A Secure Authentication and Key Establishment Scheme for Wearable Devices

With rapid growth of wireless local area networks (WLAN) and computing techniques, handheld devices have become a popular tool in terms of working, entertaining and communicating in daily life. Considering the huge amounts of messages travelling in WLAN, a secure authentication scheme is definitely necessary, which is also required to be flexible across multiple organizations. Aiming for establishing a secure and flexible WLAN authentication scheme for various organizations, this paper reviews existing secure authentication mechanisms, describes the details of the proposed authentication scheme, and evaluates achievements of such a scheme.

Developments in wireless communications and wearable devices have facilitated the emergence of a network of tiny sensors embedded in, on or around human body called Wireless Body Area Network (WBAN). Over the last decade, WBAN has increasingly been playing a vital role in modern medical systems because of its potential to revolutionize healthcare delivery. The data collected by the sensors contain sensitive information and are transmitted via wireless channels. However, the openness of these channels makes WBAN vulnerable to attacks by unauthorized users. Therefore, secure authentication and data encryption schemes in WBAN are essential. The resource constraint nature of the sensors makes traditional cryptographic schemes unsuitable. Consequently, authentication schemes based on channel characteristics are proposed, which are more suitable with fewer requirements. However, existing approaches do not consider mutual authentication as well as passive/active attacks. Motivated by these limitations, we propose in this paper, a mutual authentication and data encryption scheme based on signal propagation characteristics and enhanced butterfly algorithm. To validate the effectiveness of our scheme, we conducted an extensive real-world experiment involving 5 volunteers in indoor and outdoor areas, under distinct scenarios. We further conducted security and performance analyses to validate the effectiveness of our scheme in terms of resources and its resilience to various attacks. The results of the experiments and the analyses show that our scheme could mutually identify legitimate users and protect user data against active/passive eavesdropping attacks with minimal overhead.

A paradigm that combines cloud computing and the Internet of Things (IoT) allows for more impressive services to be provided to users while addressing storage and computational resource issues in the IoT environments. This cloud-based IoT environment has been used in various industries, including public services, for quite some time, and has been researched in academia. However, various security issues can arise during the communication between IoT devices and cloud servers, because communication between devices occurs in open channels. Moreover, issues such as theft of a user's IoT device or extraction of key parameters from the user's device in a remote location can arise. Researchers interested in these issues have proposed lightweight mutual authentication key agreement protocols that are safe and suitable for IoT environments. Recently, a lightweight authentication scheme between IoT devices and cloud servers has been presented. However, we found out their scheme had various security vulnerabilities, vulnerable to insider, impersonation, verification table leakage, and privileged insider attacks, and did not provide users with untraceability. To address these flaws, we propose a provably secure lightweight authentication scheme. The proposed scheme uses the user's biometric information and the cloud server's secret key to prevent the exposure of key parameters. Additionally, it ensures low computational costs for providing users with real-time and fast services using only exclusive OR operations and hash functions in the IoT environments. To analyze the safety of the proposed scheme, we use informal security analysis, Burrows-Abadi-Needham (BAN) logic and a Real-or-Random (RoR) model. The analysis results confirm that our scheme is secure against insider attacks, impersonation attacks, stolen verifier attacks, and so on; furthermore, it provides additional security elements. Simultaneously, it has been verified to possess enhanced communication costs, and total bit size has been shortened to 3776 bits, which is improved by almost 6% compared to Wu et al.'s scheme. Therefore, we demonstrate that the proposed scheme is suitable for cloud-based IoT environments.

Internet of Drones (IoD), designed to coordinate the access of unmanned aerial vehicles (UAVs), is a specific application of the Internet of Things (IoT). Drones are used to control airspace and offer services such as rescue, traffic surveillance, environmental monitoring, delivery and so on. However, IoD continues to suffer from privacy and security issues. Firstly, messages are transmitted over public channels in IoD environments, which compromises data security. Further, sensitive data can also be extracted from stolen mobile devices of remote users. Moreover, drones are susceptible to physical capture and manipulation by adversaries, which are called drone capture attacks. Thus, the development of a secure and lightweight authentication scheme is essential to overcoming these security vulnerabilities, even on resource-constrained drones. In 2021, Akram et al. proposed a secure and lightweight user–drone authentication scheme for drone networks. However, we discovered that Akram et al.’s scheme is susceptible to user and drone impersonation, verification table leakage, and denial of service (DoS) attacks. Furthermore, their scheme cannot provide perfect forward secrecy. To overcome the aforementioned security vulnerabilities, we propose a secure mutual authentication and key agreement scheme between user and drone pairs. The proposed scheme utilizes physical unclonable function (PUF) to give drones uniqueness and resistance against drone stolen attacks. Moreover, the proposed scheme uses a fuzzy extractor to utilize the biometrics of users as secret parameters. We analyze the security of the proposed scheme using informal security analysis, Burrows–Abadi–Needham (BAN) logic, a Real-or-Random (RoR) model, and Automated Verification of Internet Security Protocols and Applications (AVISPA) simulation. We also compared the security features and performance of the proposed scheme and the existing related schemes. Therefore, we demonstrate that the proposed scheme is suitable for IoD environments that can provide users with secure and convenient wireless communications.

IoT and ICT are building the framework of the world all around us smarter and further receptive, integrating the digital and substantial universe; consequently, there are already more connected things than humans across the globe. Networked coupled gadgets use integrated sensors to accumulate statistics and process it, thereby improving our performance and lifestyle. Practical IoT instances extent from an intelligent home that instinctively regulates light and heat, smart watches to RFID chips that is automatically adjusted to prevent failures. As the users and smart gadgets communicate via an unsafe transmission medium, the crucial data interchanged amidst the network becomes prone to an opponent that causes security and privacy problems such as impersonation, failed mutual authentication and session key disclosure. In this paper, we address these drawbacks and vulnerabilities and put forward a more efficient, secure, and lightweight authentication scheme. Using the AVISPA tool, we also illustrate that the propounded scheme guarantees higher safety and protection while decreasing implementation complexity to correlated schemes and it is appropriate with applications of smart home environments established on IoT.KeywordsIoTSmart homeSecurityMutual authenticationAVISPA

A provably secure and lightweight authentication scheme for Internet of Drones for smart city surveillance

As the technology of mobile devices spreads fast, the price of mobile devices is getting cheaper. Most of the people have mobile devices, and these devices have the technology of near field communication (NFC). With the long time development and research, the mobile devices use NFC technology on the payment and authentication applications, and replace the smartcard, the access control card, and the credit card by using the card emulation mode. It helps the development of NFC applications. In recent years, more and more users begin using NFC technology on mobile payment and authentication. Many researches have proposed the related NFC authentication protocols, but their schemes are still lack of some security properties and functions, which are necessary for NFC authentication protocols. In this paper, we propose a secure and efficient NFC authentication scheme between two NFC devices by the help of the authentication server that provides mutual authentication.

Over the past decades, Session Initiation Protocol (SIP) has been commonly utilized in signaling protocol to control and signal multimedia communication sessions for providing various services to users. Video calls and internet telephony over Internet Protocol (IP) are the most common applications on SIP. Generally, the SIP acts as an unsafe communication platform, due to the exchange of information via public channels. Thus, the security of the SIP network should be increased prominently and require secure authentication and key establishment schemes. In this article, a deep learning model fractional lyrebird optimization algorithm–deep stack autoencoder (FLOA‐DSA) is developed for the detection of SIP‐based distributed reflection denial‐of‐service (DRDoS) attacks in SIP network. Here, the authentication process is carried out under different phases based on various mathematical model functionalities. Moreover, the deep stack autoencoder (DSA) model is used to perform intrusion detection in the attack validation phase. The detection performance of DSA is increased by training using the fractional lyrebird optimization algorithm (FLOA); FLOA provides a more effective, reliable, and scalable optimization strategy for training DSAs than traditional algorithms. Its ability to dynamically interact with DSA’s learning dynamics makes it not just a suitable choice, but the optimal optimization choice for this hybrid deep learning system. Further, the detection performance of the FLOA‐DSA is evaluated based on the metrics, such as detection rate, F ‐measure, false positive rate (FPR), memory usage, validation time, conditional privacy, response time, energy efficiency, and latency, and the FLOA‐DSA obtained best results of 90.12%, 91.40%, 9.13%, 6.9 MB, 48.5 s, 3.86 s, 88.88 bits/J, and 2.68 s. The F ‐measure of the proposed method is 9.06%, 6.63%, 4.80%, and 2.61% improved than other existing comparative methods.

The development of the industrial Internet of Things (IIoT) promotes the integration of the cross-platform systems in fog computing, which enable users to obtain access to multiple application located in different geographical locations. Fog users at the network’s edge communicate with many fog servers in different fogs and newly joined servers that they had never contacted before. This communication complexity brings enormous security challenges and potential vulnerability to malicious threats. The attacker may replace the edge device with a fake one and authenticate it as a legitimate device. Therefore, to prevent unauthorized users from accessing fog servers, we propose a new secure and lightweight multi-factor authentication scheme for cross-platform IoT systems (SELAMAT). The proposed scheme extends the Kerberos workflow and utilizes the AES-ECC algorithm for efficient encryption keys management and secure communication between the edge nodes and fog node servers to establish secure mutual authentication. The scheme was tested for its security analysis using the formal security verification under the widely accepted AVISPA tool. We proved our scheme using Burrows Abdi Needham’s logic (BAN logic) to prove secure mutual authentication. The results show that the SELAMAT scheme provides better security, functionality, communication, and computation cost than the existing schemes.

Decoding motion aftereffects from activity patterns in human visual cortex

In recent years, the Internet of vehicles (IoV) has become an indispensable part of wireless communication. To protect users' privacy and communication security, an increasing number of scholars have focused on studying the safety of the IoV. However, due to the characteristics of the IoV, the problem of privacy protection and communication security has not been sufficiently studied and remains open in the IoV; thus, it is worthwhile for us to further explore and study the precise and dynamic safety certification in high-speed driving environments. In our study, we divide the IoV into several fogs to reduce the burden on the traffic control center and propose a new security authentication scheme with the vehicle's identity based on the security elliptic curve. The fog-based identity authentication (FBIA) scheme consists of two layers: the security authentication layer for vehicles outside the fog and the security monitoring layer for the rest of the vehicles. We propose two-way authentication based on the vehicle's identity in the security authentication layer and a deep learning scheme in the security monitoring layer to conduct real-time security in the IoV. Finally, we compare and analyze our FBIA scheme with related approaches, and the results show that the FBIA scheme has higher authentication accuracy and better adaptability to a high-speed mobile network environment in the IoV.

With ubiquitous computing and penetration of high-speed data networks, the Internet of Medical Things (IoMT) has found widespread application. Digital healthcare helps medical professionals monitor patients and provide services remotely. With the increased adoption of IoMT comes an increased risk profile. Private and confidential medical data is gathered across various IoMT devices and transmitted to medical servers. Privacy breach or unauthorized access to personal medical data has far-reaching consequences. However, heterogeneity, limited computational resources, and lack of standardization in authentication schemes prevent a robust IoMT security framework. This paper introduces a secure lightweight authentication and authorization scheme. The use of the Physical Unclonable Function (PUF) reduces pressure on computational resources and establishes the authenticity of the IoMT. The use of OAuth 2.0 open standard for authorization allows interoperability between different vendors. The resilience of the model to impersonation and replay attacks is analyzed.

Rapid development in mobile devices and cloud computing technologies has increased the number of mobile services from different vendors on the cloud platform. However, users of these services are facing different security and access control challenges due to the nonexistence of security solutions capable of providing secure access to these services, which are from different vendors, using a single key. An effective security solution for heterogeneous Mobile Cloud Computing (MCC) services should be able to guarantee confidentiality and integrity through single key-based authentication scheme. Meanwhile, a few of the existing authentication schemes for MCC services require different keys to access different services from different vendors on a cloud platform, thus increases complexity and overhead incurred through generation and storage of different keys for different services. In this paper, an efficient mutual authentication scheme for accessing heterogeneous MCC services is proposed. The proposed scheme combines the user’s voice signature with cryptography operations to evolve efficient mutual authentication scheme devoid of key escrow problem and allows authorized users to use single key to access the heterogeneous MCC services at a reduced cost.

Secure and efficient mutual authentication and key agreement schemes form the basis for any robust network communication system. Elliptic Curve Cryptography (ECC) has emerged as one of the most successful Public Key Cryptosystem that efficiently meets all the security challenges. Comparison of ECC with other Public Key Cryptosystems (RSA, Rabin, ElGamal) shows that it provides equal level of security for a far smaller bit size, thereby substantially reducing the processing overhead. This makes it suitable for constrained environments like wireless networks and mobile devices as well as for security sensitive applications like electronic banking, financial transactions and smart grids. With the successful implementation of ECC in security applications (e-passports, e-IDs, embedded systems), it is getting widely commercialized. ECC is simple and faster and is therefore emerging as an attractive alternative for providing security in lightweight device, which contributes to its popularity in the present scenario. In this paper, we have analyzed some of the recent password based authentication and key agreement schemes using ECC for various environments. Furthermore, we have carried out security, functionality and performance comparisons of these schemes and found that they are unable to satisfy their claimed security goals.

Recent advances in semiconductor technologies and computing systems have led to the proliferation of mobile and portable electronic devices opening the ubiquitous mobile computing environment. A wearable computing technology is an example for the user to facilely place such devices around the human body. The wearable electronic devices (e.g., wrist-type computers, earphones, video eyeglasses, and head-mounted displays) and sensors offer potentials for wide range of applications from the health management to ambient intelligence [1–2]. Since such devices are distributed on the human body, a body area network (BAN) can provide the connectivity between each wearable device with the communication range of the human body, corresponding to 1–2 m. Moreover, it should get powered by a very small battery in order to minimize its physical size and get connected through simple interfaces for the convenience of the use. Since the wearer utilizes wearable electronic devices and sensors continuously anytime and anywhere, the devices require a low power data transceiver employing energy-efficient communication schemes and also the high data rate operation needs for exchanging multimedia data such as audio or video over BANs.