Physical Sciences and Mathematics Commons^™

Reducing Human Error In Cyber Security Using The Human Factors Analysis Classification System (Hfacs)., Tommy Pollock

KSU Proceedings on Cybersecurity Education, Research and Practice

For several decades, researchers have stated that human error is a significant cause of information security breaches, yet it still remains to be a major issue today. Quantifying the effects of security incidents is often a difficult task because studies often understate or overstate the costs involved. Human error has always been a cause of failure in many industries and professions that is overlooked or ignored as an inevitability. The problem with human error is further exacerbated by the fact that the systems that are set up to keep networks secure are managed by humans. There are several causes of …

A Developmental Study On Assessing The Cybersecurity Competency Of Organizational Information System Users, Richard Nilsen, Yair Levy, Steven Terrell, Dawn Beyer

KSU Proceedings on Cybersecurity Education, Research and Practice

Organizational information system users (OISUs) that are open to cyber threats vectors are contributing to major financial and information losses for individuals, businesses, and governments. Moreover, technical cybersecurity controls may be rendered useless due to a lack of cybersecurity competency of OISUs. The main goal of this research study was to propose and validate, using subject matter experts (SMEs), a reliable hands-on assessment prototype tool for measuring the knowledge, skills, and abilities (KSAs) that comprise the cybersecurity competency of an OISU. Primarily using the Delphi methodology, this study implemented four phases of data collection using cybersecurity SMEs for proposing and …

Voice Hacking Proof Of Concept: Using Smartphones To Spread Ransomware To Traditional Pcs, Leonardo I. Mazuran, Bryson R. Payne, Tamirat T. Abegaz

KSU Proceedings on Cybersecurity Education, Research and Practice

This paper presents a working proof of concept that demonstrates the ability to deploy a sequence of hacks, triggered by speaking a smartphone command, to launch ransomware and other destructive attacks against vulnerable Windows computers on any wireless network the phone connects to after the voice command is issued. Specifically, a spoken, broadcast, or pre-recorded voice command directs vulnerable Android smartphones or tablets to a malicious download page that compromises the Android device and uses it as a proxy to run software designed to scan the Android device’s local area network for Windows computers vulnerable to the EternalBlue exploit, spreading …

Security Device Roles, Vabrice Wilder

KSU Proceedings on Cybersecurity Education, Research and Practice

“An abstract of this article was published in the proceedings of the Conference on Cybersecurity Education, Research & Practice, 2017”. Communication has evolved since the beginning of mankind from smoke signals to drones to now the internet. In a world filled with technology the security of one’s device is not to be taken for granted. A series of research was done in order to gather details about network devices that can aid in the protection of one’s information while being transferred through the internet. The findings included but not limited to, switches, the seven layers of OSI, routers, firewalls, load …

Analyzing Http Requests For Web Intrusion Detection, Sara Althubiti, Xiaohong Yuan, Albert Esterline

KSU Proceedings on Cybersecurity Education, Research and Practice

Many web application security problems related to intrusion have resulted from the rapid development of web applications. To reduce the risk of web application problems, web application developers need to take measures to write secure applications to prevent known attacks. When such measures fail, it is important to detect such attacks and find the source of the attacks to reduce the estimated risks. Intrusion detection is one of the powerful techniques designed to identify and prevent harm to the system. Most defensive techniques in Web Intrusion Systems are not able to deal with the complexity of cyber-attacks in web applications. …

"Think Before You Click. Post. Type." Lessons Learned From Our University Cyber Secuity Awareness Campaign, Rachael Innocenzi, Kaylee Brown, Peggy Liggit, Samir Tout, Andrea Tanner, Theodore Coutilish, Rocky Jenkins

KSU Proceedings on Cybersecurity Education, Research and Practice

This article discusses the lessons learned after implementing a successful university-wide cyber security campaign. The Cyber Security Awareness Committee (CyberSAC), a group comprised of diverse units across campus, collaborated together on resources, talent, people, equipment, technology, and assessment practices to meet strategic goals for cyber safety and education. The project involves assessing student learning and behavior changes after participating in a Cyber Security Password Awareness event that was run as a year-long campaign targeting undergraduate students. The results have implications for planning and implementing university-wide initiatives in the field of cyber security, and more broadly, higher education at large.

Ssetgami: Secure Software Education Through Gamification, Hector Suarez, Hooper Kincannon, Li Yang

KSU Proceedings on Cybersecurity Education, Research and Practice

Since web browsers have become essential to accomplishing everyday tasks, developing secure web applications has become a priority in order to protect user data, corporate databases and critical infrastructure against cyber-crimes . This research presents a game-like (gamification) approach to teach key concepts and skills on how to develop secure web applications. Gamification draws on motivational models, one of psychological theories. Gamification design has great potential over traditional education where we often find students demotivated and lecturers failing to engage them in learning activities. This research created game-like learning modules to teach top vulnerabilities and countermeasures for these top vulnerabilities …

The Transformation Of Science With Hpc, Big Data, And Ai, Jeffrey Kirk

Commonwealth Computational Summit

High performance computing has matured into an indispensable tool for not only academic research and government labs and agencies, but also for many industry sectors: energy, manufacturing, healthcare, financial services, even digital content creation. More recently, the advent of Big Data has enabled the use of HPC techniques for large scale data analysis, expanding the scope of HPC and the reach of it into more research and enterprise use cases. Since 2012, a new regime of data-driven analytics, deep learning, has erupted in popularity, fueled by both the massive performance increases in HPC technologies and in the explosive rate of …

Harnessing The Data Revolution, Chaitan Baru

Commonwealth Computational Summit

Harnessing Data for 21st Century Science and Engineering (aka Harnessing the Data Revolution, HDR) is one of NSF's six "Big Research Ideas," aimed at supporting fundamental research in data science and engineering; developing a cohesive, federated approach to the research data infrastructure needed to power this revolution; and developing of a 21st-century data-capable workforce. HDR will enable new modes of data-driven discovery allowing researchers to ask and answer new questions in frontier science and engineering, generate new knowledge and understanding by working with domain experts, and accelerate discovery and innovation. This initiative builds on NSF's history of data science investments. …

Tell Me Why? Tell Me More! Explaining Predictions, Iterated Learning Bias, And Counter-Polarization In Big Data Discovery Models, Olfa Nasraoui

Commonwealth Computational Summit

Outline:

What can go Wrong in Machine Learning?

• Unfair Machine Learning
• Iterated Bias & Polarization
• Black Box models

Tell me more: Counter-Polarization

Tell me why: Explanation Generation

Analysis Of Complex Vertebrate Genomes: Computational Challenges And Solutions, Jeramiah J. Smith

Commonwealth Computational Summit

No abstract provided.

Accurate And Scalable Query Over Large Rna‐Seq Experiments, Jinze Liu

Commonwealth Computational Summit

No abstract provided.

Resource Efficient Design Of Quantum Circuits For Quantum Algorithms, Himanshu Thapliyal

Commonwealth Computational Summit

No abstract provided.

Additional Data Via Autonomous Systems To Supplement Traditional Sparse Sources For Weather Forecasting And Atmospheric Science, Suzanne Weaver Smith

Commonwealth Computational Summit

No abstract provided.

Correct Model Selection In Multiple Regression Analyses Of Big Data, Katherine L. Thompson

Commonwealth Computational Summit

Goals:

• Improve statistical modeling in a variety of application areas
• Correctly identify the relationships present in data sets
• Understand the difficulty in choosing the correct statistical model in big data

Integrative Computational Modeling For Developing Means To Manipulate Biological Cells And For Solving Complex Engineering Problems, Yu Zhao, Guigen Zhang

Commonwealth Computational Summit

A brief discussion on reductive vs integrative investigation

A case study: how integrative computational modeling helps advance the understanding and application of dielectrophoresis (DEP) in various situations

Other applications in advancing the design and development of nanopore, medical devices, novel materials, actuation devices, and coupled spectroscopic techniques, etc.

Cloud‐Based Text Analytics Harvesting, Cleaning And Analyzing Corporate Earnings Conference Calls, Michael Chuancai Zhang, Vikram Gazula, Dan Stone, Hong Xie

Commonwealth Computational Summit

No abstract provided.

Grading Complex Tasks Through Crowdsourcing, Lingyu Lyu

Commonwealth Computational Summit

Crowdsourcing provides huge opportunities and scalability solutions for grading large scale tasks, such as MOOCs.

Reliability and quality of graders and crowdsourced data are challenging issues.

Workers might give random grades, which are spam; or provide biased grades, which need to be corrected.

The budget for hiring graders is limited, in many cases.

Parallelization Of A Three-Dimensional Full Multigrid Algorithm To Simulate Tumor Growth, Dylan Goodin, Chin F. Ng, Hermann B. Frieboes

Commonwealth Computational Summit

We present the performance gains of an openMP implementation of a fully adaptive nonlinear full multigrid (FMG) algorithm to simulate three-dimensional multispecies desmoplastic tumor growth on computer systems of varying processing capabilities. The FMG algorithm is applied to solve a recently published thermodynamic mixture model that uses a diffuse interface approach with fourth-order reaction-advection-diffusion PDEs (Cahn-Hilliard-type equations) that are coupled, nonlinear, and numerically stiff. The model includes multiple cell species and extracellular matrix (ECM), with adhesive and elastic energy contributions in chemical potential terms, as well as including blood and lymphatic vessels represented as continuous vasculatures. Advection-reaction-diffusion PDEs are employed …

The Effect Of Inlet Pulsations On Primary Atomization Of Liquid Jets, Kyle Windland, Prashant Khare

Commonwealth Computational Summit

Objectives

• Elucidate the physics underlying the primary atomization of liquid jets.
• Investigate the effect of inlet pulsations on the atomization process.
• Identify the reliability of numerical predictions using uncertainty quantification techniques (UQ) and sensitivity analyses.

Computational Materials Characterization, Discovery, And Design With High Performance Computing, Qunfei Zhou, Xiaotao Liu, Tyler Maxwell, Thomas John Balk, Matthew J. Beck

Commonwealth Computational Summit

No abstract provided.

New Explainable Active Learning Approach For Recommender Systems, Sami Khenissi, Behnoush Abdollahi, Wenlong Sun, Pegah Sagheb, Olfa Nasraoui

Commonwealth Computational Summit

Introduction and Motivations

• Recommender Systems are intelligent programs that analyze patterns between items and users to predict the user’s taste.

Objective

• Design an efficient Active Learning Strategy to increase the explainability and the accuracy of an “Explainable Matrix Factorization” model.

A Network Tomography Approach For Traffic Monitoring In Smart Cities, Ruoxi Zhang, Sara Newman, Marco Ortolani, Simone Silvestri

Commonwealth Computational Summit

Various urban planning and managing activities required by a Smart City are feasible because of traffic monitoring. As such, this project proposes a network tomography-based approach that can be applied to road networks to achieve a cost-efficient, flexible, and scalable monitor deployment. Due to the algebraic approach of network tomography, the selection of monitoring intersections can be solved through the use of matrices, with its rows representing paths between two intersections, and its columns representing links in the road network. Because the goal of the algorithm is to provide an inexpensive monitor set, this problem can be translated into a …

Bio-Inspired Disaster Response Networks, Vijay K. Shah, Simone Silvestri, Sajal K. Das, Satyaki Roy

Commonwealth Computational Summit

Large-scale natural disasters (e.g., Earthquake, Hurricane) –

• Three times as many disasters between 1980 and 2016 compared to 1940-1980. (EM-DAT – The International Disaster Database)
• Since 1990, 217 million people affected each year. (The New England Journal of Medicine)

Aftermath a disaster,

• Loss of human lives and property
• Lack of food, clean drinking water, shelter etc.
• Disruption of infrastructure networks (e.g. cellular towers) and other public infrastructures (e.g. power sources) – Our focus !

Formation Of Supermassive Black Holes In The Early Universe: High-Resolution Numerical Simulations Of Radiation Transfer Inside Collapsing Gas, Yang Luo, Kazem Ardaneh, Isaac Shlosman, Kentaro Nagamine, John Wise, Mitchell C. Begelman

Commonwealth Computational Summit

Observations of high-redshift quasars reveal that super massive black holes (SMBHs) with masses exceeding 10⁹ M_⊙ formed as early as redshift z ~ 7 [1,3,6]. This means that SMBHs have already formed ~700 million years after the Big Bang. How did such SMBHs could grow so quickly?

In this work, we use a modified and improved version of the blockstructured adaptive mesh refinement (AMR) code ENZO [2] to provide high spatial and temporal resolution for modeling the formation of SMBHs via direct collapse within dark matter (DM) halos at high redshifts. The radiation hydrodynamics equations are solved in …

Integrative Computational Modeling For Developing Means To Manipulate Biological Cells And For Solving Complex Engineering Problems, Yu Zhao, Guigen Zhang

Commonwealth Computational Summit

Computational modeling has become more widely used to guide the design of microfluidic devices for manipulating cells using Dielectrophoresis (DEP), and devise novel means for advancing the study of cellular science and engineering. Conventionally, cells are treated as volumeless points in the system, which allows study of the movement of groups of particles under the effect of field. However, this approach often neglects the distortion effect of particle on external field, as well as interactions among particles. Moreover, it ignores the complex inner structures of cell, which are the causes of distinctive cell behavior. To more accurately model the behavior …

Dynamic Load Balancing Based On Live Virtual Machine Migration, Manh Do, Michael Galloway

Commonwealth Computational Summit

Recently, cloud computing is a new trend emerging in computer technology with a huge demand from the clients, which leads to the consumption of a tremendous amount of energy. Load balancing is taken into account as a vital part of managing income demand, improving the cloud system's performance and reducing the energy cost. Live virtual machine migration is a technique to perform the dynamic load balancing algorithm. To optimize the cloud cluster, there are three issues to consider: First, how does the cloud cluster distribute the virtual machine (VM) requests from clients to all physical machine (PM) when each machine …

Cloud-Based Text Analytics: Harvesting, Cleaning And Analyzing Corporate Earnings Conference Calls, Michael Chuancai Zhang, Vikram Gazula, Dan Stone, Hong Xie

Commonwealth Computational Summit

Does management language cohesion in earnings conference calls matter to the capital market? As a part of the research on the above question, and taking advantage of the modern IT technologies, this project:

• harvested 115,882 earnings conference call transcripts from SeekingAlpha.com
• parsed and structured 89,988 transcripts using regular expressions in Stata
• analyzed 179,976 text files using Amazon Elastic Compute Cloud (Amazon EC2), which
• saved almost 2 years (675 days) of the project time

High-Fidelity Simulations Of Water Jet In Air Crossflow, Austin Johnston, Prashant Khare

Commonwealth Computational Summit

Objectives

• Investigate detailed physics underlying liquid jets in crossflow configurations applicable to various applications such as, gas-turbine, scramjet, and afterburner fuel injection.
• Develop models to predict the statistical behaviors of resulting droplets.

Adversarial Discriminative Domain Adaptation For Extracting Protein-Protein Interactions From Text, Anthony Rios, Ramakanth Kavuluru, Zhiyong Lu

Commonwealth Computational Summit

Relation extraction is the process of extracting structured information from unstructured text. Recently, neural networks (NNs) have produced state-of-art results in extracting protein-protein interactions (PPIs) from text. While multiple corpora have been created to extract PPIs from text, most methods have shown poor cross-corpora generalization. In other words, models trained on one dataset perform poorly on other datasets for the same task. In the case of PPI, the F1 has been shown to vary by as much as 30% between different datasets. In this work, we utilize adversarial discriminative domain adaptation (ADDA) to improve the generalization between the source and …