Abstract

The healthcare sector is a very crucial and important sector of any society, and with the evolution of the various deployed technologies, like the Internet of Things (IoT), machine learning and blockchain it has numerous advantages. However, in this section, the data is much more vulnerable than others, because the data is strictly private and confidential, and it requires a highly secured framework for the transmission of data between entities. In this article, we aim to design a blockchain-envisioned authentication and key management mechanism for the IoMT-based smart healthcare applications (in short, we call it SBAKM-HS). We compare the various attributes of the proposed SBAKM-HS and other existing schemes to demonstrate that SBAKM-HS outperforms other existing schemes. The conducted security analysis

Abstract

With the increasing use of Internet of Things (IoT)- enabled drones for various purposes, including photography, de- livery, and surveillance, concerns related to privacy and security have arisen. Drones have the potential to capture sensitive infor- mation, invade privacy, and cause security breaches. Therefore, the need for advanced technology for the automated detection of drones has become crucial. In this paper, we propose an ensemble-based IoT-enabled drones detection scheme (in short, EDDSBS). The presented model is part of a computer vision- based module and uses transfer learning for improved perfor- mance. Transfer learning allows the reuse of pre-trained models and their knowledge in a different but related domain, enabling better performance with less training data. To evaluate the performance of the proposed EDDSBS, we test it on benchmark datasets, including the Drone–vs–Bird Dataset and the UAVDT dataset. The proposed EDDSBS outperforms the existing schemes of drone detection (i.e., in terms of accuracy). The results of the presented scheme demonstrate the potential of deep learning- based technology for automated drone detection in critical areas, such as airports, military bases, and other high-security areas. Thus the paper introduces a comprehensive process methodology for drone detection that can be applied in real-world settings for a sustainable and secure environment, which is required for a safe community

Abstract

In recent days, the application of cloud computing has been gaining significant popularity among people. A considerable amount of data are being stored in the cloud server. However, data owners outsource their encrypted data to the cloud for various security reasons. Unfortunately, encrypted data cannot be searched, like plaintext data. So how to search encrypted data is an interesting problem in this era. Many public key encryption with keyword search (PEKS) schemes have been designed in the literature. However, most of them cannot prevent keyword-guessing attacks. In this paper, we develop a provably secure PEKS scheme in the random oracle model. This scheme may be used for secure email access from an email server containing a list of encrypted keywords. The proposed scheme can resist keyword-guessing attacks, and offer ciphertext and trapdoor indistinguishability properties. We use the data owner’s private key during encryption to prevent keyword-guessing attacks. Using the data owner’s public key in the verification phase ensures the resilience of keyword-guessing attacks. Finally, the proposed scheme has been tested on a real testbed, and the results show that it can be used in the cloud computing scenario to search for keywords on encrypted data

Abstract

User authentication is a promising security solution in which an external user hav- ing his/her mobile device can securely access the real-time information directly from the deployed smart devices in an Internet of Things-enabled intelligent precision agri- cultural environment. To achieve this goal, we present a new signature-based three factor user authentication scheme. The established session key between a user and the accessed smart device is then used to make secure communication among them to fetch the real-time data of the device. A detailed security analysis including the random-oracle based formal security, formal security verification using the broadly recognized automated validation of internet security protocols and applications tool and nonmathematical informal security analysis show the robustness of the proposed scheme against a number of potential attacks. In addition, testbed experiments are performed for measuring computational time of various cryptographic primitives that are used for comparative study among the proposed scheme and other related exist- ing competing schemes. The detailed comparative analysis shows that the proposed scheme has a better trade-off among its offered security and functionality features, and communication and computational overheads as compared with those for other competing schemes.

Abstract

One of the most significant recent advances in technology is the advent of unmanned aerial vehicles (UAVs), i.e., drones. They have widened the scope of possible applications and provided a platform for a wide range of creative responses to a variety of challenges. The Internet of Drones (IoD) is a relatively new concept that has arisen as a consequence of the combination of drones and the Internet. The fifth-generation (5G) and beyond cellular networks (i.e., drones in networks beyond 5G) are promising solutions for achieving safe drone operations and applications. They may have many applications, like surveillance or urban areas, security, surveillance, retaliation, delivering items, smart farming, film production, capturing nature videos, and many more. Due to the fact that it is susceptible to a wide variety of cyber-attacks, there are certain concerns regarding the privacy and security of IoD communications. In this paper, a secure blockchain-enabled authentication key management framework with the big data analytics feature for drones in networks beyond 5G applications is proposed (in short, SBBDA-IoD). The security of SBBDA-IoD against multiple attacks is demonstrated through a detailed security analysis. The Scyther tool is used to perform a formal security verification test on the SBBDA-IoD’s security, confirming the system’s resistance to various potential attacks. A detailed comparative analysis has identified that SBBDA-IoD outperforms the other schemes by a significant margin. Finally, a real-world implementation of SBBDA-IoD is shown to evaluate its effect on several measures of performance.

Abstract

Internet of Vehicles (IoV) is a wireless network, which employs well-established Internet protocols and networks to share information between vehicles, people, and infrastructure by utilising Vehicular Adhoc Networks (VANETs). IoV aims to increase road user safety and lower accident rates. It is one of the main components of an intelligent transportation system (ITS). ITS appears as the most crucial component since the cities in any country are evolving into digital civilisations as a result of the smart city concept, regardless of whether people are travelling within the city, to work, in school, or for other purposes. It can also be used to improve infrastructure utilisation and road safety (i.e., reduction in road accidents), in addition to enhancing traffic management and easing congestion. However, IoV-driven ITS is susceptible to several forms of attacks because of the insecure communication among the participating entities. We, therefore, propose a secure authentication protocol for IoV-driven ITS to stop these attacks from happening (in short, SAKP-ITS). Its resistance to a number of potential attacks is confirmed by the security analysis of the proposed SAKP-ITS. Additionally, SAKP-ITS is juxtaposed with other comparable competing methods put out in an IoV environment. Additionally, it has been found that SAKP-ITS outperforms competing schemes in terms of critical metrics like communication costs, computation costs, and security and functionality attributes. To test the effect of the proposed SAKP-ITS on the critical performance attributes, a practical implementation of SAKP-ITS

Abstract

With rapid technological growth, security attacks are drastically increasing. In many crucial Internet-of-Things (IoT) applications such as healthcare and defense, the early detection of security attacks plays a significant role in protecting huge resources. An intrusion detection system is used to address this problem. The signature-based approaches fail to detect zero-day attacks. So anomaly-based detection particularly AI tools, are becoming popular. In addition, the imbalanced dataset leads to biased results. In Machine Learning (ML) models, F1 score is an important metric to measure the accuracy of class-level correct predictions. The model may fail to detect the target samples if the F1 is considerably low. It will lead to unrecoverable consequences in sensitive applications such as healthcare and defense. So, any improvement in the F1 score has significant impact on the resource protection. In this paper, we present a framework for ML-based intrusion detection system for an imbalanced dataset. In this study, the most recent dataset, namely CICIoT2023 is considered. The random forest (RF) algorithm is used in the proposed framework. The proposed approach improves 3.72%, 3.75% and 4.69% in precision, recall and F1 score, respectively, with the existing method. Additionally, for unsaturated classes (i.e., classes with F1 score < 0.99), F1 score improved significantly by 7.9%. As a result, the proposed approach is more suitable for IoT security applications for efficient detection of intrusion and is useful in further studies.

Abstract

The cloud computing technology is a novel storage and computing paradigm that enables individuals and organizations to store data, share data with intended group of users and retrieve data when require. It greatly improves peoples’ data storage and sharing, and data retrieval capabilities by providing flexible, less expensive and quality services. For data security and privacy concerns, secure and authenticated data storage, fine-grained access control of encrypted data, secure search for the outsourced data and search results verification are of critical importance. However, achieving the aforementioned functionalities simultaneously is quite challenging. In this paper, for the first time, we propose a secure lightweight Attribute-Based verifiable Data Storage and data Retrieval Scheme (ABDSRS) for cloud environments that attains the following features: (i) lightweight design, (ii) provably secure, (iii) fine-grained …

Abstract

The Internet of Things (IoT) allows better solutions for managing challenges such as reliability and power quality in a smart grid environment. It also assists in adopting smart grid measures in smart city development. A smart meter in the smart grid environment must securely access services from a service provider via public channels. An adversary can pose several security vulnerabilities as the communication occurs through a public channel. Various researchers recently conducted several research types to determine the most challenging problems with the smart grid. The security features like integrity, authentication, and confidentiality are indispensable requirements of the smart grid environment. On the other hand, different objects like smart meters in the smart grid environment are resource-constrained, posing in designing lightweight security protocols. Hence, we propose a lightweight mutual authentication

Abstract

The Energy Internet (EI) presents a novel paradigm for renewable energy distribution that utilizes communication and computing technologies to revolutionize the conventional Intelligent Transportation Systems (ITSs) and power grid into a structure that provides assistance to open innovation. The EI offers sustainable and bidirectional transmission for the improvement and analysis of energy convention among Electric Vehicles (EVs) and service providers. To ensure efficient, reliable, and secure operation, EI must be safe from security attacks. Therefore, efficient and secure key negotiation is a significant issue for the EI-based Vehicle-to-Grid (V2G) architecture. Thus, to ensure the system’s security, we have devised a robust scheme to facilitate a secure key agreement between the entities involved for the secure and efficient renewable energy distribution for the EI-based energy vehicles in V2G. The devised scheme’s robustness is solicited through the widely-accepted formal Random or Real (RoR) model. In addition, the informal security analysis is conducted on the devised scheme, which is evident that the designed scheme achieves all the required security features of EI-based ITS. Moreover, the performance evaluation results endorse that the designed scheme achieves the desired security and minimizes the communication, computation, and energy overhead by 29.33%, 27.94% and 28.08% in comparison to the existing competitive schemes.