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

下一代资源受限通信系统的自适应多目标优化框架

• 批准号: RGPIN-2017-06525
• 负责人: Sedaghat, Reza
• 金额: $ 1.75万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=679542
• 关键词: Adaptive; Multi; Objective; Optimization; Framework

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.******

在接下来的五年中，全球IP网络将为多达100亿个新的设备和连接提供支持，从2016年的163亿增加到2020年底的363亿。2020年以后的5G通信网络和服务环境需要应付物联网中数十亿个小型设备（IoT）（IoT）（IoT）和数十亿个重型数据消费者。 5G网络基础架构将不得不提供多方面的安全姿势，以减轻所有设备，所有网络域以及所有托管的所有应用程序的新威胁，恶意攻击以及不断发展的漏洞。它必须是一个无缝的基础架构，满足每个人的安全通信需求，并整合新的无线电概念，例如大型MIMO，超密集的网络，移动的网络以及设备对设备，超级可靠和大规模的机器通信。用于通信安全的下一代约束求解器已成为一项重要的科学学科，许多多方面的复杂性值得跨学科工程社区的关注和协同作用。 无线和有线网络基础架构都不仅要在其容量方面具有高度扩展性，而且还需要最佳地处理各种安全垂直行业的不同服务需求。运输当事方之间数据的安全方法至关重要，并且涉及成本和效率之间的权衡。解决此权衡的方法是使用优化方法分析加密协议，以进行安全数据通信。但是，这些优化方法不得导致该过程的安全水平大大降低。为了在安全要求的成本，效率和可靠性之间实现多目标权衡取舍，我们的研究包括与Benson基于算法的加密技术有关的方法，基于子渗透的基于子渗透的进化密钥交换，二进制粒子粒子的二进制粒子群的优化，用于密码膨胀的膨胀型密封性驱动因素等。 等级。 每个安全的通信系统都会列出功能安全级别的集合，从而确保整个系统的保密。我们提出的研究封装了新的优化方法，该方法将实施，以开发高级多目标技术，用于有效设计加密通信协议，并应对安全，成本和绩效因素之间的权衡。在这项研究中，我们将开发理论和应用的技术和算法，用于制定通信安全管理和政策。******