Disaster Recovery System And Service Continuity Of Digital Library,
2021
Hindustan University
Disaster Recovery System And Service Continuity Of Digital Library, Sivankalai S, Virumandi A, Sivasekaran K, Sharmila M
Library Philosophy and Practice (e-journal)
This paper will discuss catastrophe recovery and likelihood development for digital library structures. The article establishes a foundation for establishing Library continuity and disaster recovery strategies through the use of best practices. Library continuity development and catastrophe recovery are critical modules of the planning stage for a virtual digital library. Few institutions that experience a catastrophic disaster occurrence are powerless to recover always, but libraries can suggestively boost the possibility of long-term recovery of institutional digital resources by drafting a continuity and recovery strategy in preparation. This article is intended for system designers and administrators, as well as high-ranking library …
A Survey On Various Image Inpainting Techniques,
2021
Electrical Engineering Department - Future University in Egypt
A Survey On Various Image Inpainting Techniques, Nermin Mohamed Fawzy Salem Phd
Future Engineering Journal
Over the decades' researchers have studied the image inpainting problem intensively due to its high significance and effectiveness in various image processing applications such as people and object security, object removal, face editing applications. Image inpainting is defined as the process of completing or removing a missing region in images. It is considered one of the most challenging topics in the image processing field, although, it requires a deep understanding of the image details in terms of texture and structure. In this paper, a survey of most image inpainting techniques is presented and summarized with comparisons including the merits and …
Learning State-Dependent Sensor Measurement Models To Improve Robot Localization Accuracy,
2021
University of South Florida
Learning State-Dependent Sensor Measurement Models To Improve Robot Localization Accuracy, Troi André Williams
USF Tampa Graduate Theses and Dissertations
This dissertation proposes a novel method called state-dependent sensor measurement models (SDSMMs). Such models dynamically predict the state-dependent bias and uncertainty of sensor measurements, ultimately improving fundamental robot tasks such as localization. In our first investigation, we introduced the state-dependent sensor measurement model framework, described their properties, stated the input and output of these models, and described how to train them. We also explained how to integrate such models with an Extended Kalman Filter and a Particle Filter, two popular robot state estimation algorithms. We validated the proposed framework through a series of localization tasks. The results showed that our …
Don't Bite The Bait: Phishing Attack For Internet Banking (E-Banking),
2021
Cankiri Karatekin University
Don't Bite The Bait: Phishing Attack For Internet Banking (E-Banking), Ilker Kara
Journal of Digital Forensics, Security and Law
Phishing attacks are based on obtaining desired information from users quickly and easily with the help of misdirecting, panicking, curiosity, or excitement. Most of the phishing web sites are designed on internet banking(e-banking) and the attackers can acquire financial information of misled users with the tactics and discourses they develop. Despite the increase of prevention techniques against phishing attacks day by day, an effective solution could not be found for this issue due to the human factor. Because of this reason, real phishing attack studies are essential to study and analyze the attackers’ attack techniques and strategies. This study focused …
Intelligent Internet Of Things Frameworks For Smart City Safety,
2021
Doctoral Student, Electrical and Computer Engineering
Intelligent Internet Of Things Frameworks For Smart City Safety, Dimitrios Sikeridis
Electrical and Computer Engineering ETDs
The emerging Smart City ecosystem consists of a vast edge network of Internet of Things (IoT) devices that continuously interact with mobile devices carried by its citizens. In this setting, the IoT infrastructure, apart from the main communications facilitator, acts as a crowdsourcing mechanism that collects massive amounts of user data, and can support public safety applications for the Smart City. In this thesis, we design and analyze learning mechanisms that extract intelligence from crowd interactions with the wireless IoT infrastructure, and optimize its energy efficiency while operating as a public safety network. First, we deploy a multi-story facility testbed …
Cybert: Cybersecurity Claim Classification By Fine-Tuning The
Bert Language Model,
2021
University of Nebraska-Lincoln
Cybert: Cybersecurity Claim Classification By Fine-Tuning The Bert Language Model, Kimia Ameri, Michael Hempel, Hamid Sharif, Juan Lopez Jr., Kalyan Perumalla
Department of Electrical and Computer Engineering: Faculty Publications
We introduce CyBERT, a cybersecurity feature claims classifier based on bidirectional encoder representations from transformers and a key component in our semi-automated cybersecurity vetting for industrial control systems (ICS). To train CyBERT, we created a corpus of labeled sequences from ICS device documentation collected across a wide range of vendors and devices. This corpus provides the foundation for fine-tuning BERT’s language model, including a prediction-guided relabeling process. We propose an approach to obtain optimal hyperparameters, including the learning rate, the number of dense layers, and their configuration, to increase the accuracy of our classifier. Fine-tuning all hyperparameters of the resulting …
Reliability Models For Smartphone Applications,
2021
Western University
Reliability Models For Smartphone Applications, Sonia Meskini, Ali Bou Nassif, Luiz Fernando Capretz
Electrical and Computer Engineering Publications
Smartphones have become the most used electronic devices. They carry out most of the functionalities of desktops, offering various useful applications that suit the user’s needs. Therefore, instead of the operator, the user has been the main controller of the device and its applications, therefore its reliability has become an emergent requirement. As a first step, based on collected smartphone applications failure data, we investigated and evaluated the efficacy of Software Reliability Growth Models (SRGMs) when applied to these smartphone data in order to check whether they achieve the same accuracy as in the desktop/laptop area. None of the selected …
Protection Of Patient Privacy On Mobile Device Machine Learning,
2021
Old Dominion University
Protection Of Patient Privacy On Mobile Device Machine Learning, Matthew Nguyen
Cybersecurity Undergraduate Research Showcase
An existing StudentLife Study mobile dataset was evaluated and organized to be applied to different machine learning methods. Different variables like user activity, exercise, sleep, study space, social, and stress levels are optimized to train a model that could predict user stress level. The different machine learning methods would test if both patient data privacy and training efficiency can be ensured.
Efficient Server-Aided Secure Two-Party Computation In Heterogeneous Mobile Cloud Computing,
2021
Singapore Management University
Efficient Server-Aided Secure Two-Party Computation In Heterogeneous Mobile Cloud Computing, Yulin Wu, Xuan Wang, Willy Susilo, Guomin Yang, Zoe L. Jiang, Qian Chen, Peng Xu
Research Collection School Of Computing and Information Systems
With the ubiquity of mobile devices and rapid development of cloud computing, mobile cloud computing (MCC) has been considered as an essential computation setting to support complicated, scalable and flexible mobile applications by overcoming the physical limitations of mobile devices with the aid of cloud. In the MCC setting, since many mobile applications (e.g., map apps) interacting with cloud server and application server need to perform computation with the private data of users, it is important to realize secure computation for MCC. In this article, we propose an efficient server-aided secure two-party computation (2PC) protocol for MCC. This is the …
Traffic Collision Avoidance System: False Injection Viability,
2021
Air Force Institute of Technology
Traffic Collision Avoidance System: False Injection Viability, John Hannah, Robert F. Mills, Richard Dill, Douglas D. Hodson
Faculty Publications
Safety is a simple concept but an abstract task, specifically with aircraft. One critical safety system, the Traffic Collision Avoidance System II (TCAS), protects against mid-air collisions by predicting the course of other aircraft, determining the possibility of collision, and issuing a resolution advisory for avoidance. Previous research to identify vulnerabilities associated with TCAS’s communication processes discovered that a false injection attack presents the most comprehensive risk to veritable trust in TCAS, allowing for a mid-air collision. This research explores the viability of successfully executing a false injection attack against a target aircraft, triggering a resolution advisory. Monetary constraints precluded …
Concolic Execution Of Nmap Scripts For Honeyfarm Generation,
2021
Portland State University
Concolic Execution Of Nmap Scripts For Honeyfarm Generation, Zhe Li, Bo Chen, Wu-Chang Feng, Fei Xie
Computer Science Faculty Publications and Presentations
Attackers rely upon a vast array of tools for automating attacksagainst vulnerable servers and services. It is often the case thatwhen vulnerabilities are disclosed, scripts for detecting and exploit-ing them in tools such asNmapandMetasploitare released soonafter, leading to the immediate identification and compromise ofvulnerable systems. Honeypots, honeynets, tarpits, and other decep-tive techniques can be used to slow attackers down, however, such approaches have difficulty keeping up with the sheer number of vulnerabilities being discovered and attacking scripts that are being released. To address this issue, this paper describes an approach for applying concolic execution on attacking scripts in Nmap in …
Formulating Automated Responses To Cognitive Distortions For Cbt Interactions,
2021
Technological University Dublin
Formulating Automated Responses To Cognitive Distortions For Cbt Interactions, Ignacio De Toledo, Giancarlo Salton, Robert J. Ross
Conference papers
One of the key ideas of Cognitive Behavioural Therapy (CBT) is the ability to convert negative or distorted thoughts into more realistic alternatives. Although modern machine learning techniques can be successfully applied to a variety of Natural Language Processing tasks, including Cognitive Behavioural Therapy, the lack of a publicly available dataset makes supervised training difficult for tasks such as reforming distorted thoughts. In this research, we constructed a small CBT dataset via crowd-sourcing, and leveraged state of the art pre-trained architectures to transform cognitive distortions, producing text that is relevant and more positive than the original negative thoughts. In particular, …
Warshipping: Hacking The Mailroom,
2021
University of North Georgia
Warshipping: Hacking The Mailroom, Jackson Szwast, Bryson Payne
KSU Proceedings on Cybersecurity Education, Research and Practice
Everyone knows what package shipping is, but not everyone knows what warshipping is. Corporate mailrooms are rarely considered as part of the cybersecurity attack surface of most organizations, but they offer physical access to millions of uninspected packages daily. UPS shipped 5.5 billion items last year, with their daily average being 21.9 million items and operating through 1,800 locations in 2020. FedEx shipped 6.5 million packages daily and operates 2,150 locations. The United States Postal Service delivered 143 billion pieces of mail in 2019. Increasingly the world’s consumers are relying on e-commerce, and during the recent COVID-19 pandemic, package deliveries …
Study On The Implications Of Automomous Ships On Maritime Security And Law Enforcement By Reviewing Maritime Security Incidents,
2021
World Maritime University
Study On The Implications Of Automomous Ships On Maritime Security And Law Enforcement By Reviewing Maritime Security Incidents, Aditya Pratap Singh
World Maritime University Dissertations
No abstract provided.
Resampling And Super-Resolution Of Hexagonally Sampled Images Using Deep Learning,
2021
University of Dayton
Resampling And Super-Resolution Of Hexagonally Sampled Images Using Deep Learning, Dylan Flaute, Russell C. Hardie, Hamed Elwarfalli
Electrical and Computer Engineering Faculty Publications
Super-resolution (SR) aims to increase the resolution of imagery. Applications include security, medical imaging, and object recognition. We propose a deep learning-based SR system that takes a hexagonally sampled low-resolution image as an input and generates a rectangularly sampled SR image as an output. For training and testing, we use a realistic observation model that includes optical degradation from diffraction and sensor degradation from detector integration. Our SR approach first uses non-uniform interpolation to partially upsample the observed hexagonal imagery and convert it to a rectangular grid. We then leverage a state-of-the-art convolutional neural network (CNN) architecture designed for SR …
Trilateration-Based Localization In Known Environments With Object Detection,
2021
University of South Florida
Trilateration-Based Localization In Known Environments With Object Detection, Valeria M. Salas Pacheco
USF Tampa Graduate Theses and Dissertations
Many strategies for localization have been proposed, the majority of which rely on distance calculations and estimates. The proposed approach is a method that combines image-based single-camera localization techniques and the principle of trilateration to perform localization in a known indoor environment. By using a camera, the proposed system can detect custom objects using object detection in an indoor environment and calculate an approximation of the camera’s position. To recognize the location, previous information such as the size of the environment and the coordinates and sizes of the objects in the environment are given as input to the system together …
Generating Synthetic Training Data For Deep Learning-Based Uav Trajectory Prediction,
2021
University of Nevada, Las Vegas
Generating Synthetic Training Data For Deep Learning-Based Uav Trajectory Prediction, Brendan T. Morris, Stefan Becker, Ronny Hug, Wolfgang Huebner, Michael Arens
Electrical & Computer Engineering Faculty Research
Deep learning-based models, such as recurrent neural networks (RNNs), have been applied to various sequence learning tasks with great success. Following this, these models are increasingly replacing classic approaches in object tracking applications for motion prediction. On the one hand, these models can capture complex object dynamics with less modeling required, but on the other hand, they depend on a large amount of training data for parameter tuning. Towards this end, we present an approach for generating synthetic trajectory data of unmanned-aerial-vehicles (UAVs) in image space. Since UAVs, or rather quadrotors are dynamical systems, they can not follow arbitrary trajectories. …
A Reduced-Order Lumped Model For Li-Ion Battery Packs During Operation,
2021
University of South Carolina
A Reduced-Order Lumped Model For Li-Ion Battery Packs During Operation, Paul T. Coman, Eric C. Darcy, Brad Strangways, Ralph E. White
Faculty Publications
Modeling heat distribution in Li-ion battery packs can be challenging, especially if the battery pack is large and the cells are operated at high C-rates, which usually requires high-order physics-based mathematical models. Reduced and simplifying models can, however, be used at lower rates. This paper presents a fast novel reduced lumped model (RLM) that can be used to calculate the temperature increase during the high-current discharge of cylindrical Li-ion cells in a subscale of a battery pack. By reducing the PDE utilized to calculate the state of charge (SoC) to ODE's and solving them analytically, the reduced model can be …
Modeling And Simulation Of Crowd Multi-Perception Behavior Model In Closed Public Places,
2021
School of Management and Engineering, Capital University of Economics and Business, Beijing 100070, China;
Modeling And Simulation Of Crowd Multi-Perception Behavior Model In Closed Public Places, Ma Jun, Hu Jun
Journal of System Simulation
Abstract: The social forces-based multi-agent modeling method is used to build the crowd simulation models in most of the existing crowd behavior simulation software systems. From the perspective of cognitive psychology, combined with the spatial logic model of the generalized influence of the crowd obtained by the author’s previous research, and based on the sigmoid function, the mathematical model of the individual visual and auditory perception of the crowd is constructed. Taking the typical subway transfer hall as an example, the objective function of large passenger volume evacuation optimization is established to construct the crowd evacuation simulation model. The simulation …
High Performance Simulation Method And Test Platform For Full Envelop Of Flight Vehicle,
2021
1. Key Laboratory of Space Physics, Beijing 100076, China; ;
High Performance Simulation Method And Test Platform For Full Envelop Of Flight Vehicle, Jianlin Wang, Sufang Chen, Tie Ming, Liu Jing, Zhang Jun
Journal of System Simulation
Abstract: In order to meet the needs of the overall performance simulation and verification of the vehicle with large subsamples and massive states, a high-performance simulation method is proposed, in which a parallel simulation architecture based on high-performance computers is established, the technologies and software such as decoupling of simulation tasks, real-time monitoring of simulation, concurrent conflict control and automatic aggregation of large-scale test results are realized, and a test platform for the large-scale parallel verification of flight performance is developed. Simulation results show that the method has high acceleration ratio and scalability, and can complete the verification efficiently, …
