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Articles 6661 - 6690 of 13048

Full-Text Articles in Computer Engineering

Digital Forensics In The Next Five Years, Laoise Luciano, Ibrahim Baggili, Mateusz Topor, Peter Casey, Frank Breitinger Aug 2018

Digital Forensics In The Next Five Years, Laoise Luciano, Ibrahim Baggili, Mateusz Topor, Peter Casey, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

Cyber forensics has encountered major obstacles over the last decade and is at a crossroads. This paper presents data that was obtained during the National Workshop on Redefining Cyber Forensics (NWRCF) on May 23-24, 2017 supported by the National Science Foundation and organized by the University of New Haven. Qualitative and quantitative data were analyzed from twenty-four cyber forensics expert panel members. This work identified important themes that need to be addressed by the community, focusing on (1) where the domain currently is; (2) where it needs to go and; (3) steps needed to improve it. Furthermore, based on the …

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I Know What You Did Last Summer: Your Smart Home Internet Of Things And Your Iphone Forensically Ratting You Out, Gokila Dorai, Shiva Houshmand, Ibrahim Baggili Aug 2018

I Know What You Did Last Summer: Your Smart Home Internet Of Things And Your Iphone Forensically Ratting You Out, Gokila Dorai, Shiva Houshmand, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

The adoption of smart home Internet of Things (IoT) devices continues to grow. What if your devices can snitch on you and let us know where you are at any given point in time? In this work we examined the forensic artifacts produced by Nest devices, and in specific, we examined the logical backup structure of an iPhone used to control a Nest thermostat, Nest Indoor Camera and a Nest Outdoor Camera. We also integrated the Google Home Mini as another method of controlling the studied Smart Home devices. Our work is the primary account for the examination of Nest …

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Computational Thinking And Literacy, Sharin Rawhiya Jacob, Mark Warschauer Aug 2018

Computational Thinking And Literacy, Sharin Rawhiya Jacob, Mark Warschauer

Journal of Computer Science Integration

Today’s students will enter a workforce that is powerfully shaped by computing. To be successful in a changing economy, students must learn to think algorithmically and computationally, to solve problems with varying levels of abstraction. These computational thinking skills have become so integrated into social function as to represent fundamental literacies. However, computer science has not been widely taught in K-12 schools. Efforts to create computer science standards and frameworks have yet to make their way into mandated course requirements. Despite a plethora of research on digital literacies, research on the role of computational thinking in the literature is sparse. …

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Chaos Firefly Algorithm With Self-Adaptation Mutation Mechanism For Solving Large-Scale Economic Dispatch With Valve-Point Effects And Multiple Fuel Options, Yude Yang, Bori Wei, Hui Liu, Yiyi Zhang, Junhui Zhao, Emad Manla Aug 2018

Chaos Firefly Algorithm With Self-Adaptation Mutation Mechanism For Solving Large-Scale Economic Dispatch With Valve-Point Effects And Multiple Fuel Options, Yude Yang, Bori Wei, Hui Liu, Yiyi Zhang, Junhui Zhao, Emad Manla

Electrical & Computer Engineering and Computer Science Faculty Publications

This paper presents a new metaheuristic optimization algorithm, the firefly algorithm (FA), and an enhanced version of it, called chaos mutation FA (CMFA), for solving power economic dispatch problems while considering various power constraints, such as valve-point effects, ramp rate limits, prohibited operating zones, and multiple generator fuel options. The algorithm is enhanced by adding a new mutation strategy using self-adaptation parameter selection while replacing the parameters with fixed values. The proposed algorithm is also enhanced by a self-adaptation mechanism that avoids challenges associated with tuning the algorithm parameters directed against characteristics of the optimization problem to be solved. The …

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Self-Powered Time-Keeping And Time-Of-Occurrence Sensing, Liang Zhou Aug 2018

Self-Powered Time-Keeping And Time-Of-Occurrence Sensing, Liang Zhou

McKelvey School of Engineering Graduate Student Theses & Dissertations

Self-powered and passive Internet-of-Things (IoT) devices (e.g. RFID tags, financial assets, wireless sensors and surface-mount devices) have been widely deployed in our everyday and industrial applications. While diverse functionalities have been implemented in passive systems, the lack of a reference clock limits the design space of such devices used for applications such as time-stamping sensing, recording and dynamic authentication. Self-powered time-keeping in passive systems has been challenging because they do not have access to continuous power sources. While energy transducers can harvest power from ambient environment, the intermittent power cannot support continuous operation for reference clocks. The thesis of this …

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Forensic Analysis Of Immersive Virtual Reality Social Applications: A Primary Account, Ananya Yarramreddy, Peter Gromkowski, Ibrahim Baggili Aug 2018

Forensic Analysis Of Immersive Virtual Reality Social Applications: A Primary Account, Ananya Yarramreddy, Peter Gromkowski, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

Our work presents the primary account for exploring the forensics of immersive Virtual Reality (VR) systems and their social applications. The Social VR applications studied in this work include Bigscreen, Altspace VR, Rec Room and Facebook Spaces. We explored the two most widely adopted consumer VR systems: the HTC Vive and the Oculus Rift. Our tests examined the efficacy of reconstructing evidence from network traffic as well as the systems themselves. The results showed that a significant amount of forensically relevant data such as user names, user profile pictures, events, and system details may be recovered. We anticipate that this …

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Investigating Dataset Distinctiveness, Andrew Ulmer, Kent W. Gauen, Yung-Hsiang Lu, Zohar R. Kapach, Daniel P. Merrick Aug 2018

Investigating Dataset Distinctiveness, Andrew Ulmer, Kent W. Gauen, Yung-Hsiang Lu, Zohar R. Kapach, Daniel P. Merrick

The Summer Undergraduate Research Fellowship (SURF) Symposium

Just as a human might struggle to interpret another human’s handwriting, a computer vision program might fail when asked to perform one task in two different domains. To be more specific, visualize a self-driving car as a human driver who had only ever driven on clear, sunny days, during daylight hours. This driver – the self-driving car – would inevitably face a significant challenge when asked to drive when it is violently raining or foggy during the night, putting the safety of its passengers in danger. An extensive understanding of the data we use to teach computer vision models – …

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Sort Vs. Hash Join On Knights Landing Architecture, Victor L. Pan, Felix Lin Aug 2018

Sort Vs. Hash Join On Knights Landing Architecture, Victor L. Pan, Felix Lin

The Summer Undergraduate Research Fellowship (SURF) Symposium

With the increasing amount of information stored, there is a need for efficient database algorithms. One of the most important database operations is “join”. This involves combining columns from two tables and grouping common values in the same row in order to minimize redundant data. The two main algorithms used are hash join and sort merge join. Hash join builds a hash table to allow for faster searching. Sort merge join first sorts the two tables to make it more efficient when comparing values. There has been a lot of debate over which approach is superior. At first, hash join …

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Deep Neural Network Architectures For Modulation Classification Using Principal Component Analysis, Sharan Ramjee, Shengtai Ju, Diyu Yang, Aly El Gamal Aug 2018

Deep Neural Network Architectures For Modulation Classification Using Principal Component Analysis, Sharan Ramjee, Shengtai Ju, Diyu Yang, Aly El Gamal

The Summer Undergraduate Research Fellowship (SURF) Symposium

In this work, we investigate the application of Principal Component Analysis to the task of wireless signal modulation recognition using deep neural network architectures. Sampling signals at the Nyquist rate, which is often very high, requires a large amount of energy and space to collect and store the samples. Moreover, the time taken to train neural networks for the task of modulation classification is large due to the large number of samples. These problems can be drastically reduced using Principal Component Analysis, which is a technique that allows us to reduce the dimensionality or number of features of the samples …

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Security Services Using Blockchains: A State Of The Art Survey, Maeda Zolanvari, Aiman Erbad, Raj Jain, Mohammed Samaka Aug 2018

Security Services Using Blockchains: A State Of The Art Survey, Maeda Zolanvari, Aiman Erbad, Raj Jain, Mohammed Samaka

All Computer Science and Engineering Research

This article surveys blockchain-based approaches for several security services. These services include authentication, confidentiality, privacy and access control list (ACL), data and resource provenance, and integrity assurance. All these services are critical for the current distributed applications, especially due to the large amount of data being processed over the networks and the use of cloud computing. Authentication ensures that the user is who he/she claims to be. Confidentiality guarantees that data cannot be read by unauthorized users. Privacy provides the users the ability to control who can access their data. Provenance allows an efficient tracking of the data and resources …

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Scaling Up An Infrastructure For Controlled Experimentation With Testing Techniques, Wayne D. Motycka Aug 2018

Scaling Up An Infrastructure For Controlled Experimentation With Testing Techniques, Wayne D. Motycka

School of Computing: Dissertations, Theses, and Student Research

Software testing research often involves reproducing previous experimental results. Previous work created a repository infrastructure for containment and dissemination of testable research subjects using a private centralized storage mechanism for hosting these test subject archives. While this is a good way to store these subjects it can be inefficient when the size of subjects increases or the number of versions of the subject’s source code is large. The delivery of these large subjects from a centralized repository can be quite large and on occasion may not succeed requiring the user to repeat the download request. Coupled with the limited resources …

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Exact Processing Of Uncertain Top-K Queries In Multi-Criteria Settings, Kyriakos Mouratidis, Bo Tang Aug 2018

Exact Processing Of Uncertain Top-K Queries In Multi-Criteria Settings, Kyriakos Mouratidis, Bo Tang

Research Collection School Of Computing and Information Systems

Traditional rank-aware processing assumes a dataset that contains available options to cover a specific need (e.g., restaurants, hotels, etc) and users who browse that dataset via top-k queries with linear scoring functions, i.e., by ranking the options according to the weighted sum of their attributes, for a set of given weights. In practice, however, user preferences (weights) may only be estimated with bounded accuracy, or may be inherently uncertain due to the inability of a human user to specify exact weight values with absolute accuracy. Motivated by this, we introduce the uncertain top-k query (UTK). Given uncertain preferences, that is, …

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Learning Representations Of Ultrahigh-Dimensional Data For Random Distance-Based Outlier Detection, Guansong Pang, Longbing Cao, Ling Chen, Defu Lian, Huan Liu Aug 2018

Learning Representations Of Ultrahigh-Dimensional Data For Random Distance-Based Outlier Detection, Guansong Pang, Longbing Cao, Ling Chen, Defu Lian, Huan Liu

Research Collection School Of Computing and Information Systems

Learning expressive low-dimensional representations of ultrahigh-dimensional data, e.g., data with thousands/millions of features, has been a major way to enable learning methods to address the curse of dimensionality. However, existing unsupervised representation learning methods mainly focus on preserving the data regularity information and learning the representations independently of subsequent outlier detection methods, which can result in suboptimal and unstable performance of detecting irregularities (i.e., outliers).This paper introduces a ranking model-based framework, called RAMODO, to address this issue. RAMODO unifies representation learning and outlier detection to learn low-dimensional representations that are tailored for a state-of-the-art outlier detection approach - the random …

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Customer Segmentation Using Online Platforms: Isolating Behavioral And Demographic Segments For Persona Creation Via Aggregated User Data, Jisun An, Haewoon Kwak, Soon‑Gyo Jung, Joni Salminen, Bernard J. Jansen Aug 2018

Customer Segmentation Using Online Platforms: Isolating Behavioral And Demographic Segments For Persona Creation Via Aggregated User Data, Jisun An, Haewoon Kwak, Soon‑Gyo Jung, Joni Salminen, Bernard J. Jansen

Research Collection School Of Computing and Information Systems

We propose a novel approach for isolating customer segments using online customer data for products that are distributed via online social media platforms. We use non-negative matrix factorization to first identify behavioral customer segments and then to identify demographic customer segments. We employ a methodology for linking the two segments to present integrated and holistic customer segments, also known as personas. Behavioral segments are generated from customer interactions with online content. Demographic segments are generated using the gender, age, and location of these customers. In addition to evaluating our approach, we demonstrate its practicality via a system leveraging these customer …

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Code Smells For Model-View-Controller Architectures, Maurício Aniche, Gabriele Bavota, Christoph Treude, Marco Aurélio Gerosa, Arie Van Deursen Aug 2018

Code Smells For Model-View-Controller Architectures, Maurício Aniche, Gabriele Bavota, Christoph Treude, Marco Aurélio Gerosa, Arie Van Deursen

Research Collection School Of Computing and Information Systems

Previous studies have shown the negative effects that low-quality code can have on maintainability proxies, such as code change- and defect-proneness. One of the symptoms of low-quality code are code smells, defined as sub-optimal implementation choices. While this definition is quite general and seems to suggest a wide spectrum of smells that can affect software systems, the research literature mostly focuses on the set of smells defined in the catalog by Fowler and Beck, reporting design issues that can potentially affect any kind of system, regardless of their architecture (e.g., Complex Class). However, systems adopting a specific architecture (e.g., the …

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An Application Of Game Theory In Distributed Collaborative Decision Making, Angran Xiao Jul 2018

An Application Of Game Theory In Distributed Collaborative Decision Making, Angran Xiao

Publications and Research

In a distributed product realization environment, new paradigms and accompanying software systems are necessary to support the collaborative work of geographically dispersed engineering teams from different disciplines who have different knowledge, experience, tools and resources. To verify the concept of collaboration by separation, we propose a generic information communication medium to enable knowledge representation and exchange between engineering teams, a digital interface. Across digital interfaces, each engineering team maintains its own perspective towards the product realization problem, and each controls a subset of design variables and seeks to maximize its own payoff function subject to individual constraints. Hence, we postulate …

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An Ensemble Stacked Convolutional Neural Network Model For Environmental Event Sound Recognition, Shaobo Li, Yong Yao, Jie Hu, Guokai Liu, Xuemei Yao, Jianjun Hu Jul 2018

An Ensemble Stacked Convolutional Neural Network Model For Environmental Event Sound Recognition, Shaobo Li, Yong Yao, Jie Hu, Guokai Liu, Xuemei Yao, Jianjun Hu

Faculty Publications

Convolutional neural networks (CNNs) with log-mel audio representation and CNN-based end-to-end learning have both been used for environmental event sound recognition (ESC). However, log-mel features can be complemented by features learned from the raw audio waveform with an effective fusion method. In this paper, we first propose a novel stacked CNN model with multiple convolutional layers of decreasing filter sizes to improve the performance of CNN models with either log-mel feature input or raw waveform input. These two models are then combined using the Dempster–Shafer (DS) evidence theory to build the ensemble DS-CNN model for ESC. Our experiments over three …

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High-Performance Testbed For Vision-Aided Autonomous Navigation For Quadrotor Uavs In Cluttered Environments, Shakeeb Ahmad Jul 2018

High-Performance Testbed For Vision-Aided Autonomous Navigation For Quadrotor Uavs In Cluttered Environments, Shakeeb Ahmad

Electrical and Computer Engineering ETDs

This thesis presents the development of an aerial robotic testbed based on Robot Operating System (ROS). The purpose of this high-performance testbed is to develop a system capable of performing robust navigation tasks using vision tools such as a stereo camera. While ensuring the computation of robot odometery, the system is also capable of sensing the environment using the same stereo camera. Hence, all the navigation tasks are performed using a stereo camera and an inertial measurement unit (IMU) as the main sensor suite. ROS is used as a framework for software integration due to its capabilities to provide efficient …

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Compact Hardware Implementation Of A Sha-3 Core For Wireless Body Sensor Networks, Yi Yang, Debiao He, Neeraj Kumar, Sherali Zeadally Jul 2018

Compact Hardware Implementation Of A Sha-3 Core For Wireless Body Sensor Networks, Yi Yang, Debiao He, Neeraj Kumar, Sherali Zeadally

Information Science Faculty Publications

One of the most important Internet of Things applications is the wireless body sensor network (WBSN), which can provide universal health care, disease prevention, and control. Due to large deployments of small scale smart sensors in WBSNs, security, and privacy guarantees (e.g., security and safety-critical data, sensitive private information) are becoming a challenging issue because these sensor nodes communicate using an open channel, i.e., Internet. We implement data integrity (to resist against malicious tampering) using the secure hash algorithm 3 (SHA-3) when smart sensors in WBSNs communicate with each other using the Internet. Due to the limited resources (i.e., storage, …

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Survey Results On Adults And Cybersecurity Education, Frank Breitinger, Joseph Ricci, Ibrahim Baggili Jul 2018

Survey Results On Adults And Cybersecurity Education, Frank Breitinger, Joseph Ricci, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

Cyberattacks and identity theft are common problems nowadays where researchers often say that humans are the weakest link in the security chain. Therefore, this survey focused on analyzing the interest for adults for ‘cyber threat education seminars’, e.g., how to project themselves and their loved ones. Specifically, we asked questions to understand a possible audience, willingness for paying / time commitment, or fields of interest as well as background and previous training experience. The survey was conducted in late 2016 and taken by 233 participants. The results show that many are worried about cyber threats and about their children exploring …

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Adaptive Virtual Impedance Droop Control Based On Consensus Control Of Reactive Current, Zhilin Lu, Qing Wei, Yiyi Zhang, Junhui Zhao, Emad Manla Jul 2018

Adaptive Virtual Impedance Droop Control Based On Consensus Control Of Reactive Current, Zhilin Lu, Qing Wei, Yiyi Zhang, Junhui Zhao, Emad Manla

Electrical & Computer Engineering and Computer Science Faculty Publications

It is difficult to achieve accurate distribution of reactive power based on conventional droop control due to the line impedance mismatch in an islanded microgrid. An adaptive virtual impendence method based on consensus control of reactive current is proposed in this paper. A distributed control structure without the central controller has been established. In this structure, each distributed generation unit (DG) is an independent agent, one-way communication is used between the adjacent DGs, and the reactive power sharing is equivalent to a problem of reactive power current consensus. It has been proven that the system is asymptotically stable under the …

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Moving Target Defense For Securing Scada Communications, Vahid Heydari Jul 2018

Moving Target Defense For Securing Scada Communications, Vahid Heydari

College of Science & Mathematics Departmental Research

In this paper, we introduce a framework for building a secure and private peer to peer communication used in supervisory control and data acquisition networks with a novel Mobile IPv6-based moving target defense strategy. Our approach aids in combating remote cyber-attacks against peer hosts by thwarting any potential attacks at their reconnaissance stage. The IP address of each host is randomly changed at a certain interval creating a moving target to make it difficult for an attacker to find the host. At the same time, the peer host is updated through the use of the binding update procedure (standard Mobile …

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A Building Permit System For Smart Cities: A Cloud-Based Framework, Magdalini Eirinaki, Subhankar Dhar, Shishir Mathur, Adwait Kaley, Arpit Patel, Akshar Joshi, Dhvani Shah Jul 2018

A Building Permit System For Smart Cities: A Cloud-Based Framework, Magdalini Eirinaki, Subhankar Dhar, Shishir Mathur, Adwait Kaley, Arpit Patel, Akshar Joshi, Dhvani Shah

Faculty Publications

In this paper we propose a novel, cloud-based framework to support citizens and city officials in the building permit process. The proposed framework is efficient, user-friendly, and transparent with a quick turn-around time for homeowners. Compared to 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 both the end user experience and the permitting and urban planning processes. This is enabled through a data mining-powered permit recommendation engine as well as a data analytics process that allow a gleaning of key …

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The Use Of Recommender Systems In Web Applications – The Troi Case, Donjeta Mulaj Jul 2018

The Use Of Recommender Systems In Web Applications – The Troi Case, Donjeta Mulaj

Theses and Dissertations

Avoiding digital marketing, surveys, reviews and online users behavior approaches on digital age are the key elements for a powerful businesses to fail, there are some systems that should preceded some artificial intelligence techniques. In this direction, the use of data mining for recommending relevant items as a new state of the art technique is increasing user satisfaction as well as the business revenues. And other related information gathering approaches in order to our systems thing and acts like humans. To do so there is a Recommender System that will be elaborated in this thesis. How people interact, how to …

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Performanca E Makinave Kerkuese Duke Perdorur Cloud Shërbimet “Elasticsearch” Dhe “Algolia”, Besnik Korça Jul 2018

Performanca E Makinave Kerkuese Duke Perdorur Cloud Shërbimet “Elasticsearch” Dhe “Algolia”, Besnik Korça

Theses and Dissertations

Ueb Aplikacionet me data-set të mëdha në kohën e tanishme janë shumë më të përhapura. Kërkimet e të dhënave në data-set të tilla për shkak të performances bëhen duke përdorur makinat kërkuese. Provider të ndryshëm ofrojnë makina kërkuese si Software as a Service(SaaS) shërbime të cilat kanë për avantazh konfigurimin minimal që duhet bërë makinave kërkuese për t’i vënë në funksion. Nëpërmjet këtij punimi synohet që së pari të analizohen shërbimet cloud computing që ofrohen nga provider të ndryshem. Pastaj pasi që fokusi i makinave kërkuese ndodhet në “information retrieval” është bë analizimi i disa teknikave të “information retrieval”. Makinat …

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Identification And Optimal Linear Tracking Control Of Odu Autonomous Surface Vehicle, Nadeem Khan Jul 2018

Identification And Optimal Linear Tracking Control Of Odu Autonomous Surface Vehicle, Nadeem Khan

Mechanical & Aerospace Engineering Theses & Dissertations

Autonomous surface vehicles (ASVs) are being used for diverse applications of civilian and military importance such as: military reconnaissance, sea patrol, bathymetry, environmental monitoring, and oceanographic research. Currently, these unmanned tasks can accurately be accomplished by ASVs due to recent advancements in computing, sensing, and actuating systems. For this reason, researchers around the world have been taking interest in ASVs for the last decade. Due to the ever-changing surface of water and stochastic disturbances such as wind and tidal currents that greatly affect the path-following ability of ASVs, identification of an accurate model of inherently nonlinear and stochastic ASV system …

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Compositional Reasoning For Shared-Variable Concurrent Programs, Fuyuan Zhang, Yongwang Zhao, David Sanan, Yang Liu, Alwen Tiu, Shang-Wei Lin, Jun Sun Jul 2018

Compositional Reasoning For Shared-Variable Concurrent Programs, Fuyuan Zhang, Yongwang Zhao, David Sanan, Yang Liu, Alwen Tiu, Shang-Wei Lin, Jun Sun

Research Collection School Of Computing and Information Systems

Scalable and automatic formal verification for concurrent systems is always demanding. In this paper, we propose a verification framework to support automated compositional reasoning for concurrent programs with shared variables. Our framework models concurrent programs as succinct automata and supports the verification of multiple important properties. Safety verification and simulations of succinct automata are parallel compositional, and safety properties of succinct automata are preserved under refinements. We generate succinct automata from infinite state concurrent programs in an automated manner. Furthermore, we propose the first automated approach to checking rely-guarantee based simulations between infinite state concurrent programs. We have prototyped our …

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Experience Constructing The Artifact Genome Project (Agp): Managing The Domain's Knowledge One Artifact At A Time, Cinthya Grajeda, Laura Sanchez, Ibrahim Baggili, Devon R. Clark, Frank Breitinger Jul 2018

Experience Constructing The Artifact Genome Project (Agp): Managing The Domain's Knowledge One Artifact At A Time, Cinthya Grajeda, Laura Sanchez, Ibrahim Baggili, Devon R. Clark, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

While various tools have been created to assist the digital forensics community with acquiring, processing, and organizing evidence and indicating the existence of artifacts, very few attempts have been made to establish a centralized system for archiving artifacts. The Artifact Genome Project (AGP) has aimed to create the largest vetted and freely available digital forensics repository for Curated Forensic Artifacts (CuFAs). This paper details the experience of building, implementing, and maintaining such a system by sharing design decisions, lessons learned, and future work. We also discuss the impact of AGP in both the professional and academic realms of digital forensics. …

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Privacy-Preserving Mining Of Association Rule On Outsourced Cloud Data From Multiple Parties, Lin Liu, Jinshu Su, Rongmao Chen, Ximeng Liu, Xiaofeng Wang, Shuhui Chen, Ho-Fung Fung Leung Jul 2018

Privacy-Preserving Mining Of Association Rule On Outsourced Cloud Data From Multiple Parties, Lin Liu, Jinshu Su, Rongmao Chen, Ximeng Liu, Xiaofeng Wang, Shuhui Chen, Ho-Fung Fung Leung

Research Collection School Of Computing and Information Systems

It has been widely recognized as a challenge to carry out data analysis and meanwhile preserve its privacy in the cloud. In this work, we mainly focus on a well-known data analysis approach namely association rule mining. We found that the data privacy in this mining approach have not been well considered so far. To address this problem, we propose a scheme for privacy-preserving association rule mining on outsourced cloud data which are uploaded from multiple parties in a twin-cloud architecture. In particular, we mainly consider the scenario where the data owners and miners have different encryption keys that are …

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A Unified Approach To Route Planning For Shared Mobility, Yongxin Tong, Yuxiang Zeng, Zimu Zhou, Lei Chen, Jieping Ye, Ke Xu Jul 2018

A Unified Approach To Route Planning For Shared Mobility, Yongxin Tong, Yuxiang Zeng, Zimu Zhou, Lei Chen, Jieping Ye, Ke Xu

Research Collection School Of Computing and Information Systems

There has been a dramatic growth of shared mobility applications such as ride-sharing, food delivery and crowdsourced parcel delivery. Shared mobility refers to transportation services that are shared among users, where a central issue is route planning. Given a set of workers and requests, route planning finds for each worker a route, i.e., a sequence of locations to pick up and drop off passengers/parcels that arrive from time to time, with different optimization objectives. Previous studies lack practicability due to their conflicted objectives and inefficiency in inserting a new request into a route, a basic operation called insertion. In this …

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