed system, the state of processes is hard to determine due to isolation of memory. By using information flow security models, we reason about a process's beliefs of the system state in a distributed system. Information flow analysis aided in the creation …

Mechanisms For Improving Information Quality In Smartphone Crowdsensing Systems, Francesco Restuccia

Doctoral Dissertations

"Given its potential for a large variety of real-life applications, smartphone crowdsensing has recently gained tremendous attention from the research community. Smartphone crowdsensing is a paradigm that allows ordinary citizens to participate in large-scale sensing surveys by using user-friendly applications installed in their smartphones. In this way, fine-grained sensing information is obtained from smartphone users without employing fixed and expensive infrastructure, and with negligible maintenance costs.

Existing smartphone sensing systems depend completely on the participants' willingness to submit up-to-date and accurate information regarding the events being monitored. Therefore, it becomes paramount to scalably and effectively determine, enforce, and optimize the …

Fairness And Approximation In Multi-Version Transactional Memory., Basem Ibrahim Assiri

LSU Doctoral Dissertations

Shared memory multi-core systems bene_x000C_t from transactional memory implementations due to the inherent avoidance of deadlocks and progress guarantees. In this research, we examine how the system performance is a_x000B_ected by transaction fairness in scheduling and by the precision in consistency. We _x000C_rst explore the fairness aspect using a Lazy Snapshot (multi-version) Algorithm. The fairness of transactions scheduling aims to balance the load between read-only and update transactions. We implement a fairness mechanism based on machine learning techniques that improve fairness decisions according to the transaction execution history. Experimental analysis shows that the throughput of the Lazy Snapshot Algorithm is …

An Algorithm For Inferring Big Data Objects Correlation Using Word Net, M. Basel Almourad, Mohammed Hussain, Talal Bonny

All Works

© 2016 The Authors. The value of big data comes from its variety where data is collected from various sources. One of the key big data challenges is identifying which data objects are relevant or refer to the same logical entity across various data sources. This challenge is traditionally known as schema matching. Due to big data velocity traditional approaches to data matching can no longer be used. In this paper we present an approach for inferring data objects correlation. We present our algorithm that relies on the objects meta-data and it consults the Word Net thesaurus.

Bloom Filters Optimized Wu-Manber For Intrusion Detection, Monther Aldwairi, Koloud Al-Khamaiseh, Fatima Alharbi, Babar Shah

All Works

With increasing number and severity of attacks, monitoring ingress and egress network traffic is becoming essential everyday task. Intrusion detection systems are the main tools for capturing and searching network traffic for potential harm. Signature -based intrusion detection systems are the most widely used, and they simply use a pattern matching algorithms to locate attack signatures in intercepted network traffic. Pattern matching algorithms are very expensive in terms of running time and memory usage, leaving intrusion detection systems unable to detect attacks in real-time. We propose a Bloom filters optimized Wu-Manber pattern matching algorithm to speed up intrusion detection. The …

Factororacle: An Extensible Max External For Investigating Applications Of The Factor Oracle Automaton In Real-Time Music Improvisation, Adam James Wilson

Publications and Research

There are several extant software systems designed to generate music in real-time using a factor oracle automaton constructed from the musical input of a human improvisor. The impetus for the design of the factorOracle external is neither a desire to supersede these systems nor introduce novel algorithms for traversing the oracle, but rather to provide a fast, canonical interface for the automaton in Cycling74’s Max and, in future iterations, the Pure Data programming environment. Technical features of the factorOracle software are introduced here.

Optical Fiber Sensors In Physical Intrusion Detection Systems: A Review, Gary Andrew Allwood, Graham Wild, Steven Hinkley

Research outputs 2014 to 2021

Fiber optic sensors have become a mainstream sensing technology within a large array of applications due to their inherent benefits. They are now used significantly in structural health monitoring, and are an essential solution for monitoring harsh environments. Since their first development over 30 years ago, they have also found promise in security applications. This paper reviews all of the optical fiber-based techniques used in physical intrusion detection systems. It details the different approaches used for sensing, interrogation, and networking, by research groups, attempting to secure both commercial and residential premises from physical security breaches. The advantages and the disadvantages …

Building Online Community On Snac: A Netnographic Study Of The Early Years Sector, Ruth Wallace, Leesa Costello, Amanda Devine

Research outputs 2014 to 2021

‘‘Build it and they will come,’’ an adage critiqued as a common misconception of participatory engagement with online communities. Previous research indicated that a netnographic approach based upon researcher– participant engagement would provide the best opportunity to build and sustain a successful support community [...].

An Automated Approach For Digital Forensic Analysis Of Heterogeneous Big Data, Hussam Mohammed, Nathan Clarke, Fudong Li

Research outputs 2014 to 2021

The major challenges with big data examination and analysis are volume, complex interdependence across content, and heterogeneity. The examination and analysis phases are considered essential to a digital forensics process. However, traditional techniques for the forensic investigation use one or more forensic tools to examine and analyse each resource. In addition, when multiple resources are included in one case, there is an inability to cross-correlate findings which often leads to inefficiencies in processing and identifying evidence. Furthermore, most current forensics tools cannot cope with large volumes of data. This paper develops a novel framework for digital forensic analysis of heterogeneous …

Applying Grounded Theory Methods To Digital Forensics Research, Ahmed Almarzooqi, Andrew Jones

Research outputs 2014 to 2021

Deciding on a suitable research methodology is challenging for researchers. In this paper, grounded theory is presented as a systematic and comprehensive qualitative methodology in the emergent field of digital forensics research. This paper applies grounded theory in a digital forensics research project undertaken to study how organisations build and manage digital forensics capabilities. This paper gives a step-by-step guideline to explain the procedures and techniques of using grounded theory in digital forensics research. The paper gives a detailed explanation of how the three grounded theory coding methods (open, axial, and selective coding) can be used in digital forensics research. …

A Cloud-Based Framework For Smart Permit System For Buildings, Magdalini Eirinaki, Subhankar Dhar, Shishir Mathur

Faculty Publications

In this paper we propose a novel cloud-based platform for building permit system that is efficient, user-friendly, transparent, and has quick turn-around time for homeowners. Compared to the existing permit systems, the proposed smart city permit framework provides a pre-permitting decision workflow, and incorporates a data analytics and mining module that enables the continuous improvement of a) the end user experience, by analyzing explicit and implicit user feedback, and b) the permitting and urban planning process, allowing a gleaning of key insights for real estate development and city planning purposes, by analyzing how users interact with the system depending on …

Pro-Fit: Exercise With Friends, Saumil Dharia, Vijesh Jain, Jvalant Patel, Jainikkumar Vora, Rizen Yamauchi, Magdalini Eirinaki, Iraklis Varlamis

Faculty Publications

The advancements in wearable technology, where embedded accelerometers, gyroscopes and other sensors enable the users to actively monitor their activity have made it easier for individuals to pursue a healthy lifestyle. However, most of the existing applications expect continuous commitment from the end users, who need to proactively interact with the application in order to connect with friends and attain their goals. These applications fail to engage and motivate users who have busy schedules, or are not as committed and self-motivated. In this work, we present PRO-Fit, a personalized fitness assistant application that employs machine learning and recommendation algorithms in …

Threshold-Bounded Influence Dominating Sets For Recommendations In Social Networks, Magdalini Eirinaki, Nuno Moniz, Katerina Potika

Faculty Publications

The process of decision making in humans involves a combination of the genuine information held by the individual, and the external influence from their social network connections. This helps individuals to make decisions or adopt behaviors, opinions or products. In this work, we seek to investigate under which conditions and with what cost we can form neighborhoods of influence within a social network, in order to assist individuals with little or no prior genuine information through a two-phase recommendation process. Most of the existing approaches regard the problem of identifying influentials as a long-term, network diffusion process, where information cascading …

Time-Based Ensembles For Prediction Of Rare Events In News Streams, Nuno Moniz, Luís Torgo, Magdalini Eirinaki

Faculty Publications

Thousands of news are published everyday reporting worldwide events. Most of these news obtain a low level of popularity and only a small set of events become highly popular in social media platforms. Predicting rare cases of highly popular news is not a trivial task due to shortcomings of standard learning approaches and evaluation metrics. So far, the standard task of predicting the popularity of news items has been tackled by either of two distinct strategies related to the publication time of news. The first strategy, a priori, is focused on predicting the popularity of news upon their publication when …

An Efficient Method For Optimizing Segmentation Parameters, Jacob D' Avy, Wei-Wen Hsu, Chung-Hao Chen, Andreas F. Koschan, Mongi Abidi

Electrical & Computer Engineering Faculty Publications

Segmenting an image into meaningful regions is an important step in many computer vision applications such as facial recognition, target tracking and medical image analysis. Because image segmentation is an ill-posed problem, parameters are needed to constrain the solution to one that is suitable for a given application. For a user, setting parameter values is often unintuitive. We present a method for automating segmentation parameter selection using an efficient search method to optimize a segmentation objective function. Efficiency is improved by utilizing prior knowledge about the relationship between a segmentation parameter and the objective function terms. An adaptive sampling of …

Positioning Commuters And Shoppers Through Sensing And Correlation, Rufeng Meng

Theses and Dissertations

Positioning is a basic and important need in many scenarios of human daily activities. With position information, multifarious services could be vitalized to benefit all kinds of users, from individuals to organizations. Through positioning, people are able to obtain not only geo-location but also time related information. By aggregating position information from individuals, organizations could derive statistical knowledge about group behaviors, such as traffic, business, event, etc.

Although enormous effort has been invested in positioning related academic and industrial work, there are still many holes to be filled. This dissertation proposes solutions to address the need of positioning in people’s …

Interest Detection In Image, Video And Multiple Videos: Model And Applications, Yuewei Lin

Theses and Dissertations

Interest detection is detecting an object, event, or process that draws attention. In this dissertation, we focus on interest detection in images, video and multiple videos. Interest detection in an image or a video is closely related to visual attention. However, the interest detection in multiple videos needs to consider all the videos as a whole rather than considering the attention in each single video independently.

Visual attention is an important mechanism of human vision. The computational model of visual attention has recently attracted a lot of interest in the computer vision community mainly because it helps find the objects …

Mining The Web And Literature To Discover New Knowledge About Diabetes, Farhi Marir, Huwida Said, Feras Al-Obeidat

All Works

© 2016 The Authors. Social Networks are powerful social media for sharing information about various issues and can be used to raise awareness and collect pointers about associated risk factors and preventive measures in chronical disease like diabetes. Since the olden times, knowledge in medicine was established through recording and analysing human experiences. This paper presents the results of text mining techniques of more than five hundred thousands of texts retrieved from social networks, blogs, forums, and also research papers from MEDLINE database to discovering new knowledge related to diabetes disease covering symptoms and treatments. The text mining approach consists …

A Lightweight Security Protocol For Nfc-Based Mobile Payments, Mohamad Badra, Rouba Borghol Badra

All Works

© 2016 Published by Elsevier B.V. In this work, we describe a security solution that can be used to securely establish mobile payment transactions over the Near-Field Communication (NFC) radio interface. The proposed solution is very lightweight one; it uses symmetric cryptographic primitives on devices having memory and CPU resources limitations. We show that our approach maintains the security of NFC communications and we further demonstrate that our solution is simple, scalable, cost-effective, and incurs minimal computational processing overheads.

A Mof-Based Social Web Services Description Metamodel, Amel Benna, Zakaria Maamar, Mohamed Ahmed Nacer

All Works

© Copyright 2016 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved. To promote and support the development and use of social Web services by the IT community on the Web, both social Web service-based applications and their support platforms should evolve independently from each other while sharing a common model that represents the characteristics of these social Web services. To achieve this duality, this paper proposes a model-driven approach. First, the approach identifies a social Web service's properties. Then a Meta-Object-Facility (MOF)-based social Web services description metamodel is developed. Finally, a prototype illustrates how the MOF-based metamodel …

An Architecture For Qos-Enabled Mobile Video Surveillance Applications In A 4g Epc And M2m Environment, Mohammad Abu-Lebdeh, Fatna Belqasmi, Roch Glitho

All Works

© 2016 IEEE. Mobile video surveillance applications are used widely nowadays. They offer real-time video monitoring for homes, offices, warehouses, airports, and so on with live and pre-recorded on-demand video streaming. Quality of service (QoS) remains a key challenge faced by most of these applications. In this article, we propose an architecture for mobile video surveillance applications with a guaranteed and differentiated QoS support. The architecture relies on the 3GPP 4G evolved packet core (EPC). The main components are the QoS enabler, media server, and machine-to-machine gateway and surveillance application. To demonstrate its feasibility, a proof of concept prototype has …

Forensic Investigation Of Cyberstalking Cases Using Behavioural Evidence Analysis, Noora Al Mutawa, Joanne Bryce, Virginia N.L. Franqueira, Andrew Marrington

All Works

Behavioural Evidence Analysis (BEA) is, in theory, useful in developing an understanding of the offender, the victim, the crime scene, and the dynamics of the crime. It can add meaning to the evidence obtained through digital forensic techniques and assist investigators with reconstruction of a crime. There is, however, little empirical research examining the application of BEA to actual criminal cases, particularly cyberstalking cases. This study addresses this gap by examining the utility of BEA for such cases in terms of understanding the behavioural and motivational dimensions of offending, and the way in which digital evidence can be interpreted. It …

Instructional Videos As Part Of A 'Flipped' Approach In Academic Writing, Marion Engin, Senem Donanci

All Works

This paper reports on a project in which students watched short instructional videos on aspects of academic writing as part of a 'flipped classroom' approach at an English-medium university in the United Arab Emirates. The authors present the video tutorial project in the context of the flipped classroom, and evaluate student satisfaction with the video input. The findings suggest that although most students liked watching the videos at home, and found the input easy to understand, they still felt the need for teacher explanations. One conclusion from this study is that students are not yet ready for a complete flipped …

Towards On Demand Road Condition Monitoring Using Mobile Phone Sensing As A Service, Wael Alrahal Alorabi, Sawsan Abdul Rahman, May El Barachi, Azzam Mourad

All Works

© 2016 The Authors. With the increased need for mobility and the overcrowding of cities, the area of Intelligent Transportation aims at improving the efficiency, safety, and productivity of transportation systems by relying on communication and sensing technologies. One of the main challenges faced in Intelligent Transportation Systems (ITS) pertains to the real time collection of traffic and road related data, in a cost effective, efficient, and scalable manner. The current approaches still suffer from problems related to the energy consumption of mobile devices and overhead in terms of communications and processing. We have previously proposed the concept of Mobile …

Auto-Configuration Of Acl Policy In Case Of Topology Change In Hybrid Sdn, Rashid Amin, Nadir Shah, Babar Shah, Omar Alfandi

All Works

© 2016 IEEE. Software-defined networking (SDN) has emerged as a new network architecture, which decouples both the control and management planes from data plane at forwarding devices. However, SDN deployment is not widely adopted due to the budget constraints of organizations. This is because organizations are always reluctant to invest too much budget to establish a new network infrastructure from scratch. One feasible solution is to deploy a limited number of SDN-enabled devices along with traditional (legacy) network devices in the network of an organization by incrementally replacing traditional network by SDN, which is called hybrid SDN (Hybrid SDN) architecture. …

Temperature Forecasts With Stable Accuracy In A Smart Home, Bruce Spencer, Feras Al-Obeidat

All Works

© 2016 The Authors. We forecast internal temperature in a home with sensors, modeled as a linear function of recent sensor values. When delivering forecasts as a service, two desirable properties are that forecasts have stable accuracy over a variety of forecast horizons - so service levels can be predicted - and that the forecasts rely on a modest amount of sensor history - so forecasting can be restarted soon after any data outage due to, for example, sensor failure. From a publicly available data set, we show that sensor values over the past one or two hours are sufficient …

Forecasting Internal Temperature In A Home With A Sensor Network, Bruce Spencer, Omar Alfandi

All Works

© 2016 The Authors. We forecast internal temperature in a home with sensors, modeled as a linear function of recent sensor values. The Smart∗Project provides publicly available data from an inhabited home over a three month period, reporting on 38 sensors including environmental readings, circuit loads, motion detectors, and switches controlling lights and fans. We select 13 of these sensors that have some influence on the internal temperature, and create forecasts that are accurate to within about 1.6°F (0.9°C) over the next six hours. Temperature prediction is important for saving energy while maintaining comfortable conditions in the home.

Digital Forensics In Law Enforcement: A Needs Based Analysis Of Indiana Agencies, Teri A. Cummins Flory

Journal of Digital Forensics, Security and Law

Cyber crime is a growing problem, with the impact to society increasing exponentially, but the ability of local law enforcement agencies to investigate and successfully prosecute criminals for these crimes is unclear. Many national needs assessments have previously been conducted, and all indicated that state and local law enforcement did not have the training, tools, or staff to effectively conduct digital investigations, but very few have been completed recently. This study provided a current and localized assessment of the ability of Indiana law enforcement agencies to effectively investigate crimes involving digital evidence, the availability of training for both law enforcement …

Verification Of Recovered Digital Evidence On The Amazon Kindle, Marcus Thompson, Raymond Hansen

Journal of Digital Forensics, Security and Law

The Amazon Kindle is a popular e-book reader. This popularity will lead criminals to use the Kindle as an accessory to their crime. Very few Kindle publications in the digital forensics domain exist at the time of this writing. Various blogs on the Internet currently provide some of the foundation for Kindle forensics. For this research each fifth generation Kindle was populated with various types of files a typical user may introduce using one method, the USB interface. The Kindle was forensically imaged with AccessData’s Forensic Toolkit Imager before and after each Kindle was populated. Each file was deleted through …