Distributed Authentication Model for Secure Network Connectivity in Network Separation Technology

Considering the increasing scale and severity of damage from recent cybersecurity incidents, the need for fundamental solutions to external security threats has increased. Hence, network separation technology has been designed to stop the leakage of information by separating business computing networks from the Internet. However, security accidents have been continuously occurring, owing to the degradation of data transmission latency performance between the networks, decreasing the convenience and usability of the work environment. In a conventional centralized network connection concept, a problem occurs because if either usability or security is strengthened, the other is weakened. In this study, we proposed a distributed authentication mechanism for secure network connectivity (DAM4SNC) technology in a distributed network environment that requires security and latency performance simultaneously to overcome the trade-off limitations of existing technology. By communicating with separated networks based on the authentication between distributed nodes, the inefficiency of conventional centralized network connection solutions is overcome. Moreover, the security is enhanced through periodic authentication of the distributed nodes and differentiation of the certification levels. As a result of the experiment, the relative efficiency of the proposed scheme (REP) was about 420% or more in all cases.

Improved Handover Authentication in Fifth-Generation Communication Networks Using Fuzzy Evolutionary Optimisation with Nanocore Elements in Mobile Healthcare Applications

Authentication is a suitable form of restricting the network from different types of attacks, especially in case of fifth-generation telecommunication networks, especially in healthcare applications. The handover and authentication mechanism are one such type that enables mitigation of attacks in health-related services. In this paper, we model an evolutionary model that uses a fuzzy evolutionary model in maintaining the handover and key management to improve the performance of authentication in nanocore technology-based 5G networks. The model is designed in such a way that it minimizes the delays and complexity while authenticating the networks in 5G networks. The attacks are mitigated using an evolutionary model when it is trained with the relevant attack datasets, and the model is validated to mitigate the attacks. The simulation is conducted to test the efficacy of the model, and the results of simulation show that the proposed method is effective in improving the handling and authentication and mitigation against various types of attacks in mobile health applications.

A Blockchain-Based Efficient, Secure and Anonymous Conditional Privacy-Preserving and Authentication Scheme for the Internet of Vehicles

The rapid advancement in the area of the Internet of Vehicles (IoV) has provided numerous comforts to users due to its capability to support vehicles with wireless data communication. The exchange of information among vehicle nodes is critical due to the rapid and changing topologies, high mobility of nodes, and unpredictable network conditions. Finding a single trusted entity to store and distribute messages among vehicle nodes is also a challenging task. IoV is exposed to various security and privacy threats such as hijacking and unauthorized location tracking of smart vehicles. Traceability is an increasingly important aspect of vehicular communication to detect and penalize malicious nodes. Moreover, achieving both privacy and traceability can also be a challenging task. To address these challenges, this paper presents a blockchain-based efficient, secure, and anonymous conditional privacy-preserving and authentication mechanism for IoV networks. This solution is based on blockchain to allow vehicle nodes with mechanisms to become anonymous and take control of their data during the data communication and voting process. The proposed secure scheme provides conditional privacy to the users and the vehicles. To ensure anonymity, traceability, and unlinkability of data sharing among vehicles, we utilize Hyperledger Fabric to establish the blockchain. The proposed scheme fulfills the requirement to analyze different algorithms and schemes which are adopted for blockchain technology for a decentralized, secure, efficient, private, and traceable system. The proposed scheme examines and evaluates different consensus algorithms used in the blockchain and anonymization techniques to preserve privacy. This study also proposes a reputation-based voting system for Hyperledger Fabric to ensure a secure and reliable leader selection process in its consensus algorithm. The proposed scheme is evaluated with the existing state-of-the-art schemes and achieves better results.

Provably Secure Authentication Approach for Data Security in Cloud Using Hashing, Encryption, and Chebyshev-Based Authentication

Secure and efficient authentication mechanism becomes a major concern in cloud computing due to the data sharing among cloud server and user through internet. This paper proposed an efficient Hashing, Encryption and Chebyshev HEC-based authentication in order to provide security among data communication. With the formal and the informal security analysis, it has been demonstrated that the proposed HEC-based authentication approach provides data security more efficiently in cloud. The proposed approach amplifies the security issues and ensures the privacy and data security to the cloud user. Moreover, the proposed HEC-based authentication approach makes the system more robust and secured and has been verified with multiple scenarios. However, the proposed authentication approach requires less computational time and memory than the existing authentication techniques. The performance revealed by the proposed HEC-based authentication approach is measured in terms of computation time and memory as 26ms, and 1878bytes for 100Kb data size, respectively.

Device Identity-Based User Authentication on Electronic Payment System for Secure E-Wallet Apps

E-wallets are a modern electronic payment system technology that easily recognize consumer interest, making our transactions very convenient and efficient. E-wallets are intended to substitute the existing physical wallet, which may tell others something about us as a person. That is why using a physical wallet is a unique, personal experience that cannot be duplicated. A solution would be to replace the physical wallet with an e-wallet on an existing mobile device. The personal nature of the e-wallet is that it should be installed on a unique device. One of the fundamental protections against any illegal access to e-wallet application is through authentication. In particular, the fundamental authentication category used in an existing e-wallet is based on knowledge (i.e., what you know), ownership (i.e., what you have), and biometric (i.e., what you are) authentication, which are sometimes prone to security threats such as account takeover, sim swapping, app cloning, or know your customer verification attacks. The design of an e-wallet authentication on mobile device solution must take into consideration the intensity of the security. To address this problem, this study proposes a design of e-wallet apps with an extension security element that focuses on the device identity in the existing user authentication mechanism. This study covers four fundamental categories of authentication: password, one time password, fingerprints, and international mobile equipment identifier. Using IMEI limits an e-wallet to be in one specific device in one time; this brings it into line with the nature of a physical wallet. In addition, it will be ready to handle the mentioned threats above, which will ultimately result in the far more reliable to use of e-wallet apps. The proposed authentication design has two phases, a registration phase and an authentication phase. The proposed method has been developed and implemented based on an Android Studio Firebase real-time database management and PayPal. In addition, the complete design has been evaluated using functional requirement testing to see how closely it meets functionality requirements. The results obtained from functional testing show that the functionalities of the proposed method meet the requirements, and one cannot use a same account on two devices; hence, it is secure from attacks. The result also shows that the proposed method has no errors. Moreover, it has been shown that our proposed method has better security parameters in terms of the existing method.

A Secure Data Storage Architecture for Internet of Medical Things (IoMT) Using an Adaptive Gaussian Mutation Based Sine Cosine Optimization Algorithm and Fuzzy-Based Secure Clustering

The fast-growing Internet of Things (IoT) paradigm can be referred to be the interconnection of physical things or human beings along with the digital electronics devices, Softwares to exchange data with centralized systems through the defined communication infrastructures. Moreover, it provides better opportunities for the direct connection between the physical world and computer-based systems. Nevertheless, the security of data transmission through IoMT (Internet of Medical Things) is the biggest challenge. Hence to provide better security we proposed a novel method known as, Fuzzy based Adaptive Gaussian Mutation based Sine Cosine Optimization approach to ensure security and Quality of Service (QoS) by exploiting the Mutual authentication mechanism. Moreover, an adaptive Gaussian mutation-based SCO algorithm is exploited for cluster formulation of IoMT nodes. The Intuitionistic fuzzy based weight estimation is made for the selection of CH and effective routing. Our proposed work is compared to several recent works. From the performance analysis and evaluation, we conclude that the proposed work outperforms all the existing works and provides better QoS and security.

Privacy-Preserving Scheme in the Blockchain Based on Group Signature with Multiple Managers

Group signature can provide the privacy-preserving authentication mechanism for the blockchain. In the traditional blockchain privacy-preserving scheme based on the group signature, there is only one group manager to revoke the anonymity. Thus, the traditional scheme will have single point of failure and key escrow problems. To solve these problems, we propose a privacy-preserving scheme in the blockchain based on the group signature with multiple managers. Our scheme is constructed based on bilinear pairing and the technique of distributed key generation. Finally, we analyze the application of the proposed scheme in the field of blockchain-based provable data possession (PDP), as well as the correctness and security of the scheme.

Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT

The Industrial Internet of Things (IIoT) has led to the growth and expansion of various new opportunities in the new Industrial Transformation. There have been notable challenges regarding the security of data and challenges related to privacy when collecting real-time and automatic data while observing applications in the industry. This paper proposes an Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT. In FT-Block (Federated transfer learning blockchain), several blockchains are applied to preserve privacy and security for all types of industrial applications. Additionally, by introducing the authentication mechanism based on transfer learning, blockchains can enhance the preservation and security standards for industrial applications. Specifically, Novel Supportive Twin Delayed DDPG trains the user model to authenticate specific regions. As it is considered one of the most open and scalable interacting platforms of information, it successfully helps in the positive transfer of different kinds of data between devices in more significant and local operations of the industry. It is mainly due to a single authentication factor, and the poor adaptation to regular increases in the number of users and different requirements that make the current authentication mechanism suffer a lot in IIoT. As a result, it has been very clearly observed that the given solutions are very useful.