Výsledky vyhledávání - "Nichols, Jeff A."

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Ferret-UI 2: Mastering Universal User Interface Understanding Across Platforms

Autor: Li, Zhangheng, You, Keen, Zhang, Haotian, Feng, Di, Agrawal, Harsh, Li, Xiujun, Moorthy, Mohana Prasad Sathya, Nichols, Jeff, Yang, Yinfei, Gan, Zhe

Building a generalist model for user interface (UI) understanding is challenging due to various foundational issues, such as platform diversity, resolution variation, and data limitation. In this paper, we introduce Ferret-UI 2, a multimodal large la

Externí odkaz: http://arxiv.org/abs/2410.18967

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Automated Code Fix Suggestions for Accessibility Issues in Mobile Apps

Autor: Mehralian, Forough, Barik, Titus, Nichols, Jeff, Swearngin, Amanda

Accessibility is crucial for inclusive app usability, yet developers often struggle to identify and fix app accessibility issues due to a lack of awareness, expertise, and inadequate tools. Current accessibility testing tools can identify accessibili

Externí odkaz: http://arxiv.org/abs/2408.03827

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AI ATAC 1: An Evaluation of Prominent Commercial Malware Detectors

Autor: Bridges, Robert A., Weber, Brian, Beaver, Justin M., Smith, Jared M., Verma, Miki E., Norem, Savannah, Spakes, Kevin, Watson, Cory, Nichols, Jeff A., Jewell, Brian, Iannacone, Michael. D., Stahl, Chelsey Dunivan, Huffer, Kelly M. T., Oesch, T. Sean

This work presents an evaluation of six prominent commercial endpoint malware detectors, a network malware detector, and a file-conviction algorithm from a cyber technology vendor. The evaluation was administered as the first of the Artificial Intell

Externí odkaz: http://arxiv.org/abs/2308.14835

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Testing SOAR Tools in Use

Autor: Bridges, Robert A., Rice, Ashley E., Oesch, Sean, Nichols, Jeff A., Watson, Cory, Spakes, Kevin, Norem, Savannah, Huettel, Mike, Jewell, Brian, Weber, Brian, Gannon, Connor, Bizovi, Olivia, Hollifield, Samuel C, Erwin, Samantha

Publikováno v: Computers & Security 2023

Modern security operation centers (SOCs) rely on operators and a tapestry of logging and alerting tools with large scale collection and query abilities. SOC investigations are tedious as they rely on manual efforts to query diverse data sources, over

Externí odkaz: http://arxiv.org/abs/2208.06075

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Screen Parsing: Towards Reverse Engineering of UI Models from Screenshots

Autor: Wu, Jason, Zhang, Xiaoyi, Nichols, Jeff, Bigham, Jeffrey P.

Automated understanding of user interfaces (UIs) from their pixels can improve accessibility, enable task automation, and facilitate interface design without relying on developers to comprehensively provide metadata. A first step is to infer what UI

Externí odkaz: http://arxiv.org/abs/2109.08763

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Beyond the Hype: A Real-World Evaluation of the Impact and Cost of Machine Learning-Based Malware Detection

Autor: Bridges, Robert A., Oesch, Sean, Verma, Miki E., Iannacone, Michael D., Huffer, Kelly M. T., Jewell, Brian, Nichols, Jeff A., Weber, Brian, Beaver, Justin M., Smith, Jared M., Scofield, Daniel, Miles, Craig, Plummer, Thomas, Daniell, Mark, Tall, Anne M.

Publikováno v: Digital Threats: Research and Practice 2023

In this paper, we present a scientific evaluation of four prominent malware detection tools to assist an organization with two primary questions: To what extent do ML-based tools accurately classify previously- and never-before-seen files? Is it wort

Externí odkaz: http://arxiv.org/abs/2012.09214

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