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1 |
Intelligent authentication of 5G healthcare devices: A survey
احراز هویت هوشمند دستگاه های مراقبت بهداشتی 5G: یک مرور-2022 The dynamic nature of wireless links and the mobility of devices connected to the Internet of
Things (IoT) over fifth-generation (5G) networks (IoT-5G), on the one hand, empowers pervasive
healthcare applications. On the other hand, it allows eavesdroppers and other illegitimate
actors to access secret information. Due to the poor time efficiency and high computational
complexity of conventional cryptographic methods and the heterogeneous technologies used,
it is easy to compromise the authentication of lightweight wearable and healthcare devices.
Therefore, intelligent authentication, which relies on artificial intelligence (AI), and sufficient
network resources are extremely important for securing healthcare devices connected to IoT-
5G. This survey considers intelligent authentication and includes a comprehensive overview of
intelligent authentication mechanisms for securing IoT-5G devices deployed in the healthcare
domain. First, it presents a detailed, thoughtful, and state-of-the-art review of IoT-5G, healthcare
technologies, tools, applications, research trends, challenges, opportunities, and solutions. We
selected 20 technical articles from those surveyed based on their strong overlaps with IoT,
5G, healthcare, device authentication, and AI. Second, IoT-5G device authentication, radiofrequency fingerprinting, and mutual authentication are reviewed, characterized, clustered,
and classified. Third, the review envisions that AI can be used to integrate the attributes
of the physical layer and 5G networks to empower intelligent healthcare devices. Moreover,
methods for developing intelligent authentication models using AI are presented. Finally, the
future outlook and recommendations are introduced for IoT-5G healthcare applications, and
recommendations for further research are presented as well. The remarkable contributions and
relevance of this survey may assist the research community in understanding the research gaps
and the research opportunities relating to the intelligent authentication of IoT-5G healthcare
devices.
keywords: اینترنت اشیا (IoT) | امنیت اینترنت اشیا | احراز هویت دستگاه | هوش مصنوعی | امنیت مراقبت های بهداشتی | شبکه های 5g | InternetofThings(IoT) | InternetofThingssecurity | Deviceauthentication | Artificialintelligence | Healthcaresecurity | 5Gnetworks |
مقاله انگلیسی |
2 |
Securing wireless communications from the perspective of physical layer: A survey
ایمن سازی ارتباطات بی سیم از دیدگاه لایه فیزیکی: یک مرور-2022 Ultra-reliability low-latency communication (uRLLC) is a new service category of the fifthgeneration (5G) mobile wireless networks, also plays a crucial role in the sixth-generation (6G)
networks. Given the openness of the wireless environment, the security and confidentiality of
uRLLC are of utmost important. Since traditional cryptography methods often feature significant
complex designs and processing delays, physical layer security (PLS) technologies exploiting the
inherent properties of the wireless medium have become a promising solution to secure wireless
communications. However, most existing PLS methods assume a finite block-length regime,
which cannot cater to uRLLC with short block-lengths. In this paper, the PLS technologies for
uRLLC were comprehensively investigated. First, we reviewed the typical characteristics of the
next-generation mobile networks and analyzed the threats faced by the physical layer. Then,
we introduced the traditional solutions and performance metrics of PLS with a finite blocklength regime. Furthermore, we discussed several physical layer technologies and observed their
influence on PLS. Additionally, this study also analyzed the impact of the unique characteristics
of 5G networks on communication securit, such as the mobility.
Keywords: uRLLC | Wireless networks | Security and confidentiality | PLS | Finite block-length |
مقاله انگلیسی |
3 |
5G network slice for digital real-time healthcare system powered by network data analytics
برش شبکه 5G برای سیستم دیجیتال مراقبت بهداشتی بلادرنگ طراحی شده توسط تجزیه و تحلیل داده های شبکه-2022 In the wake of the COVID-19 pandemic, where almost the entire global healthcare ecosystem struggled to handle
patients, it’s evident that the healthcare segment needs a virtual real-time digital support system. The recent
advancements in technology have enabled machine-to-machine communication, enhanced mobile broadband,
and real-time biometric data analytics. These could potentially fulfill the requirements of an end-to-end digital
healthcare system. For building such a system, there is also a need for a dedicated and specialized communication
network. Such a system will not only support dynamic throughput, latency and payload but also provide guaranteed QoS (Quality of Service) at every instant. The motive of our study was to define an implementable lowlevel architecture for the digital healthcare system by using the 5G Network Slice that incorporates all these
features. Best-in-class wearable devices will collect the biometric data and transmit it via the 5G network slice.
Data analytics is then applied to the collected data to build a knowledge graph used for quick predictions and
prescriptions. The architecture also keeps in mind the security and integrity aspects of healthcare data.
Keywords: 5G network slice | Slice dimensioning | Digital healthcare | Network data analytics framework | IoMT |
مقاله انگلیسی |
4 |
Novel Four-Layered Software Defined 5G Architecture for AI-based Load Balancing and QoS Provisioning
نرم افزار جدید چهار لایه معماری 5G تعریف شده برای تعادل بار مبتنی بر هوش مصنوعی و تأمین کیفیت QoS -2020 Software defined 5G network (SD-5G) is an evolving
networking technology. The integration of SDN and 5G brings
scalability, and efficiency. However, Quality of Service (QoS)
provision is still challenging in SD-5G due to improper load
balancing, traffic unawareness and so on. To overwhelm these
issues this paper designs a novel load balancing scheme using
Artificial Intelligence (AI) techniques. Firstly, novel fourlayered
SD-5G network is designed with user plane, smart data
plane, load balancing plane, and distributed control plane. In
the context to 5G, the data transmission rate must satisfy the
QoS constraints based on the traffic type such as text, audio,
video etc. Thus, the data from the user plane is classified by
Smart Traffic Analyzer in the data plane. For traffic analysis,
Enriched Neuro-Fuzzy (ENF) classifier is proposed. In the load
balancing plane, Primary Load balancer and Secondary Load
Balancer are deployed. This plane is responsible for balancing
the load among controllers. For controller load balancing,
switch migration is presented. Overloaded controller is
predicted by Entropy function. Then decision for migration is
made by Fitness-based Reinforcement Learning (F-RL)
algorithm. Finally, the four-layered SD-5G network is modeled
in the NS-3.26. The observations shows that the proposed work
improves the SD-5G network in terms of Loss Rate, Packet
Delivery Rate, Delay, and round trip time. Keywords: QoS | software defined 5G network | Artificial intelligence | distributed control plane |
مقاله انگلیسی |
5 |
On 5G network slice modelling: Service-, resource-, or deployment-driven?
در مدل سازی برش شبکه 5G: سرویس ، منابع یا استقرار محور؟-2020 Network slicing has been one of the hottest topics in standardization recently, as telecom operators are intensively investigating its usage for operating isolated and independently configurable logical networks, in order to ease and promote the network sharing and neutral hosting business. However, extensive deployments of slice management solutions are often impeded by incompatibilities of the used slice data models, which stem from different definitions and modelling approaches for the slicing concept, e.g., some driven by 3GPP standards, others by other standards or proprietary solutions, and so on. Although various studies on slicing have been performed, none of them has focused on slice data modelling across research and standards. Incompatible slice models do not only limit interoperability but they also reduce the efficiency of network slicing systems. This paper lays a foundation towards more efficient and interoperable network slice modelling by methodically investigating, categorizing, and formally describing core slice modelling approaches, including new modelling suggestions. Subsequently, we analyse their advantages and disadvantages and we propose slice model quality metrics, which we use for performing a case study on our testbed. Keywords: 5G | Slicing | NFV | Data modelling |
مقاله انگلیسی |
6 |
Mining and Utilization of Special Information for Archives Management Based on 5G Network and Internet of Things
استخراج و استفاده از اطلاعات ویژه برای مدیریت بایگانی بر اساس شبکه 5G و اینترنت اشیا-2020 5G technology is currently in the process of demographic data, data mining, the next-generation mobile networks are considered to be one of the main factors. Through research and data analysis, are expected to overcome the complexity of these networks, and it will be possible to carry out dynamic management and business operations. It is a trade item in that category, which is a particular file. Data collection chosen field of study is the core part. These files are considered to know how it organize their files and save them for future posterity. Finally, deal with digitized archive material; these traditional archives sought to highlight the problems faced by the digital age. Issues related to critical skills of a digitized archive of documents as extended support for mobile telephone networks, and can be considered the next generation of ultra-fast 5G network technology. 5G network includes all kinds of advanced technology, to provide excellent service. Therefore, new architecture and applications of new technology service management solutions should be advised to resolve reliability issues and ensure data transmission capacity, high data rates, and Quality of services (QoS). Cloud computing, networking, as well as software-defined network technology are some of the core networks 5G. Cloud-based service, providing flexible and efficient solutions for information and communication technologies by reducing the cost of the investment and management of information technology infrastructure. In terms of functionality are decoupled control and data planes to support programmability, flexibility and adaptability in a changing network architecture promising architecture. Keywords: Quality of services (QoS) | Internet of things (IoT) | Programmability | Flexibility | 5G network |
مقاله انگلیسی |
7 |
به سوی تقسیم بندی شبکه 5G برای شبکه های ادهاک خودرویی: یک رویکرد انتها به انتها
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 7 - تعداد صفحات فایل doc فارسی: 16 شبکه های 5G نه تنها از افزایش نرخ داده ها پشتیبانی می کنند، بکه همچنین می بایست زیرساخت مشترکی را فراهم کنند که براساس آن سرویس های جدید همراه با نیازمندی های بسیار متفاوت کیفیت سرویس (QoS) شبکه با تاخیر کمتر ارائه شود. به طور دقیق تر، کاربردهای شبکه های خودرویی چند منظوره (VANET) که اساساً گرایش آن ها به مسائل ایمنی و سرگرمی است (مانند پخش ویدیویی و مرورگر وب) در حال افزایش است. بیشتر این کاربردها دارای محدودیت های جدی از نظر تاخیر در حد چند میلی ثانیه هستند و نیاز به اطمینان پذیری بالایی دارند. پلتفورم نسل پنجم برای بررسی چنین نیازهایی نیازمند ایجاد شبکه های مجازی برنامه پذیر و راهکارهای مختلف ترافیکی همانند تقسیم بندی (برش) شبکه است. به این منظور در این مقاله یک مکانیزم تقسیم بندی پویا و برنامه پذیر انتها به انتها در شبکه LTE مبتنی بر M-CORD پیشنهاد می دهیم. یکی از ویژگی های کلیدی M-CORD که مکانیزم پیشنهاد تقسیم بندی شبکه از آن استفاده می کند، EPC مجازی است که سفارشی سازی و اصلاح را امکان پذیر می سازد. M-CORD کارکرد ضروری را برای برنامه ریزی تعاریف تقسیم بندی فراهم می کند که در آن مکانیزم پیشنهادی به طور کامل از رویکرد تعریف شده نرم افزاری خود پیروی می کند. علاوه بر این، ما نشان می دهیم که چگونه دستگاه ها انتهایی قرار گرفته در بخش های مختلف براساس QoS های متفاوت براساس نوع کاربر انتهایی تخصیص داده می شوند. این نتایج نشان می دهند که مکانیزم پیشنهادی تقسیم بندی شبکه بخش های مناسب را انتخاب می کند و منابع را به کاربران براساس نیازها و نوع سرویس آن ها اختصاص می دهد.
کلمات کلیدی: تقسیم بندی شبکه | نسل پنجم (5G) | M-CORD | LTE | NSSF | VANET |
مقاله ترجمه شده |
8 |
Multi-layered intrusion detection and prevention in the SDN/NFV enabled cloud of 5G networks using AI-based defense mechanisms
شناسایی و جلوگیری از نفوذ چند لایه در SDN / NFV ابر شبکه های 5G را با استفاده از مکانیسم های دفاعی مبتنی بر هوش مصنوعی فعال می کند-2020 Software defined networking (SDN), network function virtualization (NFV), and cloud computing are receiving significant attention in 5G networks. However, this attention creates a new challenge for security provisioning in these integrated technologies. Research in the field of SDN, NFV, cloud computing, and 5G has recently focused on the intrusion detection and prevention system (IDPS). Existing IDPS solutions are inadequate, which could cause large resource wastage and several security threats. To alleviate security issues, timely detection of an attacker is important. Thus, in this paper, we propose a novel approach that is referred to as multilayered intrusion detection and prevention (ML-IDP) in an SDN/NFV-enabled cloud of 5G networks. The proposed approach defends against security attacks using artificial intelligence (AI). In this paper, we employed five layers: data acquisition layer, switches layer, domain controllers (DC) layer, smart controller (SC) layer, and virtualization layer (NFV infrastructure). User authentication is held in the first layer using the Four-Q-Curve algorithm. To address the flow table overloading attack in the switches layer, the game theory approach, which is executed in the IDP agent, is proposed. The involvement of the IDP agent is to completely avoid a flow table overloading attack by a deep reinforcement learning algorithm, and thus, it updates the current state of all switches. In the DC layer, packets are processed and classified into two classes (normal and suspicious) by a Shannon Entropy function. Normal packets are forwarded to the cloud via the SC. Suspicious packets are sent to the VNF using a growing multiple self-organization map (GM-SOM). The proposed ML-IDP system is evaluated using NS3.26 for different security attacks, including IP Spoofing, flow table overloading, DDoS, Control Plane Saturation, and host location hijacking. From the experiment results, we proved that the ML-IDP with AI-based defense mechanisms effectively detects and prevents attacks. Keywords: SDN/NFV Cloud of 5G | Multilayered architecture | Intrusion detection and prevention | And artificial intelligence |
مقاله انگلیسی |
9 |
Intelligent handover decision scheme using double deep reinforcement learning
طرح تصمیم گیری واگذاری هوشمند با استفاده از یادگیری تقویتی عمیق دو برابر-2020 Handovers (HOs) have been envisioned to be more challenging in 5G networks due to the inclusion of
millimetre wave (mm-wave) frequencies, resulting in more intense base station (BS) deployments.
This, by its turn, increases the number of HOs taken due to smaller footprints of mm-wave BSs
thereby making HO management a more crucial task as reduced quality of service (QoS) and quality of
experience (QoE) along with higher signalling overhead are more likely with the growing number of
HOs. In this paper, we propose an offline scheme based on double deep reinforcement learning (DDRL)
to minimize the frequency of HOs in mm-wave networks, which subsequently mitigates the adverse
QoS. Due to continuous and substantial state spaces arising from the inherent characteristics of the
considered 5G environment, DDRL is preferred over conventional Q-learning algorithm. Furthermore,
in order to alleviate the negative impacts of online learning policies in terms of computational
costs, an offline learning framework is adopted in this study, a known trajectory is considered in
a simulation environment while ray-tracing is used to estimate channel characteristics. The number of
HO occurrence during the trajectory and the system throughput are taken as performance metrics. The
results obtained reveal that the proposed method largely outperform conventional and other artificial
intelligence (AI)-based models. Keywords: Double deep reinforcement learning | Handover management | Millimetre-wave communication |
مقاله انگلیسی |
10 |
Security assessment of suppliers of telecommunications infrastructure for the provision of services in 5G technology
ارزیابی امنیتی تامین کنندگان زیرساخت های مخابراتی برای ارائه خدمات در فناوری 5G-2020 The process of commencing services based on 5G technology has begun. One condition for starting up 5G technology is the distribution of the frequencies required for the provision of those services. For the first time in the process of making frequencies available, require- ments have arisen pertaining to the security of the infrastructure necessary for the provision of those services. In the EU, recommendations have been drawn up, based in particular on an NISCG report entitled Cybersecurity of 5G networks EU Toolbox of risk mitigating measures. In this article, an analysis is made of the implementation of those recommendations concern- ing suppliers of infrastructure, based on examples from selected EU countries, in order to ensure that such assessments are objective and transparent. In some cases, the provisions implementing the recommendations do not fully protect the fundamental rights of the en- tities assessed as foreseen in EU and domestic law, particularly the right to a fair trial before an independent court. I propose certain changes in the regulations pertaining to suppliers of telecommunications equipment. Keywords: 5G | Security | Telecommunications infrastructure | Supplier infrastructure | 5G toolbox |
مقاله انگلیسی |