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Articles 1411 - 1440 of 4827

Full-Text Articles in Computer Sciences

A Low-Cost Machine Learning Based Network Intrusion Detection System With Data Privacy Preservation, Jyoti Fakirah, Lauhim Mahfuz Zishan, Roshni Mooruth, Michael L. Johnstone, Wencheng Yang Jan 2022

A Low-Cost Machine Learning Based Network Intrusion Detection System With Data Privacy Preservation, Jyoti Fakirah, Lauhim Mahfuz Zishan, Roshni Mooruth, Michael L. Johnstone, Wencheng Yang

Annual ADFSL Conference on Digital Forensics, Security and Law

Network intrusion is a well-studied area of cyber security. Current machine learning-based network intrusion detection systems (NIDSs) monitor network data and the patterns within those data but at the cost of presenting significant issues in terms of privacy violations which may threaten end-user privacy. Therefore, to mitigate risk and preserve a balance between security and privacy, it is imperative to protect user privacy with respect to intrusion data. Moreover, cost is a driver of a machine learning-based NIDS because such systems are increasingly being deployed on resource-limited edge devices. To solve these issues, in this paper we propose a NIDS …

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Human-Controlled Fuzzing With Afl, Maxim Grishin, Igor Korkin, Phd Jan 2022

Human-Controlled Fuzzing With Afl, Maxim Grishin, Igor Korkin, Phd

Annual ADFSL Conference on Digital Forensics, Security and Law

Fuzzing techniques are applied to reveal different types of bugs and vulnerabilities. American Fuzzy Lop (AFL) is a free most popular software fuzzer used by many other fuzzing frameworks. AFL supports autonomous mode of operation that uses the previous step output into the next step, as a result fuzzer spends a lot of time analyzing minor code sections. By making fuzzing process more focused and human controlled security expert can save time and find more bugs in less time. We designed a new module that can fuzz only the specified functions. As a result, the chosen ones will be inspected …

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The Amorphous Nature Of Hackers: An Exploratory Study, Kento Yasuhara, Daniel Walnycky, Ibrahim Baggili, Ahmed Alhishwan Jan 2022

The Amorphous Nature Of Hackers: An Exploratory Study, Kento Yasuhara, Daniel Walnycky, Ibrahim Baggili, Ahmed Alhishwan

Annual ADFSL Conference on Digital Forensics, Security and Law

In this work, we aim to better understand outsider perspectives of the hacker community through a series of situation based survey questions. By doing this, we hope to gain insight into the overall reputation of hackers from participants in a wide range of technical and non-technical backgrounds. This is important to digital forensics since convicted hackers will be tried by people, each with their own perception of who hackers are. Do cyber crimes and national security issues negatively affect people’s perceptions of hackers? Does hacktivism and information warfare positively affect people’s perception of hackers? Do individual personality factors affect one’s …

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The Two-Echelon Vehicle Routing Problem With Transshipment Nodes And Occasional Drivers: Formulation And Adaptive Large Neighborhood Search Heuristic, Vincent F. Yu, Minh P. K. Nguyen, Kuza Putra, Aldy Gunawan, I. Gusti Bagus Budi Dharma Jan 2022

The Two-Echelon Vehicle Routing Problem With Transshipment Nodes And Occasional Drivers: Formulation And Adaptive Large Neighborhood Search Heuristic, Vincent F. Yu, Minh P. K. Nguyen, Kuza Putra, Aldy Gunawan, I. Gusti Bagus Budi Dharma

Research Collection School Of Computing and Information Systems

This research introduces a new variant of the two-echelon vehicle routing problem (2EVRP) called the two-echelon vehicle routing problem with transshipment nodes and occasional drivers (2EVRP-TN-OD). In addition to city freighters in the second-echelon network, a set of occasional drivers (ODs) is available to serve customers. ODs are the basis of a crowd-shipping system in which crowds with planned trips are willing to take detours to deliver packages in exchange for some compensation. To serve customers, ODs collect the assigned packages at either satellite served by first-echelon trucks or transshipment nodes served by city freighters. We formulate this problem as …

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A Comparison Of Deep Learning Algorithms On Image Data For Detecting Floodwater On Roadways, Sarp Salih, Kuzlu Murat, Zhao Yanxiao, Cetin Mecit Jan 2022

A Comparison Of Deep Learning Algorithms On Image Data For Detecting Floodwater On Roadways, Sarp Salih, Kuzlu Murat, Zhao Yanxiao, Cetin Mecit

Engineering Technology Faculty Publications

Object detection and segmentation algorithms evolved significantly in the last decade. Simultaneous object detection and segmentation paved the way for real-time applications such as autonomous driving. Detection and segmentation of (partially) flooded roadways are essential inputs for vehicle routing and traffic management systems. This paper proposes an automatic floodwater detection and segmentation method utilizing the Mask Region-Based Convolutional Neural Networks (Mask-R-CNN) and Generative Adversarial Networks (GAN) algorithms. To train the model, manually labeled images with urban, suburban, and natural settings are used. The performances of the algorithms are assessed in accurately detecting the floodwater captured in images. The results show …

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Examination Of Strategies To Implementing Chip-And-Personal Identification Number Credit Card Authentication Infrastructures, Neville Arthur Gallimore Jan 2022

Examination Of Strategies To Implementing Chip-And-Personal Identification Number Credit Card Authentication Infrastructures, Neville Arthur Gallimore

Walden Dissertations and Doctoral Studies

Chip-and-Personal Identification Number (PIN) technology is seen as a game changer in many e-commerce industries and a transformational technology in the 21st century. However, security concerns have made chip-and-PIN adoption relatively slow. Massive unauthorized card payment transactions in the United States (U.S.) cost victims an estimate totaling billions of dollars. Information Technology (IT) managers are concerned with credit card fraud's financial loss and liability cost. Grounded in Rogers’s diffusion of innovation theory, the purpose of this qualitative pragmatic study was to explore strategies used by IT managers to transition their e-commerce organizations to chip-and-PIN credit card authentication infrastructures. The participants …

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Modernization Of Legacy Information Technology Systems, Rabie Khabouze Jan 2022

Modernization Of Legacy Information Technology Systems, Rabie Khabouze

Walden Dissertations and Doctoral Studies

Large enterprises spend a large portion of their Information Technology (IT) budget on maintaining their legacy systems. Legacy systems modernization projects are a catalyst for IT architects to save cost, provide new and efficient systems that increase profitability, and create value for their organization. Grounded in sociotechnical systems theory, the purpose of this qualitative multiple case study was to explore strategies IT architects use to modernize their legacy systems. The population included IT architects in large enterprises involved in legacy systems modernization projects, one in healthcare, and one in the financial services industry in the San Antonio-New Braunfels, Texas metropolitan …

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Strategy: A Business And Cybersecurity Intertwined Necessity, Sharon L. Burton Jan 2022

Strategy: A Business And Cybersecurity Intertwined Necessity, Sharon L. Burton

Publications

Strategy development and application continue to shift. Evolving leadership with well-informed judgment relating to generating sound strategy within the realm of cybersecurity strengthening methods remains perplexing in this COVID-19 pandemic epoch. Investigated in this paper is the shaping of this context regarding the leadership position to study spats, procedures, and the way that this data clarifies the organization and outcomes of cybersecurity awareness, proficiency, know-how, practice, actions, purposes, harmonization, in addition to know-how immersion. This investigation’s documentation is geared toward the expansion of the context and semi-structured purposive sampling interview outcomes as this context is rationalized via the proper instrument …

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Exclusion Cycles: Reinforcing Disparities In Medicine, Ana Bracic, Shawneequa L. Callier, Nicholson Price Jan 2022

Exclusion Cycles: Reinforcing Disparities In Medicine, Ana Bracic, Shawneequa L. Callier, Nicholson Price

Articles

Minoritized populations face exclusion across contexts from politics to welfare to medicine. In medicine, exclusion manifests in substantial disparities in practice and in outcome. While these disparities arise from many sources, the interaction between institutions, dominant-group behaviors, and minoritized responses shape the overall pattern and are key to improving it. We apply the theory of exclusion cycles to medical practice, the collection of medical big data, and the development of artificial intelligence in medicine. These cycles are both self-reinforcing and other-reinforcing, leading to dismayingly persistent exclusion. The interactions between such cycles offer lessons and prescriptions for effective policy.

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Modeling And Visualization Of Long-Term Public Opinion On Covid-19 Vaccine, Ashiqur Rahman Jan 2022

Modeling And Visualization Of Long-Term Public Opinion On Covid-19 Vaccine, Ashiqur Rahman

Graduate Research Theses & Dissertations

The coronavirus pandemic created significant dependence on social media. While the social web was crucial in spreading timely information and informing the public, misinformation has also spread with little to no oversight. Several works have focused on identifying misinformation and topic analysis in COVID-19 (SARS-COV-2) tweets. While most of the previous studies focus on a shorter time frame, we analyzed a larger dataset starting from the beginning of the pandemic until the end of December 2021. Our work focuses on a novel area that identifies the motivating and demotivating topics of COVID-19 vaccination and analyzes these topics based on time, …

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Digital Forensics For Mobility As A Service Platform: Analysis Of Uber Application On Iphone And Cloud, Nina Matulis, Umit Karabiyik Jan 2022

Digital Forensics For Mobility As A Service Platform: Analysis Of Uber Application On Iphone And Cloud, Nina Matulis, Umit Karabiyik

Annual ADFSL Conference on Digital Forensics, Security and Law

Uber is a ride-hailing smartphone application (app) that allows users to order a ride in a highly efficient manner. The Uber app provides Mobility as a Service and allows users to easily order a ride in a private car with just a few clicks. Uber stores large amounts of data on both the mobile device the app is being used on, and in the cloud. Examples of this data include geolocation data, date/time, origin/destination addresses, departure/arrival times, and distance. Uber geolocation data has been previously researched to investigate the privacy of the Uber app; however, there is minimal research relating …

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Smart Home Forensics: Identifying Ddos Attack Patterns On Iot Devices, Samuel Ho, Hope Greeson, Umit Karabiyik Jan 2022

Smart Home Forensics: Identifying Ddos Attack Patterns On Iot Devices, Samuel Ho, Hope Greeson, Umit Karabiyik

Annual ADFSL Conference on Digital Forensics, Security and Law

Smart homes are becoming more common as more people integrate IoT devices into their home environment. As such, these devices have access to personal data on their homeowners’ networks. One of the advantages of IoT devices is that they are compact. However, this limits the incorporation of security measures in their hardware. Misconfigured IoT devices are commonly the target of malicious attacks. Additionally, distributed denial-of-service attacks are becoming more common due to applications and software that provides users with easy-to-use user interfaces. Since one vulnerable device is all an attacker needs to launch an attack on a network, in regards …

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Strategies For Catalyzing Supply Chain Innovation In Midsized Manufacturing Firms, Matthew J. Szukalowski Iii Jan 2022

Strategies For Catalyzing Supply Chain Innovation In Midsized Manufacturing Firms, Matthew J. Szukalowski Iii

Walden Dissertations and Doctoral Studies

Supply chain inflexibility results in reduced efficiency and profitability. Without supply chain flexibility, supply chain managers in manufacturing firms risk the loss of competitive advantage due to reduced efficiency and profitability. Grounded in business process engineering conceptual framework, the purpose of this qualitative multiple case study was to explore strategies supply chain leaders in manufacturing organizations use to achieve supply chain flexibility. The participants were five supply chain leaders in the manufacturing industry in the midwestern United States and successfully implemented innovative solutions to achieve supply chain flexibility. Data were collected using semistructured interviews and a review of company documents …

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Forward-Looking Strategies For Safely Adopting Digital Transformation In Aviation, Melissa King Jan 2022

Forward-Looking Strategies For Safely Adopting Digital Transformation In Aviation, Melissa King

Walden Dissertations and Doctoral Studies

Aviation leaders in the U.S. federal government face challenges in adopting technical evolution and advancing modernization while adhering to the rigor of a deeply entrenched safety culture. The purpose of this qualitative modified Delphi study was to determine how a panel of 21 aerospace experts based in Washington, DC viewed strategies for adopting to new technologies while ensuring safety. The management concepts that framed the study were safety culture and digital transformation. The study addressed the research question of how a panel of aviation experts viewed the desirability, feasibility, and importance of forward-looking strategies for adopting digital transformation while adhering …

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Strategies That Improve Ux (User Experience) Design Through Product Innovation, Jibing Zhao Jan 2022

Strategies That Improve Ux (User Experience) Design Through Product Innovation, Jibing Zhao

Walden Dissertations and Doctoral Studies

User Experience (UX) design improvement can alter business results. Information technology (IT) company leaders are concerned with UX design improvement, as it is the number one indication of product innovation success and user satisfaction. Grounded in Christensen’s disruptive innovation theory, the purpose of the qualitative single case study was to explore strategies IT company leaders and UX designers used to identify critical UX design elements that lead to improved product innovations. The participants were five IT company leaders and a focus group of four UX designers employed by a sizeable telecom organization in Beijing, China. The data were collected from …

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Using Ai-Enabled Gaze Tracking System To Understand Comprehension Patterns Of Computer Science Students, Bradley Boswell Jan 2022

Using Ai-Enabled Gaze Tracking System To Understand Comprehension Patterns Of Computer Science Students, Bradley Boswell

College of Graduate Studies: Theses & Dissertations

Academic institutions and instructors lack the ability to accurately assess the moment-to-moment attentiveness of students in classrooms where students’ faces are obscured by computer monitors. This can cause the lectures of Computer Science, Information Technology, or other lab-based courses to be incorrectly-paced, which can lead to students having an overall poorer grasp of the subject material. We propose a system for real-time accurate detection of classroom attentiveness using monitor-mounted webcams and eye trackers, along with a Convolutional Neural Network machine learning model (NiCATS). Through the use of a neural network, we produce an initial attentiveness score based on student webcam …

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Microsoft Defender Will Be Defended: Memoryranger Prevents Blinding Windows Av, Denis Pogonin, Igor Korkin, Phd Jan 2022

Microsoft Defender Will Be Defended: Memoryranger Prevents Blinding Windows Av, Denis Pogonin, Igor Korkin, Phd

Annual ADFSL Conference on Digital Forensics, Security and Law

Windows OS is facing a huge rise in kernel attacks. An overview of popular techniques that result in loading kernel drivers will be presented. One of the key targets of modern threats is disabling and blinding Microsoft Defender, a default Windows AV. The analysis of recent driver-based attacks will be given, the challenge is to block them. The survey of user- and kernel-level attacks on Microsoft Defender will be given. One of the recently published attackers’ techniques abuses Mandatory Integrity Control (MIC) and Security Reference Monitor (SRM) by modifying Integrity Level and Debug Privileges for the Microsoft Defender via syscalls. …

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Bias Mitigation For Toxicity Detection Via Sequential Decisions, Lu Cheng, Ahmadreza Mosallanezhad, Yasin N. Silva, Deborah Hall, Huan Liu Jan 2022

Bias Mitigation For Toxicity Detection Via Sequential Decisions, Lu Cheng, Ahmadreza Mosallanezhad, Yasin N. Silva, Deborah Hall, Huan Liu

Computer Science: Faculty Publications and Other Works

Increased social media use has contributed to the greater prevalence of abusive, rude, and offensive textual comments. Machine learning models have been developed to detect toxic comments online, yet these models tend to show biases against users with marginalized or minority identities (e.g., females and African Americans). Established research in debiasing toxicity classifiers often (1) takes a static or batch approach, assuming that all information is available and then making a one-time decision; and (2) uses a generic strategy to mitigate different biases (e.g., gender and racial biases) that assumes the biases are independent of one another. However, in real …

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Exploring Algorithmic Literacy For College Students: An Educator’S Roadmap, Susan Gardner Archambault Jan 2022

Exploring Algorithmic Literacy For College Students: An Educator’S Roadmap, Susan Gardner Archambault

LMU Theses and Dissertations

Research shows that college students are largely unaware of the impact of algorithms on their everyday lives. Also, most university students are not being taught about algorithms as part of the regular curriculum. This exploratory, qualitative study aimed to explore subject-matter experts’ insights and perceptions of the knowledge components, coping behaviors, and pedagogical considerations to aid faculty in teaching algorithmic literacy to college students. Eleven individual, semi-structured interviews and one focus group were conducted with scholars and teachers of critical algorithm studies and related fields. Findings suggested three sets of knowledge components that would contribute to students’ algorithmic literacy: general …

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Detection Of Overlapping Passive Manipulation Techniques In Image Forensics, Gianna S. Lint, Umit Karabiyik Jan 2022

Detection Of Overlapping Passive Manipulation Techniques In Image Forensics, Gianna S. Lint, Umit Karabiyik

Annual ADFSL Conference on Digital Forensics, Security and Law

With a growing number of images uploaded daily to social media sites, it is essential to understand if an image can be used to trace its origin. Forensic investigations are focusing on analyzing images that are uploaded to social media sites resulting in an emphasis on building and validating tools. There has been a strong focus on understanding active manipulation or tampering techniques and building tools for analysis. However, research on manipulation is often studied in a vacuum, involving only one technique at a time. Additionally, less focus has been placed on passive manipulation, which can occur by simply uploading …

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Bitcoin Selfish Mining Modeling And Dependability Analysis, Chencheng Zhou, Liudong Xing, Jun Guo, Qisi Liu Jan 2022

Bitcoin Selfish Mining Modeling And Dependability Analysis, Chencheng Zhou, Liudong Xing, Jun Guo, Qisi Liu

Electrical & Computer Engineering Faculty Publications

Blockchain technology has gained prominence over the last decade. Numerous achievements have been made regarding how this technology can be utilized in different aspects of the industry, market, and governmental departments. Due to the safety-critical and security-critical nature of their uses, it is pivotal to model the dependability of blockchain-based systems. In this study, we focus on Bitcoin, a blockchain-based peer-to-peer cryptocurrency system. A continuous-time Markov chain-based analytical method is put forward to model and quantify the dependability of the Bitcoin system under selfish mining attacks. Numerical results are provided to examine the influences of several key parameters related to …

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Arithfusion: An Arithmetic Deep Model For Temporal Remote Sensing Image Fusion, Md Reshad Ul Hoque, Jian Wu, Chiman Kwan, Krzysztof Koperski, Jiang Li Jan 2022

Arithfusion: An Arithmetic Deep Model For Temporal Remote Sensing Image Fusion, Md Reshad Ul Hoque, Jian Wu, Chiman Kwan, Krzysztof Koperski, Jiang Li

Electrical & Computer Engineering Faculty Publications

Different satellite images may consist of variable numbers of channels which have different resolutions, and each satellite has a unique revisit period. For example, the Landsat-8 satellite images have 30 m resolution in their multispectral channels, the Sentinel-2 satellite images have 10 m resolution in the pan-sharp channel, and the National Agriculture Imagery Program (NAIP) aerial images have 1 m resolution. In this study, we propose a simple yet effective arithmetic deep model for multimodal temporal remote sensing image fusion. The proposed model takes both low- and high-resolution remote sensing images at t1 together with low-resolution images at a …

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Eye Movement And Pupil Measures: A Review, Bhanuka Mahanama, Yasith Jayawardana, Sundararaman Rengarajan, Gavindya Jayawardena, Leanne Chukoskie, Joseph Snider, Sampath Jayarathna Jan 2022

Eye Movement And Pupil Measures: A Review, Bhanuka Mahanama, Yasith Jayawardana, Sundararaman Rengarajan, Gavindya Jayawardena, Leanne Chukoskie, Joseph Snider, Sampath Jayarathna

Computer Science Faculty Publications

Our subjective visual experiences involve complex interaction between our eyes, our brain, and the surrounding world. It gives us the sense of sight, color, stereopsis, distance, pattern recognition, motor coordination, and more. The increasing ubiquity of gaze-aware technology brings with it the ability to track gaze and pupil measures with varying degrees of fidelity. With this in mind, a review that considers the various gaze measures becomes increasingly relevant, especially considering our ability to make sense of these signals given different spatio-temporal sampling capacities. In this paper, we selectively review prior work on eye movements and pupil measures. We first …

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Streaminghub: Interactive Stream Analysis Workflows, Yasith Jayawardana, Vikas G. Ashok, Sampath Jayarathna Jan 2022

Streaminghub: Interactive Stream Analysis Workflows, Yasith Jayawardana, Vikas G. Ashok, Sampath Jayarathna

Computer Science Faculty Publications

Reusable data/code and reproducible analyses are foundational to quality research. This aspect, however, is often overlooked when designing interactive stream analysis workflows for time-series data (e.g., eye-tracking data). A mechanism to transmit informative metadata alongside data may allow such workflows to intelligently consume data, propagate metadata to downstream tasks, and thereby auto-generate reusable, reproducible analytic outputs with zero supervision. Moreover, a visual programming interface to design, develop, and execute such workflows may allow rapid prototyping for interdisciplinary research. Capitalizing on these ideas, we propose StreamingHub, a framework to build metadata propagating, interactive stream analysis workflows using visual programming. We conduct …

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D-Lib Magazine Pioneered Web-Based Scholarly Communication, Michael L. Nelson, Herbert Van De Sompel Jan 2022

D-Lib Magazine Pioneered Web-Based Scholarly Communication, Michael L. Nelson, Herbert Van De Sompel

Computer Science Faculty Publications

The web began with a vision of, as stated by Tim Berners-Lee in 1991, “that much academic information should be freely available to anyone”. For many years, the development of the web and the development of digital libraries and other scholarly communications infrastructure proceeded in tandem. A milestone occurred in July, 1995, when the first issue of D-Lib Magazine was published as an online, HTML-only, open access magazine, serving as the focal point for the then emerging digital library research community. In 2017 it ceased publication, in part due to the maturity of the community it served as well as …

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Scholarly Big Data Quality Assessment: A Case Study Of Document Linking And Conflation With S2orc, Jian Wu, Ryan Hiltabrand, Dominik Soós, C. Lee Giles Jan 2022

Scholarly Big Data Quality Assessment: A Case Study Of Document Linking And Conflation With S2orc, Jian Wu, Ryan Hiltabrand, Dominik Soós, C. Lee Giles

Computer Science Faculty Publications

Recently, the Allen Institute for Artificial Intelligence released the Semantic Scholar Open Research Corpus (S2ORC), one of the largest open-access scholarly big datasets with more than 130 million scholarly paper records. S2ORC contains a significant portion of automatically generated metadata. The metadata quality could impact downstream tasks such as citation analysis, citation prediction, and link analysis. In this project, we assess the document linking quality and estimate the document conflation rate for the S2ORC dataset. Using semi-automatically curated ground truth corpora, we estimated that the overall document linking quality is high, with 92.6% of documents correctly linking to six major …

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The Dsa Toolkit Shines Light Into Dark And Stormy Archives, Shawn Morgan Jones, Himarsha R. Jayanetti, Alex Osborne, Paul Koerbin, Klein Martin, Michele C. Weigle, Michael L. Nelson Jan 2022

The Dsa Toolkit Shines Light Into Dark And Stormy Archives, Shawn Morgan Jones, Himarsha R. Jayanetti, Alex Osborne, Paul Koerbin, Klein Martin, Michele C. Weigle, Michael L. Nelson

Computer Science Faculty Publications

Web archive collections are created with a particular purpose in mind. A curator selects seeds, or original resources, which are then captured by an archiving system and stored as archived web pages, or mementos. The systems that build web archive collections are often configured to revisit the same original resource multiple times. This is incredibly useful for understanding an unfolding news story or the evolution of an organization. Unfortunately, over time, some of these original resources can go off-topic and no longer suit the purpose for which the collection was originally created. They can go off-topic due to web site …

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Theory Entity Extraction For Social And Behavioral Sciences Papers Using Distant Supervision, Xin Wei, Lamia Salsabil, Jian Wu Jan 2022

Theory Entity Extraction For Social And Behavioral Sciences Papers Using Distant Supervision, Xin Wei, Lamia Salsabil, Jian Wu

Computer Science Faculty Publications

Theories and models, which are common in scientific papers in almost all domains, usually provide the foundations of theoretical analysis and experiments. Understanding the use of theories and models can shed light on the credibility and reproducibility of research works. Compared with metadata, such as title, author, keywords, etc., theory extraction in scientific literature is rarely explored, especially for social and behavioral science (SBS) domains. One challenge of applying supervised learning methods is the lack of a large number of labeled samples for training. In this paper, we propose an automated framework based on distant supervision that leverages entity mentions …

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A Synthetic Prediction Market For Estimating Confidence In Published Work, Sarah Rajtmajer, Christopher Griffin, Jian Wu, Robert Fraleigh, Laxmann Balaji, Anna Squicciarini, Anthony Kwasnica, David Pennock, Michael Mclaughlin, Timothy Fritton, Nishanth Nakshatri, Arjun Menon, Sai Ajay Modukuri, Rajal Nivargi, Xin Wei, Lee Giles Jan 2022

A Synthetic Prediction Market For Estimating Confidence In Published Work, Sarah Rajtmajer, Christopher Griffin, Jian Wu, Robert Fraleigh, Laxmann Balaji, Anna Squicciarini, Anthony Kwasnica, David Pennock, Michael Mclaughlin, Timothy Fritton, Nishanth Nakshatri, Arjun Menon, Sai Ajay Modukuri, Rajal Nivargi, Xin Wei, Lee Giles

Computer Science Faculty Publications

[First paragraph] Concerns about the replicability, robustness and reproducibility of findings in scientific literature have gained widespread attention over the last decade in the social sciences and beyond. This attention has been catalyzed by and has likewise motivated a number of large-scale replication projects which have reported successful replication rates between 36% and 78%. Given the challenges and resources required to run high-powered replication studies, researchers have sought other approaches to assess confidence in published claims. Initial evidence has supported the promise of prediction markets in this context. However, they require the coordinated, sustained effort of collections of human experts …

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Taming The Data In The Internet Of Vehicles, Shahab Tayeb Jan 2022

Taming The Data In The Internet Of Vehicles, Shahab Tayeb

Mineta Transportation Institute

As an emerging field, the Internet of Vehicles (IoV) has a myriad of security vulnerabilities that must be addressed to protect system integrity. To stay ahead of novel attacks, cybersecurity professionals are developing new software and systems using machine learning techniques. Neural network architectures improve such systems, including Intrusion Detection System (IDSs), by implementing anomaly detection, which differentiates benign data packets from malicious ones. For an IDS to best predict anomalies, the model is trained on data that is typically pre-processed through normalization and feature selection/reduction. These pre-processing techniques play an important role in training a neural network to optimize …

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