Convolutional neural network designed as small truth tables, application to cryptography, formal verification & explainability

• المؤلف الرئيسي: Benamira, Adrien
• مؤلفون آخرون: Thomas Peyrin
• التنسيق: Thesis-Doctor of Philosophy
• اللغة: English
• منشور في: Nanyang Technological University 2024
• الموضوعات: Computer and Information Science; Mathematical Sciences; Deep convolutional neural network; Machine/deep learning; Cryptanalysis; Neural distinguisher; Exact global xplainability; Side-channel attacks; Fully homomorphic encryption
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/177203

DCNNs have revolutionized machine learning (ML) and deep learning (DL), achieving remarkable success in image recognition, natural language processing, and other domains. However, their deployment in security-critical industries such as cybersecurity, energy, finance, and the military faces persiste...