![]() The first one relies on the cyclostationarity characteristics of the investigated waveforms combined with a support vector machine (SVM) classifier while the second one explores the use of a four-layer CNN which performs both features extraction and classification. Specifically, we design two types of classification algorithms. With the advent of spectrally efficient filtered multicarrier waveforms, we propose in this paper, to revisit the DL based ASR to account for the variety and complexity of these new transmission schemes. However, such works have been primarily focusing on single-carrier signals. Recently, many research works have been exploring deep learning (DL) based ASR, where it has been shown that simple convolutional neural networks (CNN) can outperform expert features based techniques. ZKP-AKA retains data integrity, confidentiality, anonymity, and safety from significant cyber threats.Īutomatic signal recognition (ASR) plays an important role in various applications such as dynamic spectrum access and cognitive radio, hence it will be a key enabler for beyond 5G communications. ZKP-AKA uses zero-knowledge proofs, physically unclonable function, biometrics, symmetric cryptography, message digest, etc., for accomplishing the protocol's objective at minimal computation, storage, and communication expenses. This paper proposes Zero-Knowledge Proofs (ZKP) based Authenticated Key Agreement (AKA) protocol for IoHA. ![]() ![]() We introduce a confidentiality and anonymity-preserving scheme for critical infrastructures of IoT to conquer cyber threats for sustainable healthcare. The existing security protocols are unsuitable due to the cost complexities that necessitate developing new security protocols for resource-constrained and heterogeneous IoT networks. ![]() The cyber attacks on the Internet of Healthcare applications (IoHA) could result in fatalities, decreased revenue, and reputation loss, hence endangering sustainability. Besides, tiny IoT devices have limited computing power and storage capabilities that prevent administrators from using complex and resource-hungry security protocols. Despite its enormous benefits, IoT in healthcare has not received much attention primarily due to the risk of unauthorized access to confidential medical information enabled by the vulnerable wireless channel for communication. Upgradation of technologies for sustainable smart cities has led to rapid growth in Internet of Things (IoT) applications, including e-healthcare services wherein smart devices collect patient data and deliver it remotely to the servers in real-time. ![]()
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