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

OS and Networks Commons

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

1,596 Full-Text Articles 1,451 Authors 267,473 Downloads 85 Institutions

All Articles in OS and Networks

Faceted Search

1,596 full-text articles. Page 2 of 53.

Dynamic 3d Network Data Visualization, Brok Stafford 2018 University of Arkansas, Fayetteville

Dynamic 3d Network Data Visualization, Brok Stafford

Computer Science and Computer Engineering Undergraduate Honors Theses

Monitoring network traffic has always been an arduous and tedious task because of the complexity and sheer volume of network data that is being consistently generated. In addition, network growth and new technologies are rapidly increasing these levels of complexity and volume. An effective technique in understanding and managing a large dataset, such as network traffic, is data visualization. There are several tools that attempt to turn network traffic into visual stimuli. Many of these do so in 2D space and those that are 3D lack the ability to display network patterns effectively. Existing 3D network visualization tools lack user ...


Improving The Efficacy Of Context-Aware Applications, Jon C. Hammer 2018 University of Arkansas, Fayetteville

Improving The Efficacy Of Context-Aware Applications, Jon C. Hammer

Theses and Dissertations

In this dissertation, we explore methods for enhancing the context-awareness capabilities of modern computers, including mobile devices, tablets, wearables, and traditional computers. Advancements include proposed methods for fusing information from multiple logical sensors, localizing nearby objects using depth sensors, and building models to better understand the content of 2D images.

First, we propose a system called Unagi, designed to incorporate multiple logical sensors into a single framework that allows context-aware application developers to easily test new ideas and create novel experiences. Unagi is responsible for collecting data, extracting features, and building personalized models for each individual user. We demonstrate the ...


Breathing-Based Authentication On Resource-Constrained Iot Devices Using Recurrent Neural Networks, Jagmohan CHAUHAN, Suranga SENEVIRATNE, Yining HU, Archan MISRA, Aruna SENEVIRATNE, Youngki LEE 2018 Singapore Management University

Breathing-Based Authentication On Resource-Constrained Iot Devices Using Recurrent Neural Networks, Jagmohan Chauhan, Suranga Seneviratne, Yining Hu, Archan Misra, Aruna Seneviratne, Youngki Lee

Research Collection School Of Information Systems

Recurrent neural networks (RNNs) have shown promising resultsin audio and speech-processing applications. The increasingpopularity of Internet of Things (IoT) devices makes a strongcase for implementing RNN-based inferences for applicationssuch as acoustics-based authentication and voice commandsfor smart homes. However, the feasibility and performance ofthese inferences on resource-constrained devices remain largelyunexplored. The authors compare traditional machine-learningmodels with deep-learning RNN models for an end-to-endauthentication system based on breathing acoustics.


Bayesian Network Modeling And Inference Of Gwas Catalog, Qiuping Pan 2018 University of Arkansas, Fayetteville

Bayesian Network Modeling And Inference Of Gwas Catalog, Qiuping Pan

Theses and Dissertations

Genome-wide association studies (GWASs) have received an increasing attention to understand genotype-phenotype relationships. The Bayesian network has been proposed as a powerful tool for modeling single-nucleotide polymorphism (SNP)-trait associations due to its advantage in addressing the high computational complex and high dimensional problems. Most current works learn the interactions among genotypes and phenotypes from the raw genotype data. However, due to the privacy issue, genotype information is sensitive and should be handled by complying with specific restrictions. In this work, we aim to build Bayesian networks from publicly released GWAS statistics to explicitly reveal the conditional dependency between SNPs ...


Malware For Macintosh, Nathan C. Shinabarger, Josiah E. Bills, Richard W. Lively, Noah S. Shinabarger 2018 Cedarville University

Malware For Macintosh, Nathan C. Shinabarger, Josiah E. Bills, Richard W. Lively, Noah S. Shinabarger

The Research and Scholarship Symposium

Technology is a cornerstone of modern society. Unfortunately, it seems that every new piece of technology is accompanied by five computer-security breaches elsewhere. Most people associate hacks with Windows computers. This is a problem because Apple computers, and other non-Windows systems, are also extremely vulnerable to attacks and risk being compromised. Dolos is a piece of malware we developed intended to exploit the macOS Sierra operating system. It provides a framework for running exploits and comes built in with certain control and data exfiltration capabilities. Dolos also helps destroy the misconception of "the impenetrable Macintosh computer" by showing that Apple ...


Next Generation Tcp/Ip Side Channels, Xu Zhang 2018 University of New Mexico

Next Generation Tcp/Ip Side Channels, Xu Zhang

Computer Science ETDs

Side channel techniques have been developed in recent years to fulfill various tasks in modern computer network measurements. However, due to their nature, these techniques are typically limited in terms of both fidelity and their ability to be used on the real Internet without raising ethical concerns because of packet rates. I propose the next generation of TCP/IP side channel techniques that exploit information flow in modern systems’ network stacks to overcome weaknesses in previous techniques. The proposed work is novel, non-intrusive, and can carry out measurements with high fidelity. I achieved this by deeply understanding the behaviors of ...


Virtualization In Wireless Sensor Networks: Fault Tolerant Embedding For Internet Of Things, Omprakash KAIWARTYA, Abdul Hanan ABDULLAH, Yue CAO, Jaime LLORET, Sushil KUMAR, Rajiv Ratn SHAH, Mukesh PRASAD, Shiv PRAKASH 2018 Singapore Management University

Virtualization In Wireless Sensor Networks: Fault Tolerant Embedding For Internet Of Things, Omprakash Kaiwartya, Abdul Hanan Abdullah, Yue Cao, Jaime Lloret, Sushil Kumar, Rajiv Ratn Shah, Mukesh Prasad, Shiv Prakash

Research Collection School Of Information Systems

Recently, virtualization in wireless sensor networks (WSNs) has witnessed significant attention due to the growing service domain for IoT. Related literature on virtualization in WSNs explored resource optimization without considering communication failure in WSNs environments. The failure of a communication link in WSNs impacts many virtual networks running IoT services. In this context, this paper proposes a framework for optimizing fault tolerance in virtualization in WSNs, focusing on heterogeneous networks for service-oriented IoT applications. An optimization problem is formulated considering fault tolerance and communication delay as two conflicting objectives. An adapted non-dominated sorting based genetic algorithm (A-NSGA) is developed to ...


Automated Man-In-The-Middle Attack Against Wi‑Fi Networks, Martin Vondráček, Jan Pluskal, Ondřej Ryšavý 2018 Brno University of Technology, Brno, Czech Republic

Automated Man-In-The-Middle Attack Against Wi‑Fi Networks, Martin Vondráček, Jan Pluskal, Ondřej Ryšavý

Journal of Digital Forensics, Security and Law

Currently used wireless communication technologies suffer security weaknesses that can be exploited allowing to eavesdrop or to spoof network communication. In this paper, we present a practical tool that can automate the attack on wireless security. The developed package called wifimitm provides functionality for the automation of MitM attacks in the wireless environment. The package combines several existing tools and attack strategies to bypass the wireless security mechanisms, such as WEP, WPA, and WPS. The presented tool can be integrated into a solution for automated penetration testing. Also, a popularization of the fact that such attacks can be easily automated ...


Traffic-Aware Deployment Of Interdependent Nfv Middleboxes In Software-Defined Networks, Wenrui Ma 2018 Florida International University

Traffic-Aware Deployment Of Interdependent Nfv Middleboxes In Software-Defined Networks, Wenrui Ma

FIU Electronic Theses and Dissertations

Middleboxes, such as firewalls, Network Address Translators (NATs), Wide Area Network (WAN) optimizers, or Deep Packet Inspector (DPIs), are widely deployed in modern networks to improve network security and performance. Traditional middleboxes are typically hardware based, which are expensive and closed systems with little extensibility. Furthermore, they are developed by different vendors and deployed as standalone devices with little scalability. As the development of networks in scale, the limitations of traditional middleboxes bring great challenges in middlebox deployments.

Network Function Virtualization (NFV) technology provides a promising alternative, which enables flexible deployment of middleboxes, as virtual machines (VMs) running on standard ...


Pattern-Of-Life Modeling Using Data Leakage In Smart Homes, Steven M. Beyer 2018 Air Force Institute of Technology

Pattern-Of-Life Modeling Using Data Leakage In Smart Homes, Steven M. Beyer

Theses and Dissertations

This work investigates data leakage in smart homes by providing a Smart Home Automation Architecture (SHAA) and a device classifier and pattern-of-life analysis tool, CITIoT (Classify, Identify, and Track Internet of things). CITIoT was able to capture traffic from SHAA and classify 17 of 18 devices, identify 95% of the events that occurred, and track when users were home or away with near 100% accuracy. Additionally, a mitigation tool, MIoTL (Mitigation of IoT Leakage) is provided to defend against smart home data leakage. With mitigation, CITIoT was unable to identify motion and camera devices and was inundated with an average ...


Scaling Human Activity Recognition Via Deep Learning-Based Domain Adaptation, Md Abdullah Hafiz KHAN, Nirmalya ROY, Archan MISRA 2018 Singapore Management University

Scaling Human Activity Recognition Via Deep Learning-Based Domain Adaptation, Md Abdullah Hafiz Khan, Nirmalya Roy, Archan Misra

Research Collection School Of Information Systems

We investigate the problem of making human activityrecognition (AR) scalable–i.e., allowing AR classifiers trainedin one context to be readily adapted to a different contextualdomain. This is important because AR technologies can achievehigh accuracy if the classifiers are trained for a specific individualor device, but show significant degradation when the sameclassifier is applied context–e.g., to a different device located ata different on-body position. To allow such adaptation withoutrequiring the onerous step of collecting large volumes of labeledtraining data in the target domain, we proposed a transductivetransfer learning model that is specifically tuned to the propertiesof convolutional neural ...


Obfuscation At-Source: Privacy In Context-Aware Mobile Crowd-Sourcing, Thivya KANDAPPU, Archan MISRA, Shih Fen CHENG, Randy TANDRIANSYAH, Hoong Chuin LAU 2018 Singapore Management University

Obfuscation At-Source: Privacy In Context-Aware Mobile Crowd-Sourcing, Thivya Kandappu, Archan Misra, Shih Fen Cheng, Randy Tandriansyah, Hoong Chuin Lau

Research Collection School Of Information Systems

By effectively reaching out to and engaging larger population of mobile users, mobile crowd-sourcing has become a strategy to perform large amount of urban tasks. The recent empirical studies have shown that compared to the pull-based approach, which expects the users to browse through the list of tasks to perform, the push-based approach that actively recommends tasks can greatly improve the overall system performance. As the efficiency of the push-based approach is achieved by incorporating worker's mobility traces, privacy is naturally a concern. In this paper, we propose a novel, 2-stage and user-controlled obfuscation technique that provides a trade ...


Automatic Scaling Of Cloud Applications Via Transparently Elasticizing Virtual Memory, Ehab N. Ababneh 2018 University of Colorado at Boulder

Automatic Scaling Of Cloud Applications Via Transparently Elasticizing Virtual Memory, Ehab N. Ababneh

Computer Science Graduate Theses & Dissertations

This dissertation addresses the topic of how to achieve elasticity of an operating system so that networked resources in the form of remote memory and computation can be scaled up, down and out to meet the dynamic workloads of today’s cloud applications. This dissertation shows that it is feasible to modify the Linux operating system to achieve transparent elasticity by implementing four key primitives: stretching of a process’ virtual address space across the physical memory of networked nodes; fine-grained jumping of process execution across the set of networked nodes participating in the stretched address space; pushing of memory pages ...


Back Matter, ADFSL 2018 Embry-Riddle Aeronautical University

Back Matter, Adfsl

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.


Front Matter, ADFSL 2018 Embry-Riddle Aeronautical University

Front Matter, Adfsl

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.


Contents, ADFSL 2018 Embry-Riddle Aeronautical University

Contents, Adfsl

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.


Randomized Routing On Fat-Trees, Ronald I. Greenberg, Charles E. Leiserson 2018 Loyola University Chicago

Randomized Routing On Fat-Trees, Ronald I. Greenberg, Charles E. Leiserson

Ronald Greenberg

Fat-trees are a class of routing networks for hardware-efficient parallel computation. This paper presents a randomized algorithm for routing messages on a fat-tree. The quality of the algorithm is measured in terms of the load factor of a set of messages to be routed, which is a lower bound on the time required to deliver the messages. We show that if a set of messages has load factor lambda on a fat-tree with n processors, the number of delivery cycles (routing attempts) that the algorithm requires is O(lambda + lg n lg lg n) with probability 1-O(1/n). The ...


Randomized Routing On Fat-Trees, Ronald I. Greenberg 2018 Selected Works

Randomized Routing On Fat-Trees, Ronald I. Greenberg

Ronald Greenberg

Fat-trees are a class of routing networks for hardware-efficient parallel computation. This paper presents a randomized algorithm for routing messages on a fat-tree. The quality of the algorithm is measured in terms of the load factor of a set of messages to be routed, which is a lower bound on the time required to deliver the messages. We show that if a set of messages has load factor lambda on a fat-tree with n processors, the number of delivery cycles (routing attempts) that the algorithm requires is O(lambda+lgnlglgn) with probability 1-O(1/n). The ...


On The Area Of Hypercube Layouts, Ronald I. Greenberg, Lee Guan 2018 Selected Works

On The Area Of Hypercube Layouts, Ronald I. Greenberg, Lee Guan

Ronald Greenberg

This paper precisely analyzes the wire density and required area in standard styles for the hypercube. It shows that the most natural, regular layout of a hypercube of N^2 nodes in the plane, in a NxN grid arrangement, uses floor(2N/3)+1 horizontal wiring tracks for each row of nodes. (In the process, we see that the number of tracks per row can be reduced by 1 with a less regular design, as can also be seen from an independent argument of Bezrukov et al.) This paper also gives a simple formula for the wire density at any ...


Efficient Interconnection Schemes For Vlsi And Parallel Computation, Ronald I. Greenberg 2018 Loyola University Chicago

Efficient Interconnection Schemes For Vlsi And Parallel Computation, Ronald I. Greenberg

Ronald Greenberg

This thesis is primarily concerned with two problems of interconnecting components in VLSI technologies. In the first case, the goal is to construct efficient interconnection networks for general-purpose parallel computers. The second problem is a more specialized problem in the design of VLSI chips, namely multilayer channel routing. In addition, a final part of this thesis provides lower bounds on the area required for VLSI implementations of finite-state machines. This thesis shows that networks based on Leiserson's fat-tree architecture are nearly as good as any network built in a comparable amount of physical space. It shows that these "universal ...


Digital Commons powered by bepress