Computer Sciences Commons^™

Making Sense Of Email Addresses On Drives, Neil C. Rowe, Riqui Schwamm, Michael R. Mccarrin, Ralucca Gera

Journal of Digital Forensics, Security and Law

Drives found during investigations often have useful information in the form of email addresses which can be acquired by search in the raw drive data independent of the file system. Using this data we can build a picture of the social networks that a drive owner participated in, even perhaps better than investigating their online profiles maintained by social-networking services because drives contain much data that users have not approved for public display. However, many addresses found on drives are not forensically interesting, such as sales and support links. We developed a program to filter these out using a Naïve …

Countering Noise-Based Splicing Detection Using Noise Density Transfer, Thibault Julliand, Vincent Nozick, Hugues Talbot

Journal of Digital Forensics, Security and Law

Image splicing is a common and widespread type of manipulation, which is defined as pasting a portion of an image onto a second image. Several forensic methods have been developed to detect splicing, using various image properties. Some of these methods exploit the noise statistics of the image to try and find discrepancies. In this paper, we propose a new counter-forensic approach to eliminate the noise differences that can appear in a spliced image. This approach can also be used when creating computer graphics images, in order to endow them with a realistic noise. This is performed by changing the …

Evidential Reasoning For Forensic Readiness, Yi-Ching Liao, Hanno Langweg

Journal of Digital Forensics, Security and Law

To learn from the past, we analyse 1,088 "computer as a target" judgements for evidential reasoning by extracting four case elements: decision, intent, fact, and evidence. Analysing the decision element is essential for studying the scale of sentence severity for cross-jurisdictional comparisons. Examining the intent element can facilitate future risk assessment. Analysing the fact element can enhance an organization's capability of analysing criminal activities for future offender profiling. Examining the evidence used against a defendant from previous judgements can facilitate the preparation of evidence for upcoming legal disclosure. Follow the concepts of argumentation diagrams, we develop an automatic judgement summarizing …

Table Of Contents

Journal of Digital Forensics, Security and Law

No abstract provided.

Table Of Contents

Journal of Digital Forensics, Security and Law

No abstract provided.

Electronic Voting Service Using Block-Chain, Kibin Lee, Joshua I. James, Tekachew G. Ejeta, Hyoung J. Kim

Journal of Digital Forensics, Security and Law

Cryptocurrency, and its underlying technologies, has been gaining popularity for transaction management beyond financial transactions. Transaction information is maintained in the block-chain, which can be used to audit the integrity of the transaction. The focus on this paper is the potential availability of block-chain technology of other transactional uses. Block-chain is one of the most stable open ledgers that preserves transaction information, and is difficult to forge. Since the information stored in block-chain is not related to personally identify information, it has the characteristics of anonymity. Also, the block-chain allows for transparent transaction verification since all information in the block-chain …

Java Based Visualization And Animation For Teaching The Dijkstra Shortest Path Algorithm In Transportation Networks, Ivan Makohon, Duc T. Nguyen, Masha Sosonkina, Yuzhong Shen, Manwo Ng

Civil & Environmental Engineering Faculty Publications

Shortest path (SP) algorithms, such as the popular Dijkstra algorithm has been considered as the "basic building blocks" for many advanced transportation network models. Dijkstra algorithm will find the shortest time (ST) and the corresponding SP to travel from a source node to a destination node. Applications of SP algorithms include real-time GPS and the Frank-Wolfe network equilibrium.

For transportation engineering students, the Dijkstra algorithm is not easily understood. This paper discusses the design and development of a software that will help the students to fully understand the key components involved in the Dijkstra SP algorithm. The software presents an …

Regular Expression Synthesis For Blast Two-Hit Filtering, Jordan Bradshaw

Theses and Dissertations

Genomic databases are exhibiting a growth rate that is outpacing Moore's Law, which has made database search algorithms a popular application for use on emerging processor technologies. NCBI BLAST is the standard tool for performing searches against these databases, which operates by transforming each database query into a filter that is subsequently applied to the database. This requires a database scan for every query, fundamentally limiting its performance by I/O bandwidth. In this dissertation we present a functionally-equivalent variation on the NCBI BLAST algorithm that maps more suitably to an FPGA implementation. This variation of the algorithm attempts to reduce …

Efficient Partitioning And Allocation Of Data For Workflow Compositions, Annamaria Victoria Kish

Theses and Dissertations

Our aim is to provide efficient partitioning and allocation of data for web service compositions. Web service compositions are represented as partial order database transactions. We accommodate a variety of transaction types, such as read-only and write-oriented transactions, to support workloads in cloud environments. We introduce an approach that partitions and allocates small units of data, called micropartitions, to multiple database nodes. Each database node stores only the data needed to support a specific workload. Transactions are routed directly to the appropriate data nodes. Our approach guarantees serializability and efficient execution.

In Phase 1, we cluster transactions based on data …

Hydro-Geological Flow Analysis Using Hidden Markov Models, Chandrahas Raj Venkat Gurram

Theses and Dissertations

Hidden Markov Models a class of statistical models used in various disciplines for understanding speech, finding different types of genes responsible for cancer and much more. In this thesis, Hidden Markov Models are used to obtain hidden states that can correlate the flow changes in the Wakulla Spring Cave. Sensors installed in the tunnels of Wakulla Spring Cave have recorded huge correlated changes in the water flows at numerous tunnels. Assuming the correlated flow changes are a consequence of system being in a set of discrete states, a Hidden Markov Model is calculated. This model comprising all the sensors installed …

Computational Doping For Fuel Cell Material Design Based On Genetic Algorithms And Genetic Programming, Emrah Atilgan

Theses and Dissertations

Developing new materials have historically been time-consuming. Computational material discovery can search large design space to identify promising candidates for experimental verification. Recently, Density Functional Theory (DFT) based first principle calculation has been able to calculate many electrical and physical properties of materials, making them suitable for computational doping based material discovery. In material doping, given a base material, one can change its properties by substituting some elements with new ones or adding additional elements. In computational doping, we have a grid of atoms in a supercell, some of which can be substituted with dopant atoms. There are many possible …

An Improved Smote Algorithm Based On Genetic Algorithm For Imbalanced Data Collection, Qiong Gu, Xian-Ming Wang, Zhao Wu, Bing Ning, Chun-Sheng Xin

Electrical & Computer Engineering Faculty Publications

Classification of imbalanced data has been recognized as a crucial problem in machine learning and data mining. In an imbalanced dataset, minority class instances are likely to be misclassified. When the synthetic minority over-sampling technique (SMOTE) is applied in imbalanced dataset classification, the same sampling rate is set for all samples of the minority class in the process of synthesizing new samples, this scenario involves blindness. To overcome this problem, an improved SMOTE algorithm based on genetic algorithm (GA), namely, GASMOTE was proposed. First, GASMOTE set different sampling rates for different minority class samples. A combination of the sampling rates …

Exploring Deviant Hacker Networks (Dhn) On Social Media Platforms, Samer Al-Kateeb, Kevin Conlan, Nitin Agarwal, Ibrahim Baggili, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

Online Social Networks (OSNs) have grown exponentially over the past decade. The initial use of social media for benign purposes (e.g., to socialize with friends, browse pictures and photographs, and communicate with family members overseas) has now transitioned to include malicious activities (e.g., cybercrime, cyberterrorism, and cyberwarfare). These nefarious uses of OSNs poses a signi_cant threat to society, and thus requires research attention. In this exploratory work, we study activities of one deviant groups: hacker groups on social media, which we term Deviant Hacker Networks (DHN). We investigated the connection between different DHNs on Twitter: how they are connected, identified …

Towards Syntactic Approximate Matching-A Pre-Processing Experiment, Doowon Jeong, Frank Breitinger, Hari Kang, Sangjin Lee

Electrical & Computer Engineering and Computer Science Faculty Publications

Over the past few years, the popularity of approximate matching algorithms (a.k.a. fuzzy hashing) has increased. Especially within the area of bytewise approximate matching, several algorithms were published, tested, and improved. It has been shown that these algorithms are powerful, however they are sometimes too precise for real world investigations. That is, even very small commonalities (e.g., in the header of a file) can cause a match. While this is a desired property, it may also lead to unwanted results. In this paper, we show that by using simple pre-processing, we significantly can influence the outcome. Although our test set …

Find Me If You Can: Mobile Gps Mapping Applications Forensic Analysis & Snavp The Open Source, Modular, Extensible Parser, Jason Moore, Ibrahim Baggili, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

The use of smartphones as navigation devices has become more prevalent. The ubiquity of hand-held navigation devices such as Garmins or Toms Toms has been falling whereas the ownership of smartphones and their adoption as GPS devices is growing. This work provides a comprehensive study of the most popular smartphone mapping applications, namely Google Maps, Apple Maps, Waze, MapQuest, Bing, and Scout, on both Android and iOS. It details what data was found, where it was found, and how it was acquired for each application. Based on the findings, the work allowed for the construction of a tool capable of …

Cloud-Based Lineament Extraction Of Topographic Lineaments From Nasa Shuttle Radar Topography Mission Data, Feras Al-Obeidat, Leonardo Feltrin, Farhi Marir

All Works

© 2016 The Authors. This paper presents initial results of a JavaTM based, feature extraction tool, which represents a standard implementation of a hill-shading algorithm that transforms a 2D image to pseudo 3D image to enhance edge contrast in combination with an edge detection Canny algorithm that performs segmentation to produce multidirectional sun-shaded images and their edges. Our goal is to firstly automate this processes in JavaTM to obtain multidirectional optimization of edge discovery and secondly scale this algorithm to the complete SRTM raster collection at multiple pixel resolutions to document the distribution of Earth topographic discontinuities from continental to …

Combining Weights Of Evidence Analysis With Feature Extraction - A Case Study From The Hauraki Goldfield, New Zealand, Leonardo Feltrin, João Gabriel Motta, Feras Al-Obeidat, Farhi Marir, Martina Bertelli

All Works

© 2016 The Authors. In this contribution we combine different image processing and pattern recognition methodologies to map the probability of discovering epithermal mineral deposits in the northern part of the Coromandel peninsula, in New Zealand. The objective of this work is to propose a case-study where the substitution of structural geology GIS themes (commonly developed by humans) with products derived by image processing, computer-based, semi-automatic edge detection analyses, is carried out to reduce subjective input in the prospectivity analysis. Semi-automated lineament extraction results introduced in the mineral favourability statistical modelling can more easily reveal unexpected potentially mineralised target domains, …

An Elastic Hybrid Sensing Platform: Architecture And Research Challenges, Sleiman Rabah, Fatna Belqasmi, Rabeb Mizouni, Rachida Dssouli

All Works

© 2016 Published by Elsevier B.V. The dynamic provisioning of hybrid sensing services that integrates both WSN and MPS is a promising, yet challenging concept. It does not only widen the spatial sensing coverage, but it also enables different types of sensing nodes to collaboratively perform sensing tasks and complement each other. Furthermore, it allows for the provisioning of a new category of services that was not possible to implement in pure WSN or MPS networks. Offering a hybrid sensing platform as a service results in several benefits including, but no limited to, efficient sharing and dynamic management of sensing …

Privacy-Preserving And Verifiable Data Aggregation, Ngoc Hieu Tran, Robert H. Deng, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

There are several recent research studies on privacy-preserving aggregation of time series data, where an aggregator computes an aggregation of multiple users' data without learning each individual's private input value. However, none of the existing schemes allows the aggregation result to be verified for integrity. In this paper, we present a new data aggregation scheme that protects user privacy as well as integrity of the aggregation. Towards this end, we first propose an aggregate signature scheme in a multi-user setting without using bilinear maps. We then extend the aggregate signature scheme into a solution for privacy-preserving and verifiable data aggregation. …

Performance Based Contracting For The Manufacturing Industry By Using Integrated Platform And Dynamic Pricing Model, Lindawati, Aldy Gunawan

Research Collection Lee Kong Chian School Of Business

Although Performance Based Contracting (PBC) concept is not totally new, the PBC adaptation in Industrial Machinery and Components (IMC) manufacturing, which produces high-value and long life machineries, is rather slow and it is done with extra caution. Three main concerns for manufacturers to implement PBC are the investment cost, the maintenance cost and possible revenue loss. To handle these concerns and accelerate the PBC implementation, we propose an integrated platform that consists of three components: dynamic pricing, sensor data feeding and machinery monitoring. We model the dynamic pricing as an optimization problem and propose Genetic Algorithm to solve the problem. …

Eeg Interictal Spike Detection Using Artificial Neural Networks, Howard J. Carey Iii

Theses and Dissertations

Epilepsy is a neurological disease causing seizures in its victims and affects approximately 50 million people worldwide. Successful treatment is dependent upon correct identification of the origin of the seizures within the brain. To achieve this, electroencephalograms (EEGs) are used to measure a patient’s brainwaves. This EEG data must be manually analyzed to identify interictal spikes that emanate from the afflicted region of the brain. This process can take a neurologist more than a week and a half per patient. This thesis presents a method to extract and process the interictal spikes in a patient, and use them to reduce …

A Tool-Free Calibration Method For Turntable-Based 3d Scanning Systems, Xufang Pang, Rynson W.H. Lau, Zhan Song, Shengfeng He, Shengfeng He

Research Collection School Of Computing and Information Systems

Turntable-based 3D scanners are popular but require calibration of the turntable axis. Existing methods for turntable calibration typically make use of specially designed tools, such as a chessboard or criterion sphere, which users must manually install and dismount. In this article, the authors propose an automatic method to calibrate the turntable axis without any calibration tools. Given a scan sequence of the input object, they first recover the initial rotation axis from an automatic registration step. Then they apply an iterative procedure to obtain the optimized turntable axis. This iterative procedure alternates between two steps: refining the initial pose of …

Object Pooling For Multimedia Event Detection And Evidence Localization, Ho Zhang, Chong-Wah Ngo, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Multimedia event detection (MED) and evidence hunting are two primary topics in the area of multimedia event search. The former serves to retrieve a list of relevant videos given an event query, whereas, the latter reasons why and how much the degree a retrieved video answers that query. Common practices deal with these two topics in separate methods, however, in this paper, we combine MED and evidence hunting into a joint framework. We propose a refined semantical representation named object pooling which can dynamically extract visual snippets corresponding to the location of when and where evidences might appear. The main …

Synergizing Specification Miners Through Model Fissions And Fusions, Le Bui Tien Duy, Le Dinh Xuan Bach, David Lo, Ivan Beschastnikh

Research Collection School Of Computing and Information Systems

Software systems are often developed and released without formal specifications. For those systems that are formally specified, developers have to continuously maintain and update the specifications or have them fall out of date. To deal with the absence of formal specifications, researchers have proposed techniques to infer the missing specifications of an implementation in a variety of forms, such as finite state automaton (FSA). Despite the progress in this area, the efficacy of the proposed specification miners needs to improve if these miners are to be adopted. We propose SpecForge, a new specification mining approach that synergizes many existing specification …

Posting Topics ≠ Reading Topics: On Discovering Posting And Reading Topics In Social Media, Wei Gong, Ee-Peng Lim, Feida Zhu

Research Collection School Of Computing and Information Systems

Social media users make decisions about what content to post and read. As posted content is often visible to others, users are likely to impose self-censorship when deciding what content to post. On the other hand, such a concern may not apply to reading social media content. As a result, the topics of content that a user posted and read can be different and this has major implications to the applications that require personalization. To better determine and profile social media users’ topic interests, we conduct a user survey in Twitter. In this survey, participants chose the topics they like …

Friendship Maintenance And Prediction In Multiple Social Networks, Roy Ka-Wei Lee, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Due to the proliferation of online social networks (OSNs), users find themselves participating in multiple OSNs. These users leave their activity traces as they maintain friendships and interact with other users in these OSNs. In this work, we analyze how users maintain friendship in multiple OSNs by studying users who have accounts in both Twitter and Instagram. Specifically, we study the similarity of a user's friendship and the evenness of friendship distribution in multiple OSNs. Our study shows that most users in Twitter and Instagram prefer to maintain different friendships in the two OSNs, keeping only a small clique of …

Powerforecaster: Predicting Power Impact Of Mobile Sensing Applications At Pre-Installation Time, Chulhong Min, Youngki Lee, Chungkuk Yoo, Seungwoo Kang, Inseok Hwang, Junehwa Song

Research Collection School Of Computing and Information Systems

Today's smartphone application (hereinafter 'app') markets miss a key piece of information, power consumption of apps. This causes a severe problem for continuous sensing apps as they consume significant power without users' awareness. Users have no choice but to repeatedly install one app after another and experience their power use. To break such an exhaustive cycle, we propose PowerForecaster, a system that provides users with power use of sensing apps at pre-installation time. Such advanced power estimation is extremely challenging since the power cost of a sensing app largely varies with users' physical activities and phone use patterns. We observe …

On Analyzing Geotagged Tweets For Location-Based Patterns, Philips Kokoh Prasetyo, Palakorn Achananuparp, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Geotagged social media is becoming highly popular as social media access is now made very easy through a wide range of mobile apps which automatically detect and augment social media posts with geo-locations. In this paper, we analyze two kinds of location-based patterns. The first is the association between location attributes and the locations of user tweets. The second is location association pattern which comprises a pair of locations that are co-visited by users. We demonstrate that through tracking the Twitter data of Singapore-based users, we are able to reveal association between users tweeting from school locations and the school …

Insights From Machine-Learned Diet Success Prediction, Ingmar Weber, Palakorn Achananuparp

Research Collection School Of Computing and Information Systems

To support people trying to lose weight and stay healthy, more and more fitness apps have sprung up including the ability to track both calories intake and expenditure. Users of such apps are part of a wider “quantified self“ movement and many opt-in to publicly share their logged data. In this paper, we use public food diaries of more than 4,000 long-term active MyFitnessPal users to study the characteristics of a (un-)successful diet. Concretely, we train a machine learning model to predict repeatedly being over or under self-set daily calories goals and then look at which features contribute to the …

Salient Pairwise Spatio-Temporal Interest Points For Real-Time Activity Recognition, Mengyuan Liu, Hong Liu, Qianru Sun, Tianwei Zhang, Runwei Ding

Research Collection School Of Computing and Information Systems

Real-time Human action classification in complex scenes has applications in various domains such as visual surveillance, video retrieval and human robot interaction. While, the task is challenging due to computation efficiency, cluttered backgrounds and intro-variability among same type of actions. Spatio-temporal interest point (STIP) based methods have shown promising results to tackle human action classification in complex scenes efficiently. However, the state-of-the-art works typically utilize bag-of-visual words (BoVW) model which only focuses on the word distribution of STIPs and ignore the distinctive character of word structure. In this paper, the distribution of STIPs is organized into a salient directed graph, …