[HTML][HTML] Adversarial machine learning in industry: A systematic literature review
Abstract Adversarial Machine Learning (AML) discusses the act of attacking and defending
Machine Learning (ML) Models, an essential building block of Artificial Intelligence (AI). ML …
Machine Learning (ML) Models, an essential building block of Artificial Intelligence (AI). ML …
Everyone for themselves? a qualitative study about individual security setups of open source software contributors
To increase open-source software supply chain security, protecting the development
environment of contributors against attacks is crucial. For example, contributors must protect …
environment of contributors against attacks is crucial. For example, contributors must protect …
Engaging Company Developers in Security Research Studies: A Comprehensive Literature Review and Quantitative Survey
Previous research demonstrated that company developers excel compared to freelancers
and computer science students, with the corporate environment significantly influencing …
and computer science students, with the corporate environment significantly influencing …
It's like flossing your teeth: On the importance and challenges of reproducible builds for software supply chain security
The 2020 Solarwinds attack was a tipping point that caused a heightened awareness about
the security of the software supply chain and in particular the large amount of trust placed in …
the security of the software supply chain and in particular the large amount of trust placed in …
Everybody's got ML, tell me what else you have: Practitioners' perception of ML-based security tools and explanations
Significant efforts have been investigated to develop machine learning (ML) based tools to
support security operations. However, they still face key challenges in practice. A generally …
support security operations. However, they still face key challenges in practice. A generally …
A method to facilitate membership inference attacks in deep learning models
Z Chen, K Pattabiraman - arXiv preprint arXiv:2407.01919, 2024 - arxiv.org
Modern machine learning (ML) ecosystems offer a surging number of ML frameworks and
code repositories that can greatly facilitate the development of ML models. Today, even …
code repositories that can greatly facilitate the development of ML models. Today, even …
FDI: Attack Neural Code Generation Systems through User Feedback Channel
Neural code generation systems have recently attracted increasing attention to improve
developer productivity and speed up software development. Typically, these systems …
developer productivity and speed up software development. Typically, these systems …
Architectural neural backdoors from first principles
While previous research backdoored neural networks by changing their parameters, recent
work uncovered a more insidious threat: backdoors embedded within the definition of the …
work uncovered a more insidious threat: backdoors embedded within the definition of the …
Skipping the Security Side Quests: A Qualitative Study on Security Practices and Challenges in Game Development
The video game market is one of the biggest for software products. Video game
development has progressed in the last decades to complex and multifaceted endeavors …
development has progressed in the last decades to complex and multifaceted endeavors …
Interdisciplinary Approaches to Cybervulnerability Impact Assessment for Energy Critical Infrastructure
As energy infrastructure becomes more interconnected, understanding cybersecurity risks to
production systems requires integrating operational and computer security knowledge. We …
production systems requires integrating operational and computer security knowledge. We …