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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 |
AI-based computer vision using deep learning in 6G wireless networks
بینایی کامپیوتر مبتنی بر هوش مصنوعی با استفاده از یادگیری عمیق در شبکه های بی سیم 6G-2022 Modern businesses benefit significantly from advances in computer vision technology, one of the
important sectors of artificially intelligent and computer science research. Advanced computer
vision issues like image processing, object recognition, and biometric authentication can benefit
from using deep learning methods. As smart devices and facilities advance rapidly, current net-
works such as 4 G and the forthcoming 5 G networks may not adapt to the rapidly increasing
demand. Classification of images, object classification, and facial recognition software are some
of the most difficult computer vision problems that can be solved using deep learning methods. As
a new paradigm for 6Core network design and analysis, artificial intelligence (AI) has recently
been used. Therefore, in this paper, the 6 G wireless network is used along with Deep Learning to
solve the above challenges by introducing a new methodology named Optimizing Computer
Vision with AI-enabled technology (OCV-AI). This research uses deep learning – efficiency al-
gorithms (DL-EA) for computer vision to address the issues mentioned and improve the system’s
outcome. Therefore, deep learning 6 G proposed frameworks (Dl-6 G) are suggested in this paper
to recognize pattern recognition and intelligent management systems and provide driven meth-
odology planned to be provisioned automatically. For Advanced analytics wise, 6 G networks can
summarize the significant areas for future research and potential solutions, including image
enhancement, machine vision, and access control. keywords: SHG | ارتباطات بی سیم | هوش مصنوعی | فراگیری ماشین | یادگیری عمیق | ارتباطات سیار | 6G | Wireless communication | AI | Machine learning | Deep learning | Mobile communication |
مقاله انگلیسی |
3 |
A Secure Anonymous D2D Mutual Authentication and Key Agreement Protocol for IoT
پروتکل ایمن تأیید هویت متقابل D2D و قرارداد کلیدی برای اینترنت اشیا-2022 Internet of Things (IoT) is a developing technology in our time that is prone to security problems
as it uses wireless and shared networks. A challenging scenario in IoT environments is Device-to-
Device (D2D) communication where an authentication server, as a trusted third-party, does not
participate in the Authentication and Key Agreement (AKA) process and only cooperates in the
process of allocating and updating long-term secret keys. Various authentication protocols have
been suggested for such situations but have not been able to meet security and efficiency re-
quirements. This paper examined three related protocols and demonstrated that they failed to
remain anonymous and insecure against Key Compromise Impersonation (KCI) and clogging at-
tacks. To counter these pitfalls, a new D2D mutual AKA protocol that is anonymous, untraceable,
and highly secure was designed that needed no secure channel to generate paired private and
public keys in the registration phase. Formal security proof and security analysis using BAN logic,
Real-Or-Random (ROR) model, and Scyther tool showed that our proposed protocol satisfied
security requirements. The communication and computation costs and energy consumption
comparisons denoted that our design had a better performance than existing protocols. keywords: تأیید اعتبار و توافقنامه کلید (AKA) | ارتباط دستگاه به دستگاه (D2D) | اینترنت اشیا (IoT) | حمله جعل هویت کلیدی (KCI) | Authentication and Key Agreement (AKA) | Device to Device (D2D) communication | Internet of Things (IoT) | Key Compromise Impersonation (KCI) attack |
مقاله انگلیسی |
4 |
An IoT-enabled intelligent automobile system for smart cities
یک سیستم خودروی هوشمند مجهز به اینترنت اشیا برای شهرهای هوشمند-2022 In our world of advancing technologies, automobiles are one industry where we can see
improved ergonomics and feature progressions. Artificial Intelligence (AI) integrated with
Internet of Things (IoT) is the future of most of the cutting-edge applications developed
for automobile industry to enhance performance and safety. The objective of this research
is to develop a new feature that can enhance the existing technology present in automo-
biles at low-cost. We had previously developed a technology known as Smart Accident
Precognition System (SAPS) which reduces the rate of accidents in automobile and also
enhance the safety of the passengers. Current research advances this technique by inte-
grating Google Assistant with the SAPS. The proposed system integrates several embedded
devices in the automobiles that monitor various aspects such as speed, distance, safety
measures like seatbelt, door locks, airbags, handbrakes etc. The real-time data is stored in
the cloud and the vehicle can adapt to various situations from the previous data collected.
Also, with the Google Assistant user can lock and unlock, start and stop, alert and do var-
ious automated tasks such as low fuel remainder, insurance remainders etc. The proposed
IoT enabled real-time vehicle system can detect accidents and adapt to change according
to various conditions. Further, with RFID keyless entry authentication the vehicle is secure
than ever before. This proposed system is much efficient to the existing systems and will
have a great positive impact in the automobile industry and society.
© 2020 Elsevier B.V. All rights reserved. keywords: هوش مصنوعی | سیستم هوشمند خودرو | اینترنت اشیا | شهرهای هوشمند | سیستم هوشمند | Artificial intelligence | Intelligent automobile system | Internet of Things | Smart Cities | Smart System |
مقاله انگلیسی |
5 |
Authenticated Secure Quantum-Based Communication Scheme in Internet-of-Drones Deployment
طرح ارتباطی مبتنی بر کوانتومی ایمن در استقرار اینترنت پهپادها-2022 The rapid advance of manufacturing Unmanned Aerial Vehicles (UAVs, aka drones) has led
to a rise in the use of their civilian and commercial applications. The access of these drones to controlled
airspace can be efficiently coordinated through particular layered network architecture, often referred to
as the Internet-of-Drones (IoD). The nature of IoD, which is deployed in an open-access environment,
brings significant safety and security concerns. Classical cryptosystems such as elliptic curve cryptography,
Rivest-Shamir-Adleman, and Diffie-Hellman are essential building blocks to secure communication in the
IoD. However, with the rapid development of quantum computing, it will be easy to break public-key
cryptosystems using efficient quantum algorithms like Shor’s algorithm. Thus, building quantum-safe
solutions to enhance IoD security has become imperative. Fortunately, quantum technologies can provide
unconditional security solutions to protect data and communications in the IoD environment. This paper
proposes a quantum-based scheme to prevent unauthorized drones from accessing a specific flight zone
and authenticates the identities and shared secret messages of involved entities. To do so, we used a quantum
channel to encode the private information based on a pre-shared key and a random key generated in a session.
The involved entities also perform mutual authentication and share a secret key. We also provide the security
proofs and analysis of the proposed scheme that indicates its resistance to well-known attacks.
INDEX TERMS- Authentication | internet-of-drones | quantum-based communication | quantum cryptography. |
مقاله انگلیسی |
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CREASE: Certificateless and REused-pseudonym based Authentication Scheme for Enabling security and privacy in VANETs
CREASE: طرح احراز هویت مبتنی بر نام مستعار بدون گواهی و استفاده مجدد برای فعال کردن امنیت و حریم خصوصی در VANET-2022 Due to the customers’ growing interest in using various intelligent and connected devices, we
are surrounded by the Internet of Things (IoT). It is estimated that the number of IoT devices
will exceed 60 billion by 2025. One of the primary reasons for such rapid growth is the Internet
of Vehicles (IoV). Internet of Vehicles (IoV) has evolved into an emerging concept in intelligent
transportation systems (ITS) that integrates VANETs and the IoT to enhance their capabilities.
With the emergence of IoV and the interest shown by customers, Vehicular Ad hoc NETworks
(VANETs) are likely to be widely deployed in the near future. However, for this to happen, wide
participation of vehicle owners in VANET is needed. The primary concerns of vehicle owners
to participate in VANET are privacy and security. In this paper, we present a Certificateless and
REused-pseudonym based Authentication Scheme for Enabling security and privacy (CREASE) in
VANETs. One of the ways to preserve the privacy of vehicles/drivers is to allow vehicles/drivers
to use pseudo identities (pseudonyms) instead of their real identities (such as VIN number or
driving license number) in all communications. The pseudonym used by a vehicle needs to
be changed frequently to prevent the vehicle from being tracked. Our scheme uses Merkle
Hash Tree and Modified Merkle Patricia Trie to efficiently store and manage the pseudonyms
assigned to a vehicle. This enables a vehicle to pick and use a random pseudonym from a
given set of pseudonyms assigned to it as well as change its pseudonym frequently and securely
to ensure privacy. Unlike many of the existing schemes, our scheme does not use certificates
and certificate revocation lists for authentication. Moreover, it allows vehicles to get a set of
pseudonyms only once from the trusted authority. We present a formal proof of correctness of
our scheme and also compare our scheme with some of the other contemporary schemes to
show the effectiveness of our scheme.
Keywords: VANETs | Intelligent transportation systems | Authentication | Security | Privacy-preserving authentication |
مقاله انگلیسی |
7 |
Lossless fuzzy extractor enabled secure authentication using low entropy noisy sources
استخراج کننده فازی بدون تلفات ، احراز هویت ایمن را با استفاده از منابع پر سر و صدا کم آنتروپی فعال کرد-2021 Fuzzy extractor provides a way for key generation from biometrics and other noisy data. It has been widely applied in biometric authentication systems that provides natural and passwordless user authentication. In general, given a random sample, a fuzzy extractor extracts a nearly uniform random string, and subsequently regenerates the string using a different yet similar noisy sample. However, due to error tolerance between the two samples, fuzzy extractor imposes high information loss (entropy) and thus, it only works for an input with high enough entropy. In this work, we propose a lossless fuzzy extractor for a large family of sources. The proposed lossless fuzzy extractor can be adopted for a wider range of random sources to extract an arbitrary number of nearly uniform random strings. Besides, we formally defined a new entropy measurement, named as equal error entropy, to measure the entropy loss in reproducing a bounded number of random strings. When the number of random strings is large enough, the equal error entropy is minimized and necessary for performance evaluation on the authentication using the extracted random strings. Keywords: Authentication | Biometric | Fuzzy extractor | Secure sketch |
مقاله انگلیسی |
8 |
A cancelable biometric authentication system based on feature-adaptive random projection
یک سیستم احراز هویت بیومتریک قابل لغو بر اساس طرح تصادفی سازگار با ویژگی-2021 Biometric template data protection is critical in preventing user privacy and identity from leakage. Random projection based cancelable biometrics is an efficient and effective technique to achieve biometric template protection. However, traditional random projection based cancelable template design suffers from the attack via record multiplicity (ARM), where an adversary obtains multiple transformed templates from different applica- tions and the associated parameter keys so as to assemble them into a full-rank linear equation system, thereby retrieving the original feature vector. To address this issue, in this paper we propose a feature-adaptive random projection based method, in which the projection matrixes, the key to the ARM, are generated from one basic matrix in conjunction with local feature slots. The generated projection matrixes are discarded after use, thus making it difficult for the adversary to launch the ARM. Moreover, the random projection in the proposed method is performed on a local-feature basis. This feature-adaptive random projection can mitigate the negative impact of biometric uncertainty on recognition accuracy, as it limits the error to part of the transformed feature vector rather than the entire vector. The proposed method is evaluated on four public available databases FVC2002 DB1-DB3 and FVC2004 DB2. The experimental results and security analysis show the validity of the proposed method. Keywords: Biometric authentication | Template protection | Random projection | Cancelable biometrics |
مقاله انگلیسی |
9 |
An efficient biometric-based continuous authentication scheme with HMM prehensile movements modeling
یک طرح احراز هویت مداوم مبتنی بر بیومتریک با مدل سازی حرکات پیش ساخته HMM-2021 Biometric is an emerging technique for user authentication thanks to its efficiency compared to the traditional methods, such as passwords and access-cards. However, most existing biometric authentication systems require the cooperation of users and provide only a login time authentication. To address these drawbacks, we propose in this paper a new, efficient continuous authentication scheme based on the newly biometric trait that still under development: prehensile movements. In this work, we model the movements through Hidden Markov Model-Universal Background Model (HMM-UBM) with continuous observations based on Gaussian Mixture Model (GMM). Unlike the literature, the gravity signal is included. The results of the experiments conducted on a public database HMOG and on a proprietary database, collected under uncontrolled conditions, have shown that prehensile movements are very promising. This new biometric feature will allow users to be authenticated continuously, passively and in real time. Keywords: Biometric | Authentication | Prehensile movement | HMM-UBM | GMM |
مقاله انگلیسی |
10 |
Provably secure biometric-based client–server secure communication over unreliable networks
ارتباطات امن مشتری و سرور مبتنی بر بیومتریک به طور قابل اطمینان در شبکه های غیرقابل اعتماد-2021 Due to rapid advancement in internet technologies, remote client access has become much more comfortable than in previous days. The responsibility of the system does not limit even after providing access to resources. In every system, there is a possibility that an adversary may use the resources of the system without prior authentication. This will create interruption, and the clients of the system will ultimately be affected, so the system must provide some authentication mechanism. Therefore, an authentication scheme needs to be introduced, which provides security against different attacks. Consequently, in this article, we propose a reliable and secure three factor authentication scheme that prevents various security attacks. The provable security of the proposed scheme is proved through a widely used random oracle model. We implemented the cryptographic operations of proposed and related schemes on a desktop system having good specifications to get the experimental results. Moreover, the presented scheme is compared with the existing schemes to compare its performance. The performance evaluation shows that our scheme is lightweight and efficient in terms of computation and communication costs as compared to related competing schemes. Keywords: Anonymity | Authentication | Impersonation attack | Session key | Smartcard |
مقاله انگلیسی |