OS and Networks Commons^™

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

Multipath Tcp, And New Packet Scheduling Method, Cole N. Maxwell

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

Today many devices contain hardware to transmit data across the internet via cellular, WiFi, and wired connections. Many of these devices communicate by using a protocol known as Transmission Control Protocol (TCP). TCP was developed when network resources were expensive, and it was rare for a typical network-aware device to have more than one connection to a network. An extension to TCP known as Multipath TCP (MPTCP) was developed to leverage the multiple network connections to which devices now have access. While the MPTCP extension has been successful in its goal of using multiple network connections to send data simultaneously, …

Learning And Understanding User Interface Semantics From Heterogeneous Networks With Multimodal And Positional Attributes, Meng Kiat Gary Ang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

User interfaces (UI) of desktop, web, and mobile applications involve a hierarchy of objects (e.g., applications, screens, view class, and other types of design objects) with multimodal (e.g., textual and visual) and positional (e.g., spatial location, sequence order, and hierarchy level) attributes. We can therefore represent a set of application UIs as a heterogeneous network with multimodal and positional attributes. Such a network not only represents how users understand the visual layout of UIs but also influences how users would interact with applications through these UIs. To model the UI semantics well for different UI annotation, search, and evaluation tasks, …

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. …

Adaptation Of Network Flow Problems For Course Of Action Generation, Alexander N. Stephens

Theses and Dissertations

This thesis introduces two methods to generate Courses of Action (COA) in distributed warfare scenarios: the Wargaming Commodity Course of Action Automated Method Under Uncertainty (WCCAAM-U2) and Dynamic Transshipment Problem (DTP)-generated COAs. Previous work by Deberry et al. used a Multi-Commodity Flow Problem (MCFP) to generate COAs for single-period wargame scenarios with known enemy force amounts. In WCCAAM-U2, we adapt an MCFP to work in situations where only intelligence estimates of enemy forces are known. Compared to two other COA-generation methods, the WCCAAAM-U2 COA outperforms the next highest-performing COA by 307% when compared by a ratio of objective success rate …

Quantization-Aware Interval Bound Propagation For Training Certifiably Robust Quantized Neural Networks, Mathias Lechner, Dorde Zikelic, Krishnendu Chatterjee, A. Thomas Henzinger, Daniela Rus

Research Collection School Of Computing and Information Systems

We study the problem of training and certifying adversarially robust quantized neural networks (QNNs). Quantization is a technique for making neural networks more efficient by running them using low-bit integer arithmetic and is therefore commonly adopted in industry. Recent work has shown that floating-point neural networks that have been verified to be robust can become vulnerable to adversarial attacks after quantization, and certification of the quantized representation is necessary to guarantee robustness. In this work, we present quantization-aware interval bound propagation (QA-IBP), a novel method for training robust QNNs. Inspired by advances in robust learning of non-quantized networks, our training …

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 …

An Enhanced Cloud-Native Deep Learning Pipeline For The Classification Of Network Traffic, Ahmed Sobhy Elkenawy

Theses and Dissertations

In a rapidly changing world, the way of solving real-world problems has changed to leverage the power of the advancements in multiple fields. Cloud-native computing approaches can be utilized with deep learning techniques to provide solutions in several important areas. For instance, with the emergence of the pandemic, much dependence on modern technologies came out as a replacement for face-to-face interaction. Deep learning can reach a high level of accuracy, which makes it very effective in the support of modern services and technologies. However, there are some challenging issues because deep learning requires many large-scale experiments, which demand a lot …

Artificial Intelligence Mechanisms In Countering Violent Extremism, Ammar Al-Babli

Journal of Police and Legal Sciences

The research idea revolves around the mechanisms of artificial intelligence in monitoring and combating extremist groups' dissemination of bad, misleading ideas, destructive ideologies, fake images, and videos, especially those related to terrorism and extremism. Artificial intelligence can be used to confront violent extremism on social media platforms. Social media companies widely use artificial intelligence in their efforts to remove and ban terrorist content from their platforms. The research includes threats arising from cyberspace, such as terrorism, promotion, recruitment, exploitation, and hate speech, to random email, as the ultimate goal of terrorists is to undermine societies and political systems by generating …

Proactive Scientific Forecasting Of Cyber Threats, Mohamed Badrat

Journal of Police and Legal Sciences

The cyber globalization has brought about significant transformations in human life. Despite supporting the goals of sustainable development, contributing to the exchange of ideas and beliefs, blending cultures and knowledge, and promoting the trade of goods and services among different peoples of the world, it poses threats to privacy and reduces security. Unethical behaviors and cyber crimes have been prevalent in this widespread and interconnected world, replacing traditional crimes with electronic ones. With the evolution of globalization and technological advancement, cyber threats undermine all avenues of progress and prosperity.

The study adopted a descriptive-analytical methodology to describe and study the …

Finding Forensic Evidence In The Operating System's Graphical User Interface, Edward X. Wilson Mr.

LSU Master's Theses

A branch of cyber security known as memory forensics focuses on extracting meaningful evidence from system memory. This analysis is often referred to as volatile memory analysis, and is generally performed on memory captures acquired from target systems. Inside of a memory capture is the complete state of a system under investigation, including the contents of currently running as well as previously executed applications. Analysis of this data can reveal a significant amount of activity that occurred on a system since the last reboot. For this research, the Windows operating system is targeted. In particular, the graphical user interface component …

Unmasking Deception In Vanets: A Decentralized Approach To Verifying Truth In Motion, Susan Zehra, Syed R. Rizvi, Steven Olariu

College of Sciences Posters

VANET, which stands for "Vehicular Ad Hoc Network," is a wireless network that allows vehicles to communicate with each other and with infrastructure, such as Roadside Units (RSUs), with the aim of enhancing road safety and improving the overall driving experience through real-time exchange of information and data. VANET has various applications, including traffic management, road safety alerts, and navigation. However, the security of VANET can be compromised if a malicious user alters the content of messages transmitted, which can harm both individual vehicles and the overall trust in VANET technology. Ensuring the correctness of messages is crucial for the …

A Novel Parking Management In Smart City Vehicular Datacenters, Syed Rizvi, Susan Zehra, Steven Olariu

College of Sciences Posters

Researchers have shown that most vehicles spend the majority of their time parked in parking garages, lots, or driveways. During this time, their computing resources are unused and untapped. This has led to substantial interest in Vehicular Cloud, an area of research in which each vehicle acts as a computation node. The main difference between traditional cloud computing and vehicular cloud computing is the availability of nodes. In traditional clouds, nodes are available 24/7, while in vehicular clouds, nodes (vehicles) are only available while parked in parking lots. This creates a dynamic environment as vehicles enter and exit parking garages …

Optimizing Deep Neural Networks Performance: Efficient Techniques For Training And Inference, Ankit Sharma

Graduate Thesis and Dissertation 2023-2024

Recent advances in computer vision tasks are mainly due to the success of large deep neural networks. The current state-of-the-art models have high computational costs during inference and suffer from a high memory footprint. Therefore, deploying these large networks on edge devices remains a serious concern. Furthermore, training these over-parameterized networks is computationally expensive and requires a longer training time. Thus, there is a demand to develop techniques that can efficiently reduce training costs and also be able to deploy neural networks on mobile and embedded devices. This dissertation presents practices like designing a lightweight network architecture and increasing network …

Defending Ai-Based Automatic Modulation Recognition Models Against Adversarial Attacks, Haolin Tang, Ferhat Ozgur Catak, Murat Kuzlu, Evren Catak, Yanxiao Zhao

Engineering Technology Faculty Publications

Automatic Modulation Recognition (AMR) is one of the critical steps in the signal processing chain of wireless networks, which can significantly improve communication performance. AMR detects the modulation scheme of the received signal without any prior information. Recently, many Artificial Intelligence (AI) based AMR methods have been proposed, inspired by the considerable progress of AI methods in various fields. On the one hand, AI-based AMR methods can outperform traditional methods in terms of accuracy and efficiency. On the other hand, they are susceptible to new types of cyberattacks, such as model poisoning or adversarial attacks. This paper explores the vulnerabilities …

Improving Connectivity For Remote Cancer Patient Symptom Monitoring And Reporting In Rural Medically Underserved Regions, Esther Max-Onakpoya

Theses and Dissertations--Computer Science

Rural residents are often faced with many disparities when compared to their urban counterparts. Two key areas where these disparities are apparent are access to health and Internet services. Improved access to healthcare services has the potential to increase residents' quality of life and life expectancy. Additionally, improved access to Internet services can create significant social returns in increasing job and educational opportunities, and improving access to healthcare. Therefore, this dissertation focuses on the intersection between access to Internet and healthcare services in rural areas. More specifically, it attempts to analyze systems that can be used to improve Internet access …

A Secure And Distributed Architecture For Vehicular Cloud And Protocols For Privacy-Preserving Message Dissemination In Vehicular Ad Hoc Networks, Hassan Mistareehi

Theses and Dissertations--Computer Science

Given the enormous interest in self-driving cars, Vehicular Ad hoc NETworks (VANETs) are likely to be widely deployed in the near future. Cloud computing is also gaining widespread deployment. Marriage between cloud computing and VANETs would help solve many of the needs of drivers, law enforcement agencies, traffic management, etc. The contributions of this dissertation are summarized as follows: A Secure and Distributed Architecture for Vehicular Cloud: Ensuring security and privacy is an important issue in the vehicular cloud; if information exchanged between entities is modified by a malicious vehicle, serious consequences such as traffic congestion and accidents can …

Energy-Efficient Multi-Rate Opportunistic Routing In Wireless Mesh Networks, Mohammad Ali Mansouri Khah, Neda Moghim, Nasrin Gholami, Sachin Shetty

VMASC Publications

Opportunistic or anypath routing protocols are focused on improving the performance of traditional routing in wireless mesh networks. They do so by leveraging the broadcast nature of the wireless medium and the spatial diversity of the network. Using a set of neighboring nodes, instead of a single specific node, as the next hop forwarder is a crucial aspect of opportunistic routing protocols, and the selection of the forwarder set plays a vital role in their performance. However, most opportunistic routing protocols consider a single transmission rate and power for the nodes, which limits their potential. To address this limitation, this …

A Novel Approach To Detecting And Mitigating Keyloggers, Damilola Osedumbi Elelegwu

College of Graduate Studies: Theses & Dissertations

As the digital world gets increasingly ingrained in our daily lives, cyberattacks—especially those involving malware—are growing more complex and common, which calls for developing innovative safeguards. Keylogger spyware, which combines keylogging and spyware functionalities, is one of the most insidious types of cyberattacks. This malicious software stealthily monitors and records user keystrokes, amassing sensitive data, such as passwords and confidential personal information, which can then be exploited. This research work introduces a novel browser extension designed to thwart keylogger spyware attacks effectively. The extension is underpinned by a cutting-edge algorithm that meticulously analyzes input-related processes, promptly identifying and flagging any …

Integration Of Omnet++ Into A Networking Course In An Electrical Engineering Technology Program, Murat Kuzlu, Brian Emmanuel Tamayo, Salih Sarp, Otilia Popescu, Vukica M. Jovanovic

Engineering Technology Faculty Publications

Networking courses are an integral part of electrical engineering technology programs as the majority of electronics in the modern day are required to communicate with each other. They are also getting more attention in manufacturing engineering technology programs because of the development of emerging technologies in Industry 4.0 arena. From laptops, computers, cellphones, modern day vehicles and smart refrigerators, these devices require a certain level of networking in order to communicate with other devices, whether it be locally, or even across the other side of the world. The objective of networking courses in an electrical engineering program is to demonstrate …