2 citations · 2 across the 3 of their papers we have counts for
5 papers
Comparative Insights on Adversarial Machine Learning from Industry and Academia: A User-Study Approach
Vishruti Kakkad, Paul Chung, Hanan Hibshi +1
An exponential growth of Machine Learning and its Generative AI applications brings with it significant security challenges, often referred to as Adversarial Machine Learning (AML)…
Evidence of Cognitive Biases in Capture-the-Flag Cybersecurity Competitions
Carolina Carreira, Anu Aggarwal, Alejandro Cuevas +3
Understanding how cognitive biases influence adversarial decision-making is essential for developing effective cyber defenses. Capture-the-Flag (CTF) competitions provide an ecolog…
A Mixed-Methods Study on the Implications of Unsafe Rust for Interoperation, Encapsulation, and Tooling
Ian McCormack, Tomas Dougan, Sam Estep +3
The Rust programming language restricts aliasing to provide static safety guarantees. However, in certain situations, developers need to bypass these guarantees by using a set of u…
Observations From an Online Security Competition and Its Implications on Crowdsourced Security
Alejandro Cuevas, Emma Hogan, Hanan Hibshi +1
The crowd sourced security industry, particularly bug bounty programs, has grown dramatically over the past years and has become the main source of software security reviews for ma…
Ask the Experts: What Should Be on an IoT Privacy and Security Label?
Pardis Emami-Naeini, Yuvraj Agarwal, Lorrie Faith Cranor +1
Information about the privacy and security of Internet of Things (IoT) devices is not readily available to consumers who want to consider it before making purchase decisions. While…