Integrating Quantum Computing with AI for Advanced Cryptographic Security

Lingala Thirupathi, Balla Akshaya, Pagadala Charvi Reddy +2 more

Rapid advances in artificial intelligence (AI) and quantum computing can potentially transform cybersecurity. It explores the synergistic integration to improve cyber defenses. The ability of AI to analyze data, detect anomalies, and perform predictive analytics, combined with the potential of quantum computing to solve complex cryptographic problems, provides a strong framework for today's cybersecurity challenges. Using quantum algorithms and machine learning techniques, it aims to strengthen cryptographic methods, optimize threat detection systems, and develop flexible defense protocols against sophisticated cyber attacks. The study also examines the implications of quantum cryptography and the role of AI in managing quantum-generated data It discusses the challenges and ethical considerations associated with applying these advanced technologies in cybersecurity infrastructures. The findings suggest that the convergence of AI and quantum computing can significantly improve the effectiveness and adaptability of cybersecurity measures, paving the way for a secure digital future.

Utpal Chakraborty

Pradeepkumar, S. Sheik Mydeen, Muhamed Fallahhusein +3 more

Artificial Intelligence (AI) combined with Bio-Quantum Computing is a revolutionary method of improving data security and encryption in virtual environments. Through the use of quantum mechanics and AI-optimized optimization, this combination strengthens cryptographic methods against future cyber threats. Current encryption algorithms like RSA and AES are vulnerable due to the advancement of Bio-Quantum Computing, which can decrypt conventional cryptographic algorithms. Additionally, traditional security systems are not able to adapt in real-time to advanced cyber-attacks. To meet these demands, the suggested framework combines AI with Quantum Key Distribution (AI -QKD). The QKD provides unbreakable key exchange cryptography using quantum properties, whereas AI optimizes encryption protocols in real time through threat analysis, providing heightened security resilience. This technique is used in virtual world transaction security, identity authentication, and secret communications. The AI-based mechanism flexibly adjusts encryption parameters in real time, preventing quantum attacks and increasing the integrity of the overall data. Findings reveal that the new approach enhances the robustness of encryption immensely, lowers risks of key compromise, and makes virtual interactions secure. The fusion of AI and QKD reflects high adaptability, making the encryption systems quantum-resistant and future-proof. The new approach achieves the data integrity by 98.70%, key compromise risks by 45.31%, adaptability by 97.63%.

Ankit Gupta, Shilpi Mittal

Manik Rakhra, Tiyas Sarkar, Gagandeep Singh Cheema

The convergence of blockchain technology and quantum-resistant artificial intelligence (AI) frameworks marks a significant advancement in cybersecurity. A blockchain-powered framework for quantum defensive AI aims to create robust, tamper-proof AI systems capable of withstanding the emerging threats posed by quantum computing. As quantum computers have the potential to break conventional cryptographic algorithms, integrating quantum-resistant cryptographic methods within a blockchain ensures data integrity and security. Due to being decentralized, blockchain makes it possible to see a ledger that is impossible to alter, which is required for monitoring AI actions and securing AI-powered applications. Here, blockchain is used so that data and models can be verified, their updates are secure, and everything can be audited. Machine learning is introduced to blockchain security to ensure that it remains protected from future quantum-style hacking attempts. Because of this integration, AI systems will be more secure, and the blockchain infrastructure will be better able to resist any future threats brought by quantum computers. It has been revealed by using blockchain technology with period defensive AI that both traditional and post-quantum transactions become more abundant with the passage of time. Out of every five transactions performed per second on a post-quantum computer, at least four utilize quantum principles and operate with much higher efficiency. This research is necessary to speed up the handling of transactions that need rapid attention. The choice of using a hybrid approach is sure to initiate a time when AI is highly secure and transparent, and it will be crucial in areas such as finance, healthcare, and the security of nations. Using these advanced technologies, it ensures that AI applications can remain stable against cyber threats that may exist in the future.

Petar Radanliev