Artifical Intelligence in Cryptography: Protection of Cryptographic System under Patents

Artificial Intelligence (AI) is transforming cryptographic approaches to encryption techniques, automating key generation, and strengthening safety mechanisms against cyber threats. Possible applications include strengthening data protection, detecting vulnerabilities, and optimizing cryptographic protocols. In particular, AI-based cryptographic models enhance the non- disable for security systems against advanced assaults, including those posed by quantum computing. Cryptography leverages AI through machine learning algorithms for anomaly detection, AI-based key management, and neural network-based encryption techniques. Basically, these advancements allow for adaptive security frameworks that can recognize and take action against potential breaches in real time. AI-assisted cryptanalysis can also be used to assess the strength of encryption, therefore restructuring cryptographic practices. Legal protection for AI-driven cryptographic solutions under intellectual property laws, particularly the Patents Act, will remain a crucial area of concern as they continue to evolve. Patentability in cryptography has faced challenges because it relies on mathematical algorithms, which are often not considered patentable in many jurisdictions. However, when technical applications, such as higher efficiency or enhanced security, can be demonstrated by AI-based cryptographic methods, they may find a place under the patent-protectable framework. Novelty, inventive step, and industrial applicability are three of the criteria AI innovations in cryptography must satisfy under the laws of patents, which include the Indian Patents Act, 1970, and European Patent Convention (EPC). The patent framework for cryptography is now developing, with courts and regulatory authorities analyzing the degree of protection that should be accorded to cryptographic mechanisms arising from AI. The paper analyses how AI and cryptography intersect regarding patentability in AI-powered cryptographic systems and the challenges posed by the existing intellectual property frameworks.