مشخصات مقاله | |
ترجمه عنوان مقاله | حریم خصوصی تفاضلی در شبکه های رادیو شناختی: یک بررسی جامع |
عنوان انگلیسی مقاله | Differential Privacy in Cognitive Radio Networks: A Comprehensive Survey |
نشریه | اسپرینگر |
سال انتشار | 2022 |
تعداد صفحات مقاله انگلیسی | 36 صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
نوع نگارش مقاله |
مقاله پژوهشی (Research article) |
مقاله بیس | این مقاله بیس میباشد |
نمایه (index) | JCR – Master Journal List – Scopus |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
5.240 در سال 2020 |
شاخص H_index | 56 در سال 2022 |
شاخص SJR | 1.348 در سال 2020 |
شناسه ISSN | 1866-9964 |
شاخص Quartile (چارک) | Q1 در سال 2020 |
فرضیه | ندارد |
مدل مفهومی | دارد |
پرسشنامه | ندارد |
متغیر | دارد |
رفرنس | دارد |
رشته های مرتبط | مهندسی کامپیوتر – مهندسی فناوری اطلاعات |
گرایش های مرتبط | امنیت اطلاعات – مهندسی نرم افزار – اینترنت و شبکه های گسترده |
نوع ارائه مقاله |
ژورنال |
مجله / کنفرانس | محاسبات شناختی – Cognitive Computation |
دانشگاه | Swinburne University of Technology, Australia |
کلمات کلیدی | حریم خصوصی متفاوت (DP) – شبکه های رادیویی شناختی (CRN) – حریم خصوصی در ارتباطات |
کلمات کلیدی انگلیسی | Differential Privacy (DP) – Cognitive Radio Networks (CRN) – Privacy in communication |
شناسه دیجیتال – doi |
https://doi.org/10.1007/s12559-021-09969-9 |
لینک سایت مرجع |
https://link.springer.com/article/10.1007/s12559-021-09969-9 |
کد محصول | e17085 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Abstract Introduction Key Contributions of Our Survey Article Related Survey Works Overview of the Article Fundamentals of Differential Privacy in Cognitive Radio Networks Cognitive Radio and its Preliminaries Differential Privacy Importance of Privacy Protection in CRN Adversary Models in CRN Motivation of Using Differential Privacy in CRN Scenarios of Privacy Leakage During Cognitive Cycle and Prospective Role of Differential Privacy Privacy Leakage Scenarios During Spectrum Sensing Privacy Leakage Scenarios During Spectrum Analysis Privacy Leakage Scenarios During Spectrum Sharing Privacy Leakage Scenarios During Spectrum Mobility Summary Performance Matrices for Evaluating Differentially Private CRN Mechanisms Attack Resilience Differential Privacy Approaches for Cognitive Radio Networks Differential Privacy in Spectrum Sharing Applicability of Differential Privacy in Futuristic Cognitive Radios Cognitive Radio‑Based Internet of Things Machine/Deep Learning‑Based Cognitive Radio Networks Cognitive Radio‑Based UAV Communication Cognitive Radio‑Based Industrial Internet of Things Blockchain‑Based Cognitive Radio Networks Challenges and Future Research Directions Integrating Blockchain with Differential Privacy and CRN Differential Privacy in Game‑Theoretic Spectrum Sharing Models Differentially Private Cognitive Radio Trade‑Ofs Differential Privacy in Spectrum Characterization Differential Privacy in CRN for Smart Grid System Integrating Differential Privacy in Federated Learning with CRN Conclusion Declarations References |
بخشی از متن مقاله: |
Abstract Integrating cognitive radio (CR) with traditional wireless networks is helping solve the problem of spectrum scarcity in an efficient manner. The opportunistic and dynamic spectrum access features of CR provide the functionality to its unlicensed users to utilize the underutilized spectrum at the time of need because CR nodes can sense vacant bands of spectrum and can also access them to carry out communication. Various capabilities of CR nodes depend upon efficient and continuous reporting of data with each other and centralized base stations, which in turn can cause leakage in privacy. Experimental studies have shown that the privacy of CR users can be compromised easily during the cognition cycle, because they are knowingly or unknowingly sharing various personally identifiable information (PII), such as location, device ID, signal status, etc. In order to preserve this privacy leakage, various privacy preserving strategies have been developed by researchers, and according to us differential privacy is the most significant among them. In this article, we provide a thorough survey on how differential privacy can play an active role in preserving privacy of cognitive radio networks (CRN). Firstly, we provide a thorough comparison of our work with other similar studies to show its novelty and contribution, and afterwards, we provide a thorough analysis from the perspective of various CR scenarios which can cause privacy leakage. After that, we carry out an in-depth assessment from the perspective of integration of differential privacy at different levels of CRN. Then, we discuss various parameters which should be considered while integrating differential privacy in CRN alongside providing a comprehensive discussion about all integrations of differential privacy carried out till date. Finally, we provide discussion about prospective applications, challenges, and future research directions. The discussion about integration of differential privacy in different CR scenarios indicates that differential privacy is one of the most viable mechanisms to preserve privacy of CRN in modern day scenarios. From the discussion in the article, it is evident that the proposed integration of differential privacy can pave the way for futuristic CRN in which CR users will be able to share information during the cognition cycle without the risk of losing their private information. Introduction The exponential surge in the usage of hand-held Internet of Things (IoT) devices caused a huge rise in wireless trafc. Statista report revealed that the number of hand-held mobile devices is projected to reach up to 17.72 billion by the end of the year 2024 [1]. This surge is causing an irregular usage of spectrum, which is further responsible to cause the issue of ‘artifcial spectrum scarcity’ [2]. Similarly, the worldwide analysis and measurement of spectrum utilization revealed that only 5-10 % of wireless spectrum is being used by licensed/authorized users [3]. All these factors lead researchers to investigate mechanisms which provide spectrum efciency, and cognitive radio (CR) is one of them. Cognitive radio is a widely accepted model for efcient spectrum utilization [4]. CR was frst coined by J. Mitola in 1999. CR is an ambiance-aware intelligent wireless system which can dynamically adapt changes depending upon its surrounding RF environment [5]. CR works over the principle of allowing CR users (also known as Secondary Users (SUs)), to access spectrum of licensed users (also known as Primary Users (PUs)), during idle time. This functionality of CR allows SUs to exploit underutilized bands of spectrum without causing any harmful inference to the communication of PUs [6]. Thus, SUs can dynamically access available spaces in the spectrum band in order to manage it efciently [7, 8]. Conclusion Spectrum is a non-renewable resource. It is therefore important to use this precious resource in an efcient manner. In order to carry out efcient utilization of spectrum, scientists developed the notion of CR, which works over the principle of spectrum access at vacant times. CR nodes have the ability to sense the loopholes in the spectrum and then use these loopholes to carry out communication. In this way, CR nodes can play a vital role in overcoming spectrum scarcity. Nevertheless, CRN has a large number of benefts, they are not immune to all threats and one of the most critical ones is the privacy leakage, which causes serious consequences if not handled properly. Certain research works have highlighted the use of various privacy preservation approaches to protect privacy of CRN, and diferential privacy is one of them. Diferential privacy can play an important role in the design and development of modern, private, and more secure CRN of the future. In this paper, we carried out a comprehensive survey targeting the integration of diferential privacy in CRN from various aspects. Firstly, we highlight the importance of privacy preservation in CRN, by discussing the functioning of diferential privacy. We then provide an in-depth discussion about the sources of privacy leakage in CRN. Next we provide insights into how diferential privacy can play a critical role in protecting this leakage. We then present an analysis of certain parameters that should be taken into account while developing diferential privacy-based CRN protocols. Then, an in-depth analysis of technical works integrating diferential privacy in various scenarios of CRN. Finally, we provide analysis about prospective future directions alongside highlighting certain challenges that researchers may face. |