Search Results for robust

  • Publication

    Robust Object Classification via Part-Based Models

    Abstract Robustness becomes one of the most desired properties in machine learning (ML) models due to their increasing adoption in safety/security-sensitive settings. Most attempts to train robust methods…

  • Publication

    Novel Metrics for Robust Machine Learning

    Abstract Although deep neural networks (DNNs) have achieved impressive performance in several applications, they also exhibit several well-known sensitivities and security concerns that can emerge for a variety…

  • Publication

    Adversarially Robust Machine Learning

    Machine learning provides valuable methodologies for detecting and protecting against security attacks at scale. However, a machine-learning algorithm used for security is different from other domains because in…

  • Publication

    Robust Machine Learning via Random Transformation

    Abstract Current machine learning models suffer from evasion attacks such as adversarial examples. This introduces security and safety concerns that lack any clear solution. Recently, the usage of…

  • Publication

    Robust Access in Hostile Networks

    Our research is about providing safe access to the Internet in places where network access is restricted or censored. Many people are limited in what they can say…

  • Publication

    Secure Machine Learning for Adversarial Environments

    We plan to build a pipeline that leverages novel robust secure machine learning techniques to detect and defeat cybersecurity threats against computer systems. Modern cyber-threats to computer systems…

  • Publication

    An Interpretability Study of LLMs for Code Security

    Large language models (LLMs) such as ChatGPT have greatly advanced coding tasks but often fail to generate secure code. Current approaches to improving code security, relying on fine-tuning,…

  • Publication

    Secure Machine Learning

    We will study how to harden machine learning classifiers against adversarial attack. We will explore general mechanisms for making deep-learning classifiers more robust against attack, with a special…

  • Page

    CLTC Industry Collaborators

    The Center for Long-Term Cybersecurity has had robust engagement with a wide range of supporters, including industry collaborators, since our founding in 2015. In 2023 we have scoped…

  • Event

    CLTC Seminar: “Complexity and Security: Managing the Tradeoffs” with Herb Lin

    A review of current trends in technology innovation suggests that societal demands for increased functionality conflict with the imperatives of robust cybersecurity. Articulating the nature of this tradeoff is a useful first step (and is the focus of much of this talk), but an understanding of how to manage…

  • Publication

    Cyber Resilience and Social Equity: Twin Pillars of a Sustainable Energy Future

    A report published by the Center for Long-Term Cybersecurity, Cyber Resilience and Social Equity: Twin Pillars of a Sustainable Energy Future, examines the importance of cybersecurity in ensuring equitable access to energy. In an era of worsening cybersecurity threats, the paper advocates for “sustainable energy delivery systems that ensure robust defenses without compromising the goals of reducing energy poverty and ensuring energy security.”