ОПТИМІЗАЦІЇ РЕЗЕРВУ ОБЛАДНАННЯ ДЛЯ ІНТЕЛЕКТУАЛЬНИХ АВТОМАТИЗОВАНИХ СИСТЕМ

Algorithms for a neural network analyzer involved in the decision support system (DSS) during the selection of the composition of backup equipment (CBE) for intelligent automated control systems Smart City are proposed. A model, algorithms and software have been developed for solving the optimization problem of choosing a CBE capable of ensuring the uninterrupted operation of the IACS both in conditions of technological failures and in conditions of destructive interference in the operation of the IACS by the attackers. The proposed solutions help to reduce the cost of determining the optimal CBE for IACS by 15–17% in comparison with the results of known calculation methods. The results of computational experiments to study the degree of influence of the outputs of the neural network analyzer on the efficiency of the functioning of the CBE for IACS are presented.Запропоновано алгоритми для нейромережевого аналізатора, задіяного у системі підтримки прийняття рішень (СППР) у ході вибору складу резервного обладнання (СРО) для інтелектуальних автоматизованих систем управління (ІАСУ) Smart City. Розроблено модель, алгоритми та відповідне програмне забезпечення для вирішення оптимізаційного завдання вибору СРО, здатного забезпечити безперебійну роботу ІАСУ як в умовах технологічних збоїв, так і в умовах деструктивного втручання у роботу ІАСУ з боку атакуючих. Запропоновані рішення сприяють скороченню витрат на визначення оптимального СРО для ІАС на 15–17% порівняно з результатами відомих методів розрахунку. Наведено результати обчислювальних експериментів для вивчення ступеня впливу кількості виходів нейромережевого аналізатора на ефективність функціонування СРО для ІАС

Lightweight Cryptography based Communication Model for Device Identification, Mutual Authentication, and Encryption in a Smart City Environment

Providing security to smart city networks is one of the challenging and demanding tasks in the present days, due to its increased utilization in smart intelligent transportation systems. For this purpose, there are various security protocols and mechanisms that have been developed in the existing works, which targets to establish the reliable and secured communication in smart city networks. However, it limits the major issues of increased computational cost, communication cost, storage overhead, and reduced efficiency. In order to solve these problems, the proposed work intends to design an intelligent security framework by using the Light-weight Cryptography based Communication Model (LCCM). Proposed framework includes the modules of setup initialization, vehicle registration, authentication, key generation, encryption, and decryption. Here, the Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications are performed with reduced cost complexity. For guaranteeing the security of networks, the random value-based key generation, data encryption, and decryption processes are performed. During the performance analysis, various evaluation measures have been used to assess the results of both convention and proposed security protocols. This paper presented a new methodology named as, LCCM for enhancing the security of smart city transportation networks

Novel authentication framework for securing communication in internet-of-things

Internet-of-Things (IoT) offers a big boon towards a massive network of connected devices and is considered to offer coverage to an exponential number of the smart appliance in the very near future. Owing to the nascent stage of evolution of IoT, it is shrouded by security loopholes because of various reasons. Review of existing research-based solution highlights the usage of conventional cryptographic-based solution over the traditional mechanism of data forwarding process between IoT nodes and gateway. The proposed system presents a novel solution to this problem by a model that is capable of performing a highly secured and cost-effective authentication process. The proposed system introduces Authentication Using Signature (AUS) as well as Security with Complexity Reduction (SCR) for the purpose to resist participation of any form of unknown threats. The outcome of the model shows better security strength with faster response time and energy saving of the IoT nodes

Enhancing Information Security via Physical Layer Approaches in Heterogeneous IoT With Multiple Access Mobile Edge Computing in Smart City

Heterogeneous Internet of Things (IoT) and multi-access mobile edge computing (MA-MEC) are believed as supporting technologies for building a smart city. The advancement and flourish of IoT are facilitating the entry of human society into the Internet of Everything era, which lay the foundation of the smart city. To address the conflict between computation capability and low-cost mobile devices in IoT, the MA-MEC is available for supporting the resource-limited and computation-sensitive services and applications by computation offloading and distributed content delivery/caching. However, deploying cloud computing capability within the radio access network may face serious security threats, which stem from not only the existing technologies and networks but also the MA-MEC-based IoT itself. Therefore, in this paper, the solutions to address the security threats are investigated from physical layer perspectives, since physical layer security technologies have the advantages of achieving perfect secrecy, low-computational complexity, and resource consumption, and good adaptation for channel changes. Specifically, we investigate the secure wiretap coding, resource allocation, signal processing, and multi-node cooperation, along with physical layer key generation and authentication, to cope with the emerging security challenges. Finally, the paper is concluded with some possible future research directions

A review on green caching strategies for next generation communication networks

© 2020 IEEE. In recent years, the ever-increasing demand for networking resources and energy, fueled by the unprecedented upsurge in Internet traffic, has been a cause for concern for many service providers. Content caching, which serves user requests locally, is deemed to be an enabling technology in addressing the challenges offered by the phenomenal growth in Internet traffic. Conventionally, content caching is considered as a viable solution to alleviate the backhaul pressure. However, recently, many studies have reported energy cost reductions contributed by content caching in cache-equipped networks. The hypothesis is that caching shortens content delivery distance and eventually achieves significant reduction in transmission energy consumption. This has motivated us to conduct this study and in this article, a comprehensive survey of the state-of-the-art green caching techniques is provided. This review paper extensively discusses contributions of the existing studies on green caching. In addition, the study explores different cache-equipped network types, solution methods, and application scenarios. We categorically present that the optimal selection of the caching nodes, smart resource management, popular content selection, and renewable energy integration can substantially improve energy efficiency of the cache-equipped systems. In addition, based on the comprehensive analysis, we also highlight some potential research ideas relevant to green content caching