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The fifth generation (5G) technology is expected to allow connectivity to billions of devices, known as Internet of Things (IoT). However, IoT devices will inevitably be the main target of various cyberattack types. The most common one is known as distributed denial‐of‐service (DDoS) attack. In order to mitigate such attacks, network functions virt...
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With the deployment of billions of Internet of Things (IoT) devices, more and more cyber attacks involving or even targeting such devices are rife. Cyberattack vectors are in constant evolvement in terms of diversity and complexity. Thus, to detect novel cyberattacks, we use anomaly-based techniques which model the expected behavior of the IoT devi...
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... (4) Realize dimension reduction feature processing of automatic encoder. The automatic encoder completes the dimensionality reduction processing by inputting and outputting the reconstruction error of the security attack behavior characteristics [34][35][36]. After determining its dimensionality reduction objective function, it further iterates and updates the weights with the help of the gradient descent method to realize the dimensionality reduction processing of the security attack behavior characteristics of air traffic control network. ...
... Software-defined networks (SDN) are one of the most important enabling key technologies for 5G networks to meet the user's demands [1]. It has been develop to overcome many problems one of them being spectrum scarcity due to fix allocation and emerging technologies [2]. ...
The previous method that has been suggested is to increase the automatic closing of security holes in networks that are vulnerable. This process is the amalgamation of various phases, which begin with collecting information and end with mitigating vulnerabilities. The network's internal domain name is considered input in the proposed method for internal audit purposes. The operational services collect live IPs. Exploits are typically created to gain access to a system, enable the acquisition of administrative privileges, or launch denial-of-service attacks. Each exploit is configured and executed after the list of exploits for each service has been obtained. Whether the endeavor can effectively approach the framework, the moderation step is conjured, checking the sort of access got. The suggestion evaluates the incoming data using the knowledge set stored in its memory. It maintains a table detailing the IP address incomings. The guilty detection is increased by 27.6%, and the security is increased by 36.8% compared to previous work.
The roll out of the deployment of the 5G technology has been ongoing globally. The deployment of the technologies associated with 5G has seen mixed reaction as regards its prospects to improve communication services in all spares of life amid its security concerns. The security concerns of 5G network lies in its architecture and other technologies that optimize the performance of its architecture. There are many fractions of 5G security architecture in the literature, a holistic security architectural structure will go a long way in tackling the security challenges. In this paper, the review of the security challenges of the 5G technology based on its architecture is presented along with their proposed solutions. This review was carried out with some keywords relating to 5G securities and architecture; this was used to retrieve appropriate literature for fitness of purpose. The 5G security architectures are majorly centered around the seven network security layers; thereby making each of the layers a source of security concern on the 5G network. Many of the 5G security challenges are related to authentication and authorization such as denial-of-service attacks, man in the middle attack and eavesdropping. Different methods both hardware (Unmanned Aerial Vehicles, field programmable logic arrays) and software (Artificial intelligence, Machine learning, Blockchain, Statistical Process Control) has been proposed for mitigating the threats. Other technologies applicable to 5G security concerns includes: Multi-radio access technology, smart-grid network and light fidelity. The implementation of these solutions should be reviewed on a timely basis because of the dynamic nature of threats which will greatly reduce the occurrence of security attacks on the 5G network.
There has been a dramatic expansion in the number and frequency of relationships between entities in mobile telecommunications networks over the last several years. For these interactions to be profitable, the parties involved must be able to count on one another. Since mobile networks require trust and reputation models to create feasible communications in 5 G and beyond networks, a collection of entities can create chains of operations between cross-operators with privacy and trustworthiness through mobile telecommunication network models. A major impediment to widespread communication beyond 5 G networks is the absence of automated, efficient, and scalable models for creating security and trust. Multitenancy and active infrastructure sharing will be major facilitators of new business models as 5 G networks expand. New security concerns are emerging due to these new opportunities, which is one of the primary obstacles for the mass implementation of 5 G networks. There are several ways in which attackers might use 5G-enabled situations to undertake lateral moves and disrupt 5 G services and infrastructure resources. Existing trust and security models cannot deal with the dynamic nature of the 5 G infrastructural threats or the multi-tenant security issues. Hence, we propose a Mobile Node Trust Factor Linked Privacy Preservation model for 5 G multi-stage authentication models in this work. A threat model for multi-stage authentication scenarios in an underlying 5 G network infrastructure is used to demonstrate how this model can be used. For secure end-to-end communication, authorization and strong authentication are necessary. A combination of anonymous authentication and authorization is needed to preserve the privacy of mobile devices which share personal information. The proposed model is compared with the traditional models and the proposed model results exhibit better performance.
Fifth-generation (5G) technology will play a vital role in future wireless networks. The breakthrough 5G technology will unleash a massive Internet of Everything (IoE), where billions of connected devices, people, and processes will be simultaneously served. The services provided by 5G include several use cases enabled by the enhanced mobile broadband, massive machine-type communications, and ultra-reliable low-latency communication. Fifth-generation networks potentially merge multiple networks on a single platform, providing a landscape for seamless connectivity, particularly for high-mobility devices. With their enhanced speed, 5G networks are prone to various research challenges. In this context, we provide a comprehensive survey on 5G technologies that emphasize machine learning-based solutions to cope with existing and future challenges. First, we discuss 5G network architecture and outline the key performance indicators compared to the previous and upcoming network generations. Second, we discuss next-generation wireless networks and their characteristics, applications, and use cases for fast connectivity to billions of devices. Then, we confer physical layer services, functions, and issues that decrease the signal quality. We also present studies on 5G network technologies, 5G propelling trends, and architectures that help to achieve the goals of 5G. Moreover, we discuss signaling techniques for 5G massive multiple-input and multiple-output and beam-forming techniques to enhance data rates with efficient spectrum sharing. Further, we review security and privacy concerns in 5G and standard bodies’ actionable recommendations for policy makers. Finally, we also discuss emerging challenges and future directions.
Nowadays, Wireless Sensor Networks (WSNs) are facing various challenges. Cost efficiency, low energy consumption, reliable data communication between nodes and security are the major challenges in the field of WSNs. On the other hand, blockchain is also a very hot domain in this era. Blockchain has a remedy for some challenges, which are faced by the WSNs, e.g., secure data transactions and trustworthiness, etc. By keeping in mind the security issues, we induce blockchain into the WSNs. In short, we have proposed a trust model to avoid the malicious attacks and keep the transact data using the blockchain property of immutability. Moreover, an enhanced version of Proof of Stack (PoS), i.e., the Proof of Authority (PoA) consensus mechanism is being used to add a new node in the network. Additionally, the smart contract is also written to check the working status of nodes. Simulations are performed in order to record the transaction cost and execution cost.
