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  "author": "Peter Bajcsy",
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  "author": "Peter Bajcsy",
            
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  "author_email": "",
            
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  "citation": [],
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  "citation": [],
            
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  "defined_in": "https://doi.org/10.48550/arXiv.2405.13217",
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  "defined_in": "https://doi.org/10.48550/arXiv.2405.13217",
            
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  "doi": "10.57702/3rtxxahf",
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  "doi": "10.57702/3rtxxahf",
            
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  "doi_date_published": null,
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  "doi_date_published": "2025-01-03",
            
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  "extra_authors": [
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  "extra_authors": [
            
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    {
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    {
            
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      "extra_author": "Maxime Bros",
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      "extra_author": "Maxime Bros",
            
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      "orcid": ""
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      "orcid": ""
            
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      "description": "",
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      "display_name": "Artificial Intelligence",
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      "name": "artificial-intelligence",
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      "name": "artificial-intelligence",
            
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      "title": "Artificial Intelligence"
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      "title": "Artificial Intelligence"
            
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    },
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    },
            
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    {
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    {
            
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      "description": "",
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      "description": "",
            
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      "display_name": "Neural Networks",
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      "display_name": "Neural Networks",
            
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      "name": "neural-networks",
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      "name": "neural-networks",
            
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      "title": "Neural Networks"
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      "title": "Neural Networks"
            
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  "landing_page": "https://pages.nist.gov/nn-calculator",
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  "landing_page": "https://pages.nist.gov/nn-calculator",
            
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  "license_title": null,
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  "metadata_modified": "2025-01-03T00:25:46.408792",
            
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  "name": "interactive-simulations-of-backdoors-in-neural-networks",
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  "name": "interactive-simulations-of-backdoors-in-neural-networks",
            
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  "notes": "This work addresses the problem of planting and defending 
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  "notes": "This work addresses the problem of planting and defending 
            
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cryptographic-based backdoors in artificial intelligence (AI) models. 
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cryptographic-based backdoors in artificial intelligence (AI) models. 
            
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The motivation comes from our lack of understanding and the 
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The motivation comes from our lack of understanding and the 
            
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implications of using cryptographic techniques for planting 
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implications of using cryptographic techniques for planting 
            
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undetectable backdoors under theoretical assumptions in the large AI 
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undetectable backdoors under theoretical assumptions in the large AI 
            
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model systems deployed in practice. Our approach is based on designing 
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model systems deployed in practice. Our approach is based on designing 
            
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a web-based simulation playground that enables planting, activating, 
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a web-based simulation playground that enables planting, activating, 
            
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and defending cryptographic backdoors in neural networks (NN). 
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and defending cryptographic backdoors in neural networks (NN). 
            
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Simulations of planting and activating backdoors are enabled for two 
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Simulations of planting and activating backdoors are enabled for two 
            
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scenarios: in the extension of NN model architecture to support 
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scenarios: in the extension of NN model architecture to support 
            
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digital signature verification and in the modified architectural block 
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digital signature verification and in the modified architectural block 
            
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for non-linear operators. Simulations of backdoor defense against 
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for non-linear operators. Simulations of backdoor defense against 
            
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backdoors are available based on proximity analysis and provide a 
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backdoors are available based on proximity analysis and provide a 
            
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playground for a game of planting and defending against backdoors. The 
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playground for a game of planting and defending against backdoors. The 
            
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simulations are available at https://pages.nist.gov/nn-calculator",
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simulations are available at https://pages.nist.gov/nn-calculator",
            
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  "title": "Interactive Simulations of Backdoors in Neural Networks",
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  "title": "Interactive Simulations of Backdoors in Neural Networks",
            
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}