Scalable Distributional Robustness In A Class Of Non Convex Optimization With Guarantees,
2022
Singapore Management University
Scalable Distributional Robustness In A Class Of Non Convex Optimization With Guarantees, Avinandan Bose, Arunesh Sinha, Tien Mai
Research Collection School Of Computing and Information Systems
Distributionally robust optimization (DRO) has shown lot of promise in providing robustness in learning as well as sample based optimization problems. We endeavor to provide DRO solutions for a class of sum of fractionals, non-convex optimization which is used for decision making in prominent areas such as facility location and security games. In contrast to previous work, we find it more tractable to optimize the equivalent variance regularized form of DRO rather than the minimax form. We transform the variance regularized form to a mixed-integer second order cone program (MISOCP), which, while guaranteeing near global optimality, does not scale enough …
Detecting Selfish Mining Attacks Against A Blockchain Using Machine Learing,
2022
University of South Alabama
Detecting Selfish Mining Attacks Against A Blockchain Using Machine Learing, Matthew A. Peterson
Graduate Theses and Dissertations (2019 - present)
Selfish mining is an attack against a blockchain where miners hide newly discovered blocks instead of publishing them to the rest of the network. Selfish mining has been a potential issue for blockchains since it was first discovered by Eyal and Sirer. It can be used by malicious miners to earn a disproportionate share of the mining rewards or in conjunction with other attacks to steal money from network users. Several of these attacks were launched in 2018, 2019, and 2020 with the attackers stealing as much as $18 Million. Developers made several different attempts to fix this issue, but …
Unoapi: Balancing Performance, Portability, And Productivity (P3) In Hpc Education,
2022
Loyola University Chicago
Unoapi: Balancing Performance, Portability, And Productivity (P3) In Hpc Education, Konstantin Laufer, George K. Thiruvathukal
Computer Science: Faculty Publications and Other Works
oneAPI is a major initiative by Intel aimed at making it easier to program heterogeneous architectures used in high-performance computing using a unified application programming interface (API). While raising the abstraction level via a unified API represents a promising step for the current generation of students and practitioners to embrace high- performance computing, we argue that a curriculum of well- developed software engineering methods and well-crafted exem- plars will be necessary to ensure interest by this audience and those who teach them. We aim to bridge the gap by developing a curriculum—codenamed UnoAPI—that takes a more holistic approach by looking …
Virtual Sensor Middleware: Managing Iot Data For The Fog-Cloud Platform,
2022
Western University
Virtual Sensor Middleware: Managing Iot Data For The Fog-Cloud Platform, Fadi Almahamid, Hanan Lutfiyya, Katarina Grolinger
Electrical and Computer Engineering Publications
This paper introduces the Virtual Sensor Middleware (VSM), which facilitates distributed sensor data processing on multiple fog nodes. VSM uses a Virtual Sensor as the core component of the middleware. The virtual sensor concept is redesigned to support functionality beyond sensor/device virtualization, such as deploying a set of virtual sensors to represent an IoT application and distributed sensor data processing across multiple fog nodes. Furthermore, the virtual sensor deals with the heterogeneous nature of IoT devices and the various communication protocols using different adapters to communicate with the IoT devices and the underlying protocol. VSM uses the publish-subscribe design pattern …
Algorithm-Based Fault Tolerance At Scale,
2022
University of Alabama in Huntsville
Algorithm-Based Fault Tolerance At Scale, Hayden Estes
Summer Community of Scholars Posters (RCEU and HCR Combined Programs)
No abstract provided.
Analyzing Microarchitectural Residue In Various Privilege Strata To Identify Computing Tasks,
2022
Air Force Institute of Technology
Analyzing Microarchitectural Residue In Various Privilege Strata To Identify Computing Tasks, Tor J. Langehaug
Theses and Dissertations
Modern multi-tasking computer systems run numerous applications simultaneously. These applications must share hardware resources including the Central Processing Unit (CPU) and memory while maximizing each application’s performance. Tasks executing in this shared environment leave residue which should not reveal information. This dissertation applies machine learning and statistical analysis to evaluate task residue as footprints which can be correlated to identify tasks. The concept of privilege strata, drawn from an analogy with physical geology, organizes the investigation into the User, Operating System, and Hardware privilege strata. In the User Stratum, an adversary perspective is taken to build an interrogator program that …
Gpgpu Microbenchmarking For Irregular Application Optimization,
2022
Mississippi State University
Gpgpu Microbenchmarking For Irregular Application Optimization, Dalton R. Winans-Pruitt
Theses and Dissertations
Irregular applications, such as unstructured mesh operations, do not easily map onto the typical GPU programming paradigms endorsed by GPU manufacturers, which mostly focus on maximizing concurrency for latency hiding. In this work, we show how alternative techniques focused on latency amortization can be used to control overall latency while requiring less concurrency. We used a custom-built microbenchmarking framework to test several GPU kernels and show how the GPU behaves under relevant workloads. We demonstrate that coalescing is not required for efficacious performance; an uncoalesced access pattern can achieve high bandwidth - even over 80% of the theoretical global memory …
Holistic Performance Analysis And Optimization Of Unified Virtual Memory,
2022
Clemson University
Holistic Performance Analysis And Optimization Of Unified Virtual Memory, Tyler Allen
All Dissertations
The programming difficulty of creating GPU-accelerated high performance computing (HPC) codes has been greatly reduced by the advent of Unified Memory technologies that abstract the management of physical memory away from the developer. However, these systems incur substantial overhead that paradoxically grows for codes where these technologies are most useful. While these technologies are increasingly adopted for use in modern HPC frameworks and applications, the performance cost reduces the efficiency of these systems and turns away some developers from adoption entirely. These systems are naturally difficult to optimize due to the large number of interconnected hardware and software components that …
Parallel Algorithms For Scalable Graph Mining: Applications On Big Data And Machine Learning,
2022
University of New Orleans
Parallel Algorithms For Scalable Graph Mining: Applications On Big Data And Machine Learning, Naw Safrin Sattar
University of New Orleans Theses and Dissertations
Parallel computing plays a crucial role in processing large-scale graph data. Complex network analysis is an exciting area of research for many applications in different scientific domains e.g., sociology, biology, online media, recommendation systems and many more. Graph mining is an area of interest with diverse problems from different domains of our daily life. Due to the advancement of data and computing technologies, graph data is growing at an enormous rate, for example, the number of links in social networks is growing every millisecond. Machine/Deep learning plays a significant role for technological accomplishments to work with big data in modern …
Aligning The Transit Industry And Their Vendors In The Face Of Increasing Cyber Risk: Recommendations For Identifying And Addressing Cybersecurity Challenges,
2022
Mineta Transportation Institute
Aligning The Transit Industry And Their Vendors In The Face Of Increasing Cyber Risk: Recommendations For Identifying And Addressing Cybersecurity Challenges, Scott Belcher, Terri Belcher, Kathryn Seckman, Brandon Thomas, Homayun Yaqub
Mineta Transportation Institute
Public transit agencies in the United States depend on external vendors to help deliver and maintain many essential services and to provide critical technologies, from ticket purchases to scheduling to email management. While the integration of new, advanced technologies into the public transit industry brings important advancements to U.S. critical transportation infrastructure, the application of digital technologies also brings with it a new assortment of digital risks. Transit agencies of all sizes are finding themselves subject to cyber incidents—most notably ransomware attacks—like those experienced by larger, more prominent companies and critical infrastructure providers. The findings in this report focus on …
Neural Network Based Scene Text Recognition [Us Patent Us 2022/0237403 A1],
2022
Singapore Management University
Neural Network Based Scene Text Recognition [Us Patent Us 2022/0237403 A1], Pan Zhou, Peng Tang, Ran Xu, Steven Chu Hong Hoi
Research Collection School Of Computing and Information Systems
A system uses a neural network based model to perform scene text recognition. The system achieves high accuracy of prediction of text from scenes based on a neural network architecture that uses double attention mechanism. The neural network based model includes a convolutional neural network component that outputs a set of visual features and an attention extractor neural network component that determines attention scores based on the visual features. The visual features and the attention scores are combined to generate mixed features that are provided as input to a character recognizer component that determines a second attention score and recognizes …
A Recommendation System Approach To Tune A Qubo Solver,
2022
Singapore Management University
A Recommendation System Approach To Tune A Qubo Solver, Siong Thye Goh, Jianyuan Bo, Matthieu Parizy, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
There are two major challenges to solving constrained optimization problems using a QuadraticUnconstrained Binary Optimization or QUBO solver (QS). First, we need to tune both the underlyingproblem parameters and the algorithm parameters. Second, the solution returned from a QSmight not be feasible. While it is common to use automated tuners such as SMAC and Hyperopt totune the algorithm parameters, the initial search ranges input for the auto tuner affect the performanceof the QS. In this paper, we propose a framework that resembles the Algorithm Selection(AS) framework to tune algorithm parameters for an annealing-based QS. To cope with constraints,we focus on …
Using Graph Theoretical Methods And Traceroute To Visually Represent Hidden Networks,
2022
University of Nebraska at Omaha
Using Graph Theoretical Methods And Traceroute To Visually Represent Hidden Networks, Jordan M. Sahs
UNO Student Research and Creative Activity Fair
Within the scope of a Wide Area Network (WAN), a large geographical communication network in which a collection of networking devices communicate data to each other, an example being the spanning communication network, known as the Internet, around continents. Within WANs exists a collection of Routers that transfer network packets to other devices. An issue pertinent to WANs is their immeasurable size and density, as we are not sure of the amount, or the scope, of all the devices that exists within the network. By tracing the routes and transits of data that traverses within the WAN, we can identify …
Torsh: Obfuscating Consumer Internet-Of-Things Traffic With A Collaborative Smart-Home Router Network,
2022
Dartmouth College
Torsh: Obfuscating Consumer Internet-Of-Things Traffic With A Collaborative Smart-Home Router Network, Adam Vandenbussche
Dartmouth College Undergraduate Theses
When consumers install Internet-connected "smart devices" in their homes, metadata arising from the communications between these devices and their cloud-based service providers enables adversaries privy to this traffic to profile users, even when adequate encryption is used. Internet service providers (ISPs) are one potential adversary privy to users’ incom- ing and outgoing Internet traffic and either currently use this insight to assemble and sell consumer advertising profiles or may in the future do so. With existing defenses against such profiling falling short of meeting user preferences and abilities, there is a need for a novel solution that empowers consumers to …
Developing A Miniature Smart Boat For Marine Research,
2022
California Polytechnic State University, San Luis Obispo
Developing A Miniature Smart Boat For Marine Research, Michael Isaac Eirinberg
Computer Engineering
This project examines the development of a smart boat which could serve as a possible marine research apparatus. The smart boat consists of a miniature vessel containing a low-cost microcontroller to live stream a camera feed, GPS telemetry, and compass data through its own WiFi access point. The smart boat also has the potential for autonomous navigation. My project captivated the interest of several members of California Polytechnic State University, San Luis Obispo’s (Cal Poly SLO) Marine Science Department faculty, who proposed a variety of fascinating and valuable smart boat applications.
Out-Of-Core Gpu Path Tracing On Large Instanced Scenes Via Geometry Streaming,
2022
California Polytechnic State University, San Luis Obispo
Out-Of-Core Gpu Path Tracing On Large Instanced Scenes Via Geometry Streaming, Jeremy Berchtold
Master's Theses
We present a technique for out-of-core GPU path tracing of arbitrarily large scenes that is compatible with hardware-accelerated ray-tracing. Our technique improves upon previous works by subdividing the scene spatially into streamable chunks that are loaded using a priority system that maximizes ray throughput and minimizes GPU memory usage. This allows for arbitrarily large scaling of scene complexity. Our system required under 19 minutes to render a solid color version of Disney's Moana Island scene (39.3 million instances, 261.1 million unique quads, and 82.4 billion instanced quads at a resolution of 1024x429 and 1024spp on an RTX 5000 (24GB memory …
Information Provenance For Mobile Health Data,
2022
Dartmouth College
Information Provenance For Mobile Health Data, Taylor A. Hardin
Dartmouth College Ph.D Dissertations
Mobile health (mHealth) apps and devices are increasingly popular for health research, clinical treatment and personal wellness, as they offer the ability to continuously monitor aspects of individuals' health as they go about their everyday activities. Many believe that combining the data produced by these mHealth apps and devices may give healthcare-related service providers and researchers a more holistic view of an individual's health, increase the quality of service, and reduce operating costs. For such mHealth data to be considered useful though, data consumers need to be assured that the authenticity and the integrity of the data has remained intact---especially …
Privacy Assessment Breakthrough: A Design Science Approach To Creating A Unified Methodology,
2022
Dakota State University
Privacy Assessment Breakthrough: A Design Science Approach To Creating A Unified Methodology, Lisa Mckee
Masters Theses & Doctoral Dissertations
Recent changes have increased the need for and awareness of privacy assessments. Organizations focus primarily on Privacy Impact Assessments (PIA) and Data Protection Impact Assessments (DPIA) but rarely take a comprehensive approach to assessments or integrate the results into a privacy risk program. There are numerous industry standards and regulations for privacy assessments, but the industry lacks a simple unified methodology with steps to perform privacy assessments. The objectives of this research project are to create a new privacy assessment methodology model using the design science methodology, update industry standards and present training for conducting privacy assessments that can be …
Using A Bert-Based Ensemble Network For Abusive Language Detection,
2022
University of Arkansas, Fayetteville
Using A Bert-Based Ensemble Network For Abusive Language Detection, Noah Ballinger
Computer Science and Computer Engineering Undergraduate Honors Theses
Over the past two decades, online discussion has skyrocketed in scope and scale. However, so has the amount of toxicity and offensive posts on social media and other discussion sites. Despite this rise in prevalence, the ability to automatically moderate online discussion platforms has seen minimal development. Recently, though, as the capabilities of artificial intelligence (AI) continue to improve, the potential of AI-based detection of harmful internet content has become a real possibility. In the past couple years, there has been a surge in performance on tasks in the field of natural language processing, mainly due to the development of …
Comparative Study Of Snort 3 And Suricata Intrusion Detection Systems,
2022
University of Arkansas, Fayetteville
Comparative Study Of Snort 3 And Suricata Intrusion Detection Systems, Cole Hoover
Computer Science and Computer Engineering Undergraduate Honors Theses
Network Intrusion Detection Systems (NIDS) are one layer of defense that can be used to protect a network from cyber-attacks. They monitor a network for any malicious activity and send alerts if suspicious traffic is detected. Two of the most common open-source NIDS are Snort and Suricata. Snort was first released in 1999 and became the industry standard. The one major drawback of Snort has been its single-threaded architecture. Because of this, Suricata was released in 2009 and uses a multithreaded architecture. Snort released Snort 3 last year with major improvements from earlier versions, including implementing a new multithreaded architecture …
