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Articles 1 - 5 of 5
Full-Text Articles in Cybersecurity
Friend Or Foe? The Benefits And Risks Of Llms In Cybersecurity, Niklas P. Dobler
Friend Or Foe? The Benefits And Risks Of Llms In Cybersecurity, Niklas P. Dobler
Honors Theses
The rapid growth of Large Language Models (LLMs) and their continuous increase in capabilities have affected many professions and people. Due to advancements in areas such as coding and data analysis, they are now also being utilized in Cybersecurity. Recent research has examined their use in many different areas such vulnerability detection in code and analyzing network traffic. With this rapid growth, most organizations around the world are eager to advance faster than their competition, with limited considerations for the potential harm and risks these tools could bring. Some research has been conducted on malicious uses, but as the benefits …
The Privacy Paradox: How Does Concern About Privacy Impact Actions In The Digital Age?, Julia Laduke
The Privacy Paradox: How Does Concern About Privacy Impact Actions In The Digital Age?, Julia Laduke
Honors Theses
The privacy paradox occurs when people claim to care about their digital privacy, but do not take actions to keep their data from being spread across the internet. This study examines college students, being primarily Generation Z, and their concerns and actions regarding digital privacy and security. A survey of 15 college students, 7 in humanities and 8 in STEM, was used to analyze their thoughts and concerns about their digital privacy. This survey also asked whether they took actions concerning their privacy, and if so, what tools they used to protect it. The results show that about 50% of …
Survey On Application Of Large Language Models In Network Attack And Defense, Prisha Purohit
Survey On Application Of Large Language Models In Network Attack And Defense, Prisha Purohit
Honors Theses
The emergence of Large Language Models (LLMs) has significantly transformed the technological and cybersecurity landscape, introducing both unprecedented opportunities and formidable challenges. With the public release of ChatGPT in 2022, LLMs have gained global prominence, redefining natural language processing capabilities and enabling advancements across various fields. In cybersecurity, these models represent a dual-use technology: while they offer powerful tools for threat detection, automated analysis, and security training, they also pose risks when leveraged by malicious actors for phishing, social engineering, and the creation of evasive malware. This thesis presents a comprehensive literature review exploring the dual roles of LLMs in …
A Web Application For Comparing Llm And Knowledge Graph Performance On Cybersecurity Queries, Major Schwartz
A Web Application For Comparing Llm And Knowledge Graph Performance On Cybersecurity Queries, Major Schwartz
Honors Theses
The evolution of cybersecurity has led to a spike in digital threats, both in frequency and complexity, necessitating advanced, intelligent solutions to protect sensitive information. Traditional defense mechanisms are increasingly inadequate, pushing cybersecurity professionals to seek innovative approaches for threat detection, response, and data analysis. This thesis investigates the integration of Large Language Models (LLMs) and Knowledge Graphs into cybersecurity workflows to address these challenges. Specifically, it explores the development of a web application that enables real-time, interactive use of state-of-the-art LLMs, such as OpenAI’s GPT-4 and similar models, for improved threat response and workflow efficiency. Built with a React …
Phantom Jam Sybil Attack In Connected Vehicular Networks, Ahmed Ali Elamin Mohamed
Phantom Jam Sybil Attack In Connected Vehicular Networks, Ahmed Ali Elamin Mohamed
Masters Theses and Doctoral Dissertations
Vehicular Ad-hoc Networks (VANETs) are vulnerable to Sybil attacks, mostly due to the lack of encryption in BSMs. In VANETs, multiple digital certificates (pseudonyms) are assigned to each vehicle to ensure their privacy. However, malicious nodes can exploit these pseudonyms to create ghost vehicles, inducing fake traffic jams and disturbance to other vehicles which may lead to accidents. In this work, we have developed the first sophisticated sybil attack, in which an attacker uses legitimate pseudonyms to create multiple ghost vehicles. These ghost vehicles transmit realistic kinematic data, using trajectory formulas and road maps. Additionally, the ghost vehicles randomly simulate …