Open Access. Powered by Scholars. Published by Universities.®

Physical Sciences and Mathematics Commons™

Open Access. Powered by Scholars. Published by Universities.®

Discipline
Institution
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 16591 - 16620 of 302419

Full-Text Articles in Physical Sciences and Mathematics

Solving Turkish Math Word Problems By Sequence-To-Sequence Encoder-Decoder Models, Esi̇n Gedi̇k, Tunga Güngör Mar 2023

Solving Turkish Math Word Problems By Sequence-To-Sequence Encoder-Decoder Models, Esi̇n Gedi̇k, Tunga Güngör

Turkish Journal of Electrical Engineering and Computer Sciences

Solving math word problems (MWP) is a challenging task due to the semantic gap between natural language texts and mathematical equations. The main purpose of the task is to take a written math problem as input and produce a proper equation as output for solving that problem. This paper describes a sequence-to-sequence (seq2seq) neural model for automatically solving Turkish MWPs based on their semantic meanings in the text. It comprises a bidirectional encoder to comprehend the semantics of the problem by encoding the input sequence and a decoder with attention to extract the equation by tracking the semantic meanings of …

Go to article

The Vehicle Routing Problem With Simultaneous Pickup And Delivery And Occasional Drivers, Vincent F. Yu, Grace Aloina, Panca Jodiawan, Aldy Gunawan, Tsung-C. Huang Mar 2023

The Vehicle Routing Problem With Simultaneous Pickup And Delivery And Occasional Drivers, Vincent F. Yu, Grace Aloina, Panca Jodiawan, Aldy Gunawan, Tsung-C. Huang

Research Collection School Of Computing and Information Systems

This research addresses the Vehicle Routing Problem with Simultaneous Pickup and Delivery and Occasional Drivers (VRPSPDOD), which is inspired from the importance of addressing product returns and the emerging notion of involving available crowds to perform pickup and delivery activities in exchange for some compensation. At the depot, a set of regular vehicles is available to deliver and/or pick up customers’ goods. A set of occasional drivers, each defined by their origin, destination, and flexibility, is also able to help serve the customers. The objective of VRPSPDOD is to minimize the total traveling cost of operating regular vehicles and total …

Go to article

Specification-Based Autonomous Driving System Testing, Yuan Zhou, Yang Sun, Yun Tang, Yuqi Chen, Jun Sun, Christopher M. Poskitt, Yang Liu, Zijiang Yang Mar 2023

Specification-Based Autonomous Driving System Testing, Yuan Zhou, Yang Sun, Yun Tang, Yuqi Chen, Jun Sun, Christopher M. Poskitt, Yang Liu, Zijiang Yang

Research Collection School Of Computing and Information Systems

Autonomous vehicle (AV) systems must be comprehensively tested and evaluated before they can be deployed. High-fidelity simulators such as CARLA or LGSVL allow this to be done safely in very realistic and highly customizable environments. Existing testing approaches, however, fail to test simulated AVs systematically, as they focus on specific scenarios and oracles (e.g., lane following scenario with the "no collision" requirement) and lack any coverage criteria measures. In this paper, we propose AVUnit, a framework for systematically testing AV systems against customizable correctness specifications. Designed modularly to support different simulators, AVUnit consists of two new languages for specifying dynamic …

Go to article

Design, Development, And Evaluation Of An Interactive Personalized Social Robot To Monitor And Coach Post-Stroke Rehabilitation Exercises, Min Hun Lee, Daniel P. Siewiorek, Asim Smailagic, Alexandre Bernardino, Sergi Bermudez I Badia Mar 2023

Design, Development, And Evaluation Of An Interactive Personalized Social Robot To Monitor And Coach Post-Stroke Rehabilitation Exercises, Min Hun Lee, Daniel P. Siewiorek, Asim Smailagic, Alexandre Bernardino, Sergi Bermudez I Badia

Research Collection School Of Computing and Information Systems

Socially assistive robots are increasingly being explored to improve the engagement of older adults and people with disability in health and well-being-related exercises. However, even if people have various physical conditions, most prior work on social robot exercise coaching systems has utilized generic, predefined feedback. The deployment of these systems still remains a challenge. In this paper, we present our work of iteratively engaging therapists and post-stroke survivors to design, develop, and evaluate a social robot exercise coaching system for personalized rehabilitation. Through interviews with therapists, we designed how this system interacts with the user and then developed an interactive …

Go to article

Concept-Oriented Transformers For Visual Sentiment Analysis, Quoc Tuan Truong, Hady Wirawan Lauw Mar 2023

Concept-Oriented Transformers For Visual Sentiment Analysis, Quoc Tuan Truong, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

In the richly multimedia Web, detecting sentiment signals expressed in images would support multiple applications, e.g., measuring customer satisfaction from online reviews, analyzing trends and opinions from social media. Given an image, visual sentiment analysis aims at recognizing positive or negative sentiment, and occasionally neutral sentiment as well. A nascent yet promising direction is Transformer-based models applied to image data, whereby Vision Transformer (ViT) establishes remarkable performance on largescale vision benchmarks. In addition to investigating the fitness of ViT for visual sentiment analysis, we further incorporate concept orientation into the self-attention mechanism, which is the core component of Transformer. The …

Go to article

Generalizing Graph Neural Network Across Graphs And Time, Zhihao Wen Mar 2023

Generalizing Graph Neural Network Across Graphs And Time, Zhihao Wen

Research Collection School Of Computing and Information Systems

Graph-structured data widely exist in diverse real-world scenarios, analysis of these graphs can uncover valuable insights about their respective application domains. However, most previous works focused on learning node representation from a single fixed graph, while many real-world scenarios require representations to be quickly generated for unseen nodes, new edges, or entirely new graphs. This inductive ability is essential for high-throughtput machine learning systems. However, this inductive graph representation problem is quite difficult, compared to the transductive setting, for that generalizing to unseen nodes requires new subgraphs containing the new nodes to be aligned to the neural network trained already. …

Go to article

Proactive Conversational Agents, Lizi Liao, Grace Hui Yang, Chirag Shah Mar 2023

Proactive Conversational Agents, Lizi Liao, Grace Hui Yang, Chirag Shah

Research Collection School Of Computing and Information Systems

Conversational agents, or commonly known as dialogue systems, have gained escalating popularity in recent years. Their widespread applications support conversational interactions with users and accomplishing various tasks as personal assistants. However, one key weakness in existing conversational agents is that they only learn to passively answer user queries via training on pre-collected and manually-labeled data. Such passiveness makes the interaction modeling and system-building process relatively easier, but it largely hinders the possibility of being human-like hence lowering the user engagement level. In this tutorial, we introduce and discuss methods to equip conversational agents with the ability to interact with end …

Go to article

Green Data Analytics Of Supercomputing From Massive Sensor Networks: Does Workload Distribution Matter?, Zhiling Guo, Jin Li, Ram Ramesh Mar 2023

Green Data Analytics Of Supercomputing From Massive Sensor Networks: Does Workload Distribution Matter?, Zhiling Guo, Jin Li, Ram Ramesh

Research Collection School Of Computing and Information Systems

Energy costs represent a significant share of the total cost of ownership in high performance computing (HPC) systems. Using a unique data set collected by massive sensor networks in a peta scale national supercomputing center, we first present an explanatory model to identify key factors that affect energy consumption in supercomputing. Our analytic results show that, not only does computing node utilization significantly affect energy consumption, workload distribution among the nodes also has significant effects and could effectively be leveraged to improve energy efficiency. Next, we establish the high model performance using in-sample and out-of-sample analyses. We then develop prescriptive …

Go to article

Blockscope: Detecting And Investigating Propagated Vulnerabilities In Forked Blockchain Projects, Xiao Yi, Yuzhou Fang, Daoyuan Wu, Lingxiao Jiang Mar 2023

Blockscope: Detecting And Investigating Propagated Vulnerabilities In Forked Blockchain Projects, Xiao Yi, Yuzhou Fang, Daoyuan Wu, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Due to the open-source nature of the blockchain ecosystem, it is common for new blockchains to fork or partially reuse the code of classic blockchains. For example, the popular Dogecoin, Litecoin, Binance BSC, and Polygon are all variants of Bitcoin/Ethereum. These “forked” blockchains thus could encounter similar vulnerabilities that are propagated from Bitcoin/Ethereum during forking or subsequently commit fetching. In this paper, we conduct a systematic study of detecting and investigating the propagated vulnerabilities in forked blockchain projects. To facilitate this study, we propose BlockScope, a novel tool that can effectively and efficiently detect multiple types of cloned vulnerabilities given …

Go to article

Volere: Leakage Resilient User Authentication Based On Personal Voice Challenges, Rui Zhang, Zheng Yan, Xuerui Wang, Robert H. Deng Mar 2023

Volere: Leakage Resilient User Authentication Based On Personal Voice Challenges, Rui Zhang, Zheng Yan, Xuerui Wang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Voiceprint Authentication as a Service (VAaS) offers great convenience due to ubiquity, generality, and usability. Despite its attractiveness, it suffers from user voiceprint leakage over the air or at the cloud, which intrudes user voice privacy and retards its wide adoption. The literature still lacks an effective solution on this issue. Traditional methods based on cryptography are too complex to be practically deployed while other approaches distort user voiceprints, which hinders accurate user identification. In this article, we propose a leakage resilient user authentication cloud service with privacy preservation based on random personal voice challenges, named VOLERE (VOice LEakage REsilient). …

Go to article

Towards A Design Space For Storytelling On The Fashion Technology Runway, Sydney Pratte, Anthony Tang, Shannon Hoover, Maria Elena Hoover, Matt Laprarie, Catherine Larose, Lora Oehlberg Mar 2023

Towards A Design Space For Storytelling On The Fashion Technology Runway, Sydney Pratte, Anthony Tang, Shannon Hoover, Maria Elena Hoover, Matt Laprarie, Catherine Larose, Lora Oehlberg

Research Collection School Of Computing and Information Systems

Fashion is driven by a narrative, i.e. a story or idea that the designer wants to convey to the audience. Fashion-tech now adds another dimension to this narrative through dynamically changing aspects of the garments. Many factors of presentation in a runway show affect how fashion-tech garments communicate a story to the audience. In this pictorial, we review a set of twenty-eight storytelling fashion-tech garments. We identify, catalogue, and categorize the factors designers used to convey stories to the audience from the runway. The design space consists of three levels: (1) the artifact-level, (2) the viewer-level, and (3) the context-level. …

Go to article

Investigating Guardian Awareness Techniques To Promote Safety In Virtual Reality, Sixuan Wu, Jiannan Li, Maurício Sousa, Tovi Grossman Mar 2023

Investigating Guardian Awareness Techniques To Promote Safety In Virtual Reality, Sixuan Wu, Jiannan Li, Maurício Sousa, Tovi Grossman

Research Collection School Of Computing and Information Systems

Virtual Reality (VR) can completely immerse users in a virtual world and provide little awareness of bystanders in the surrounding physical environment. Current technologies use predefined guardian area visualizations to set safety boundaries for VR interactions. However, bystanders cannot perceive these boundaries and may collide with VR users if they accidentally enter guardian areas. In this paper, we investigate four awareness techniques on mobile phones and smartwatches to help bystanders avoid invading guardian areas. These techniques include augmented reality boundary overlays and visual, auditory, and haptic alerts indicating bystanders' distance from guardians. Our findings suggest that the proposed techniques effectively …

Go to article

A Review On Learning To Solve Combinatorial Optimisation Problems In Manufacturing, Cong Zhang, Yaoxin Wu, Yining Ma, Wen Song, Zhang Le, Zhiguang Cao, Jie Zhang Mar 2023

A Review On Learning To Solve Combinatorial Optimisation Problems In Manufacturing, Cong Zhang, Yaoxin Wu, Yining Ma, Wen Song, Zhang Le, Zhiguang Cao, Jie Zhang

Research Collection School Of Computing and Information Systems

An efficient manufacturing system is key to maintaining a healthy economy today. With the rapid development of science and technology and the progress of human society, the modern manufacturing system is becoming increasingly complex, posing new challenges to both academia and industry. Ever since the beginning of industrialisation, leaps in manufacturing technology have always accompanied technological breakthroughs from other fields, for example, mechanics, physics, and computational science. Recently, machine learning (ML) technology, one of the crucial subjects of artificial intelligence, has made remarkable progress in many areas. This study thoroughly reviews how ML, specifically deep (reinforcement) learning, motivates new ideas …

Go to article

An Exploratory Study On Museum Visitor Ship Trends In Singapore, Aldy Gunawan, Chentao Liu, Heranshan S/O Subramaniam, Melissa Tan, Ranice Tan, Clarence Tay, Tasaporn. Visawameteekul Mar 2023

An Exploratory Study On Museum Visitor Ship Trends In Singapore, Aldy Gunawan, Chentao Liu, Heranshan S/O Subramaniam, Melissa Tan, Ranice Tan, Clarence Tay, Tasaporn. Visawameteekul

Research Collection School Of Computing and Information Systems

The COVID-19 outbreak has unpredictably disrupted the operations of numerous museums. Museum visitor experience has a physical, personal, and social context, which are not achievable during the pandemic. Despite the depreciation during the Circuit Breaker period, the disruption also presents an opportunity for local museums to develop new strategies of audience engagement to accommodate the altered audience behavior. This exploratory study analyses data from six Singapore-based museums to understand the visitorship patterns across different ages and genders. The impact of COVID-19 is also analysed. Using R-studio and relevant packages, we conducted statistical tests such as hypothesis testing, Chi-square testing and …

Go to article

Heart: Motion-Resilient Heart Rate Monitoring With In-Ear Microphones, Kayla-Jade Butkow, Ting Dang, Andrea Ferlini, Dong Ma, Mascolo Mar 2023

Heart: Motion-Resilient Heart Rate Monitoring With In-Ear Microphones, Kayla-Jade Butkow, Ting Dang, Andrea Ferlini, Dong Ma, Mascolo

Research Collection School Of Computing and Information Systems

With the soaring adoption of in-ear wearables, the research community has started investigating suitable in-ear heart rate (HR) detection systems. HR is a key physiological marker of cardiovascular health and physical fitness. Continuous and reliable HR monitoring with wearable devices has therefore gained increasing attention in recent years. Existing HR detection systems in wearables mainly rely on photoplethysmography (PPG) sensors, however, these are notorious for poor performance in the presence of human motion. In this work, leveraging the occlusion effect that enhances low-frequency bone-conducted sounds in the ear canal, we investigate for the first time in-ear audio-based motion-resilient HR monitoring. …

Go to article

Detecting C++ Compiler Front-End Bugs Via Grammar Mutation And Differential Testing, Haoxin Tu, He Jiang, Zhide Zhou, Yixuan Tang, Zhilei Ren, Lei Qiao, Lingxiao Jiang Mar 2023

Detecting C++ Compiler Front-End Bugs Via Grammar Mutation And Differential Testing, Haoxin Tu, He Jiang, Zhide Zhou, Yixuan Tang, Zhilei Ren, Lei Qiao, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

C++ is a widely used programming language and the C++ front-end is a critical part of a C++ compiler. Although many techniques have been proposed to test compilers, few studies are devoted to detecting bugs in C++ compiler. In this study, we take the first step to detect bugs in C++ compiler front-ends. To do so, two main challenges need to be addressed, namely, the acquisition of test programs that are more likely to trigger bugs in compiler front-ends and the bug identification from complicated compiler outputs. In this article, we propose a novel framework named Ccoft to detect bugs …

Go to article

Green Stormwater Infrastructure: A Critical Review Of The Barriers And Solutions To Widespread Implementation, Bardia Heidari, Sarah Priscilla Randle, Dean Minchillo, Fouad H. Jaber Mar 2023

Green Stormwater Infrastructure: A Critical Review Of The Barriers And Solutions To Widespread Implementation, Bardia Heidari, Sarah Priscilla Randle, Dean Minchillo, Fouad H. Jaber

Research Collection College of Integrative Studies

Rapid urbanization, aging infrastructure, and climate change impacts have put a strain on existing stormwater drainage systems. One commonly acknowledged solution to relieve such stress is Green Stormwater Infrastructure (GSI). Interest in GSI technology has been growing. However, the level of implementation in many areas around the world lags behind the interest level. This study aims to critically review the body of literature from the last decade to determine the main barriers to wide adoption and the offered solutions to overcome them. Based on a review of 92 peer-reviewed journal articles published between 2012 and 2022, we classify barriers and …

Go to article

Climate Denialism Bullshit Is Harmful, Joshua Luczak Mar 2023

Climate Denialism Bullshit Is Harmful, Joshua Luczak

Research Collection College of Integrative Studies

This paper suggests that some climate denialism is bullshit. Those who spread it do not display a proper concern for the truth. This paper also shows that this bullshit is harmful in some significant ways. It undermines the epistemic demands imposed on us by what we care about, by the social roles we occupy, and by morality. It is also harmful because it corrodes epistemic trust.

Go to article

Wearables For In-Situ Monitoring Of Cognitive States: Challenges And Opportunities, Meeralakshmi Radhakrishnan, Thivya Kandappu, Manoj Gulati, Archan Misra Mar 2023

Wearables For In-Situ Monitoring Of Cognitive States: Challenges And Opportunities, Meeralakshmi Radhakrishnan, Thivya Kandappu, Manoj Gulati, Archan Misra

Research Collection School Of Computing and Information Systems

We propose using wrist and ear-based sensing, via multiple novel and complementary modalities, to unobtrusively infer activity-aware, complex cognitive and affective states (such as confusion, boredom, and recall failure) of individuals. While state-of-the-art wearable devices are predominantly used (a) independently, with limited coordination among multiple devices, and (b) to capture macro-level physical activity and physiological state, we seek to expand the ambit of unobtrusive wearable sensing to capture the cognitive states while performing commonplace physical activities. Such states typically manifest via fine-grained, almost unobservable, microscopic head, face, and eye movements. We identify some of these fine-grained physical markers that serve …

Go to article

Exploring And Repairing Gender Fairness Violations In Word Embedding-Based Sentiment Analysis Model Through Adversarial Patches, Lin Sze Khoo, Jia Qi Bay, Ming Lee Kimberly Yap, Mei Kuan Lim, Chun Yong Chong, Zhou Yang, David Lo Mar 2023

Exploring And Repairing Gender Fairness Violations In Word Embedding-Based Sentiment Analysis Model Through Adversarial Patches, Lin Sze Khoo, Jia Qi Bay, Ming Lee Kimberly Yap, Mei Kuan Lim, Chun Yong Chong, Zhou Yang, David Lo

Research Collection School Of Computing and Information Systems

With the advancement of sentiment analysis (SA) models and their incorporation into our daily lives, fairness testing on these models is crucial, since unfair decisions can cause discrimination to a large population. Nevertheless, some challenges in fairness testing include the unknown oracle, the difficulty in generating suitable test inputs, and the lack of a reliable way of fixing the issues. To fill in these gaps, BiasRV, a tool based on metamorphic testing (MT), was introduced and succeeded in uncovering fairness issues in a transformer-based model. However, the extent of unfairness in other SA models has not been thoroughly investigated. Our …

Go to article

Effective Graph Kernels For Evolving Functional Brain Networks, Xinlei Wang, Jinyi Chen, Bing Tian Dai, Junchang Xin, Yu Gu, Ge Yu Mar 2023

Effective Graph Kernels For Evolving Functional Brain Networks, Xinlei Wang, Jinyi Chen, Bing Tian Dai, Junchang Xin, Yu Gu, Ge Yu

Research Collection School Of Computing and Information Systems

The graph kernel of the functional brain network is an effective method in the field of neuropsychiatric disease diagnosis like Alzheimer's Disease (AD). The traditional static brain networks cannot reflect dynamic changes of brain activities, but evolving brain networks, which are a series of brain networks over time, are able to seize such dynamic changes. As far as we know, the graph kernel method is effective for calculating the differences among networks. Therefore, it has a great potential to understand the dynamic changes of evolving brain networks, which are a series of chronological differences. However, if the conventional graph kernel …

Go to article

Multi-Modal Api Recommendation, Ivana Clairine Irsan, Ting Zhang, Ferdian Thung, Kisub Kim, David Lo Mar 2023

Multi-Modal Api Recommendation, Ivana Clairine Irsan, Ting Zhang, Ferdian Thung, Kisub Kim, David Lo

Research Collection School Of Computing and Information Systems

Too many options can be a problem, which is the case for Application Programming Interfaces (APIs). As there are many such APIs, with many more being introduced periodically, it raises the problem of choosing which API to be recommended. Furthermore, numerous APIs are commonly used together with other complementary third-party APIs. It can be challenging for developers to understand how to use each API and to remember all the complementary APIs for the API they want to use. Therefore, an accurate API recommendation approach can improve developers' efficiency in implementing certain functionality. Several approaches have been developed to automatically recommend …

Go to article

Prudex-Compass: Towards Systematic Evaluation Of Reinforcement Learning In Financial Markets, Shuo Sun, Molei Qin, Xinrun Wang, Bo An Mar 2023

Prudex-Compass: Towards Systematic Evaluation Of Reinforcement Learning In Financial Markets, Shuo Sun, Molei Qin, Xinrun Wang, Bo An

Research Collection School Of Computing and Information Systems

The financial markets, which involve more than $90 trillion market capitals, attract the attention of innumerable investors around the world. Recently, reinforcement learning in financial markets (FinRL) has emerged as a promising direction to train agents for making profitable investment decisions. However, the evaluation of most FinRL methods only focuses on profit-related measures and ignores many critical axes, which are far from satisfactory for financial practitioners to deploy these methods into real-world financial markets. Therefore, we introduce PRUDEX-Compass, which has 6 axes, i.e., Profitability, Risk-control, Universality, Diversity, rEliability, and eXplainability, with a total of 17 measures for a systematic evaluation. …

Go to article

Spatio-Temporal Heterogeneity In The International Trade Resilience During Covid-19, Wei Luo, Lingfeng He, Zihui Yang, Shirui Zhang, Yong Wang, Dianbo Liu, Sheng Hu, Li He, Jizhe Xia, Min Chen Mar 2023

Spatio-Temporal Heterogeneity In The International Trade Resilience During Covid-19, Wei Luo, Lingfeng He, Zihui Yang, Shirui Zhang, Yong Wang, Dianbo Liu, Sheng Hu, Li He, Jizhe Xia, Min Chen

Research Collection School Of Computing and Information Systems

The COVID-19 pandemic and subsequent lockdowns have created immeasurable health and economic crises, leading to unprecedented disruptions to world trade. The COVID-19 pandemic shows diverse impacts on different economies that suffer and recover at different rates and degrees. This research aims to evaluate the spatio-temporal heterogeneity of international trade network vulnerabilities in the current crisis to understand the global production resilience and prepare for the future crisis. We applied a series of complex network analysis approaches to the monthly international trade networks at the world, regional, and country scales for the pre- and post- COVID-19 outbreak period. The spatio-temporal patterns …

Go to article

Assessment Of Gnss Radio Occultation Data Assimilation In Numerical Weather Prediction Wind Forecasts, Gregory A. Egger Mar 2023

Assessment Of Gnss Radio Occultation Data Assimilation In Numerical Weather Prediction Wind Forecasts, Gregory A. Egger

Theses and Dissertations

A crucial component of weather forecasting in numerical weather prediction (NWP) is the analysis of the initial state of the atmosphere. Inaccurate analysis of the environment can lead to amplifying errors in the forecast which can cause devastating effects to the population and its resources. In this study, a weather model simulation was performed over the Pacific Northwest to evaluate wind speed forecast performance by assimilating Global Navigation Satellite System (GNSS) radio occultation (RO) data. Two separate events were examined: 24 - 26 October 2021 during which a strong extratropical cyclone struck the area, and 7 - 9 November 2021 …

Go to article

Classification And Analysis Of Twitter Bot And Troll Accounts, Callan P. Mccormick Mar 2023

Classification And Analysis Of Twitter Bot And Troll Accounts, Callan P. Mccormick

Theses and Dissertations

This research trains, tests, and analyzes bot and troll classification models using publicly available, open source datasets. Specifically, it applies decision tree, random forest, feed forward neural networks, and long-short term memory neural networks with hyperparameters tuned via designed experiment to five labeled bot datasets created between 2011 and 2020 and one dataset labeling state-sponsored disinformation accounts or trolls. The first three models utilize account profile features, while the last model applies natural language processing techniques, specifically GloVe embedding, to analyze a user’s Tweet history. Results indicate that the random forest model outperforms the other three models with an average …

Go to article

Distributed Reconnaissance Deception Using Software-Defined Networking In A Dynamic Network Environment, Richard Hunter Feustel Mar 2023

Distributed Reconnaissance Deception Using Software-Defined Networking In A Dynamic Network Environment, Richard Hunter Feustel

Theses and Dissertations

This research outlines the design and implementation of a DRDS, which is a RDS distributed across multiple controllers that is capable of deploying reconnaissance deception across multiple switches to mitigate network enumeration by a compromised host. This research outlines the design and development of the DRDS as well as tests its functional abilities and routing performance when compared to a two other network routing solutions: a legacy network solution and centralized ONOS controller scheme deploying layer 2 forwarding. The functional tests proved the system can properly route traffic across 100% of the tested scenarios carrying traffic that includes IP, ARP, …

Go to article

Intel Total Memory Encryption: Functional Verification And Performance Analysis, Tallas Tian Sheng Goo Mar 2023

Intel Total Memory Encryption: Functional Verification And Performance Analysis, Tallas Tian Sheng Goo

Theses and Dissertations

While more attention is generally focused on software security, computer hardware security remains an important effort. Should an attacker gain direct physical access, computers with little to no hardware security can quickly be compromised via a manner of methods. One such attacker method is to steal information directly from the active memory of a locked, powered-on computer. To counter this attack, a hardware security method was developed called memory encryption. Memory encryption, as the name suggests, protects against adversary methods like cold boot attacks by encrypting all of memory. This research evaluates the efficacy and performance specifically of Intel TME. …

Go to article

Characterizing Location-Based Electromagnetic Leakage Of Computing Devices Using Convolutional Neural Networks To Increase The Effectiveness Of Side-Channel Analysis Attacks, Ian C. Heffron Mar 2023

Characterizing Location-Based Electromagnetic Leakage Of Computing Devices Using Convolutional Neural Networks To Increase The Effectiveness Of Side-Channel Analysis Attacks, Ian C. Heffron

Theses and Dissertations

SCA attacks aim to recover some sort of secret information, often in the form of a cipher key, from a target device. Some of these attacks focus on either power-based leakage, or EM-based leakage. Neural networks have recently gained in popularity as tools in SCA attacks. Near-field EM probes with high-spatial resolution enable attackers to isolate physical locations above a processor. This enables attackers to exploit the spatial dependencies of algorithms running on said processor. These spatial dependencies result in different physical locations above a chip emanating different signal strengths. The strengths of different locations can be mapped using the …

Go to article

Ensemble Aggregation In A Multi-Perspective Environment, Jonathan P. Nash Mar 2023

Ensemble Aggregation In A Multi-Perspective Environment, Jonathan P. Nash

Theses and Dissertations

Research towards improving the performance of artificial intelligence networks has found that larger and more complex networks tends to yield better results, and continuous hardware upgrades enables the development of larger, more complicated, and better performing neural networks. However, many devices that are widely available and more practical to everyday use, such as drones or smartphones, are unable to use the state-of-the-art neural networks because they simply do not have the processing capabilities to run them in addition to their normal function. It is possible to overcome this lower performance by using a variety of these smaller neural networks as …

Go to article

First Prev Next Last