Open Access. Powered by Scholars. Published by Universities.®
- Discipline
- Keyword
-
- AI code generation (1)
- Adversarial testing (1)
- Artificial intelligence (1)
- Automotive software (1)
- CAN (1)
-
- CAPTCHA (1)
- Continuous monitoring (1)
- Cybersecurity (1)
- Embedded systems (1)
- Internet (1)
- Large language models (1)
- Least privilege (1)
- Micro-segmentation (1)
- Policy decision point (1)
- Policy enforcement point (1)
- Ransomware (1)
- ReCAPTCHA (1)
- Reinforcement learning (1)
- Secure coding practices (1)
- Security (1)
- Security risks (1)
- Turing test (1)
- Zero trust architecture (1)
Articles 1 - 4 of 4
Full-Text Articles in Cybersecurity
Assessing Flaws In Captcha Security Through Progress In Ai, Jaydon Stanislowski
Assessing Flaws In Captcha Security Through Progress In Ai, Jaydon Stanislowski
Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal
Protecting the internet from the threat of malicious bot activity is an important problem as AI tools become more powerful and commonplace over time. To that end, security measures are employed across websites in the form of CAPTCHAs, short challenges designed to identify and block fake web traffic. Yet, they become less effective over time as AI becomes more powerful, and thus more capable of solving them. This paper examines recent research on the threat to CAPTCHA security posed by current AI models and how this security can be reinforced over time, focusing primarily on Google’s reCAPTCHA v3.
Zero Trust Architecture And Ransomware Mitigation, Ely Johnson
Zero Trust Architecture And Ransomware Mitigation, Ely Johnson
Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal
Ransomware has become a critical threat to modern enterprises, exploiting excessive privileges and flat network architectures to spread rapidly. Traditional perimeter-based security models are insufficient, as they rely on implicit trust within internal networks. This paper examines how Zero Trust Architecture (ZTA) mitigates ransomware through least privilege access, continuous monitoring, and micro- segmentation. Experimental results show that ZTA can significantly reduce impact, limiting encryption to about 20% of targeted files while preserving most data. Continuous monitoring enables rapid detection (5.3 seconds) with high accuracy (up to 97.2%) and a 78% reduction in false positives. Micro-segmentation further restricts lateral movement, reducing …
Security Limitations Of The Can Bus And Detection Through Power Fingerprinting, Ken Broden
Security Limitations Of The Can Bus And Detection Through Power Fingerprinting, Ken Broden
Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal
This paper examines the vulnerabilities of the Controller Area Network (CAN), the standard communication protocol used in most modern vehicles. It explains why CAN is widely adopted and outlines key security weaknesses in its design. The paper then reviews recent research efforts to detect and mitigate these vulnerabilities, with particular focus on an approach to origin authentication that relies on the unique power consumption patterns of each individual electronic control unit on a CAN bus.
Securing Ai-Generated Code, Andreas E. Nelson
Securing Ai-Generated Code, Andreas E. Nelson
Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal
The increasing use of AI for code generation presents significant security challenges, as these tools often lack inherent security awareness and can produce vulnerable code. This paper investigates these security risks, outlining common types of vulnerabilities (such as injection flaws and improper resource handling) found in AI-generated code. It further explores and evaluates mitigation techniques aimed at im-proving code security, including model fine-tuning and adversarial strategies like Security Verifier Enhanced Neural Steering (SVEN). Findings indicate that while current methods offer promising ways to reduce vulnerabilities, ongoing research and development are crucial for the secure and responsible deployment of AI in …