An Adaptive Multi Objective Optimization Framework for Next Generation Resource Constrained Communication systems

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Over the next five years, global IP networks will support up to 10 billion new devices and connections, increasing from 16.3 billion in 2016 to 36.3 billion by the end of 2020. The 5G communication network and service environment beyond 2020 need to cope with billions of small devices in the Internet of Things (IoT), and billions of heavy data consumers. The 5G network infrastructure will have to provide a multi-faceted security posture that mitigates new threats, malicious attacks, and evolving vulnerabilities across all devices, all network domains, and all applications wherever they are hosted. It will have to be a seamless infrastructure satisfying everyone's secure communication needs reliably as well as integrating new radio concepts, such as massive MIMO, ultra-dense networks, moving networks, and device-to-device, ultra-reliable, and massive machine communications. Next-generation constraint solvers for communications security has emerged as an important scientific discipline where many multifaceted complexities deserve the attention and synergy of interdisciplinary engineering communities. Both wireless and wireline network infrastructure are required not only to be highly scalable in terms of their capacity, but also to optimally handle different service needs of various security verticals. Security methodologies employed in transporting data between parties are crucial and involve a trade-off between cost and efficiency. A solution to this trade-off is to analyze cryptographic protocols using optimization methods for secure data communication. However, these optimization methodologies must not result in significant reduction of security level of the process. To achieve a multi-objective trade-off between cost, efficiency and reliability of security requirements, our research includes methods related to Benson’s algorithm-based cryptographic techniques, Sub-permutation-based evolutionary key exchange, Binary particle swarm optimization for cipher method, Custom inflate-deflate cipher systems, etc. A crucial driving factor in many secure network fields (e.g. e-banking, e-trust, e-health etc.) is the threat level. Every secure communication system presents a collection of functional security levels, which guarantee the secrecy of the overall system. Our proposed research encapsulates new optimization approaches, which will be implemented to develop advanced multi-objective techniques for the efficient design of cryptographic communication protocols and to cope with the trade-offs between security, cost, and performance factors. In this research, we will develop techniques and algorithms, both theoretical and applied, for developing communication security management and policies.