Industrial wireless sensor networks (IWSNs) are emerging as a new network paradigm in Internet of Things (IoT) for smart manufacturing, monitoring, and automation systems. IWSNs seamlessly integrate with IoT platforms and cloud services to support advanced services such as remote monitoring, AI-powered analytics, and advanced automated control. However, these systems can be vulnerable to potential security attacks because an adversary can attempt to delete, modify, intercept, and block the transmitted messages over an insecure channel. Besides cybersecurity attacks, IoT devices may be vulnerable to physical security attacks because they are deployed in unattended environments. To resolve these security threats and weaknesses, robust and lightweight authentication and key agreement (AKA) schemes are essential. Many researchers have recently presented a PUF-based secure and lightweight AKA scheme for IWSN-based IoT. Unfortunately, we demonstrated that the previous scheme is susceptible to potential security threats and does not guarantee the necessary security functionalities. Moreover, the existing PUF-based AKA schemes may be vulnerable to machine learning (ML)-based modeling attacks. Thus, we propose a ML-based modeling attack-resistant PUF-enabled robust AKA scheme for IWSN-enabled IoT to improve the security flaws of the previous scheme, called PUF-IWSN. We evaluate the security of PUF-IWSN by performing formal security analysis such as AVISPA simulation and ROR oracle model. We demonstrate the analysis of performance comparison between PUF-IWSN and its related schemes. We present the implementation to evaluate the security of existing PUFs and the hybrid PUF against ML-based modeling attacks. Consequently, PUF-IWSN ensures superior efficiency and security than the previous schemes and can be suitable for practical IWSN-enabled IoT systems.

Fog-enabled Internet of Things (IoT) systems have a lot of attention and are being applied in various fields, including smart homes, smart healthcare, smart factories, and smart grids. These fog-enabled IoT systems enhance citizens’ quality of life and provide innovative and high-quality IoT services. However, these systems can be vulnerable to cyber security attacks since an adversary attempts to modify, delete, block, and intercept the exchanged data over an insecure channel. Besides cyber security attacks, IoT can be fragile to physical security attacks because they are deployed in hostile environments. Physical unclonable function (PUF) is a promising solution to address these issues. PUF can protect the security of IoT devices with minimal computation costs against cyber/physical attacks from an adversary. However, with recent advances in artificial intelligence (AI) technology, existing PUFs used in authentication and key agreement (AKA) schemes are susceptible to machine-learning (ML)-based modeling attacks. To address these challenges, we design the ML-based modeling attack-resistant PUF-based robust and efficient AKA scheme in fog-enabled IoT environments. We evaluate the security of the proposed scheme by performing informal and formal security analyses, such as ROR oracle model and AVISPA simulation. We present the implementation to demonstrate the accuracy against ML-based modeling attacks. Moreover, we perform the performance comparison analysis between the proposed scheme and existing schemes based on testbed implementation. Consequently, the proposed scheme provides superior security and efficiency compared to existing schemes and can be suitable for practical fog-enabled IoT systems.

Vehicle-to-grid (V2G) improves flexibility, reliability, and efficiency and ensures effective charging services by enabling two-way communication along with two-way electricity transmission between the power grid and electric vehicle (EV). However, V2G networks are fragile to lethal security threats because an attacker may try to compromise and control the communication participants at any time. Recently, Sureshkumar et al. presented a robust and lightweight authentication key establishment (AKE) for secure V2G networks to provide essential security properties. However, we prove that their scheme suffered from various security threats and lacked essential security properties. To protect against physical security attacks, a promising solution is the use of physical unclonable function (PUF) technology and many AKE schemes have been designed for V2G networks. However, these schemes are still fragile to machine learning (ML)-based modeling attacks as well as existing security threats. Thus, we design a physical unclonable function (PUF)-based robust and anonymous AKE scheme for V2G networks, called R2AKEV2G to resist ML-based modeling attacks. We prove the security of R2AKEV2G by performing formal security analyses. Moreover, we perform a network simulator (NS) 3 implementation in compliance with IEEE 802.11 to prove its feasibility and verify that R2AKE-V2G is suitable for practical V2G networks. Consequently, R2AKE-V2G supports better security features and functionalities attributes and also guarantees superior costs with regard to communication and computation as compared to existing relevant schemes.

Unmanned aerial vehicles (UAVs) integrated with the internet of things (IoT) guarantee useful advantages such as facilitating ground communications in regions where the availability of connectivity is restricted owing to physical obstacles. However, the data transmitted by sensors and IoT embedded in UAVs are facing new security issues and privacy challenges with the known security attacks over time. To address these security attacks and threats and meet lightweight UAV communication requirements, a secure and lightweight authentication and key agreement (AKA) scheme is essential. Recently, researchers have designed a lightweight blockchain-enabled AKA scheme with privacy-preserving for UAVs to provide useful and reliable services. However, we prove that the existing scheme is fragile to various security attacks and does not ensure mutual authentication. Thus, we propose a robust and lightweight blockchain-based AKA scheme for PUF-enabled UAVs, called RLBA-UAV to enhance the security problems of the existing scheme. We demonstrate the security of RLBA-UAV by using informal/formal security analyses such as the ROR oracle model and AVISPA simulation. Moreover, we demonstrate the performance comparison analysis between RLBA-UAV and related schemes for UAVs. We demonstrate an implementation of a network simulator (NS) 3 compliant with IEEE 802.11p standards to show its validation and feasibility that RLBA-UAV is appropriate for practical UAVs. Thus, RLBA-UAV offers enhanced security and operational efficiency compared to related schemes and can be applied to practical blockchain-based AKA systems for UAVs.

Wireless medical sensor networks (WMSNs)-based medical systems are an emerging paradigm of the Internet of Medical Things (IoMT) in which the patients and doctors can access various healthcare services via wireless communication technology without visiting the hospital in person. However, an adversary attempts a variety of security attacks because the sensitive information in various fields is exchanged via an insecure channel. Thus, robust and lightweight authentication protocols are essential for providing dependable healthcare services in WMSN-based medical systems. Recently, Wang et al. (IEEE Internet of Things Journal, doi: 10.1109/JIOT.2021.3117762) proposed blockchain and physically unclonable functions (PUFs)-based lightweight authentication protocol for WMSN. They claimed that their protocol is resistant to cyber and physical security threats and also does provide necessary security requirements. However, we prove that their protocol is vulnerable to various security attacks, such as man-in-the-middle and session key disclosure attacks and also lacks mutual authentication. As a result, we propose a robust authentication protocol for WMSN using blockchain and PUF to address the security problems raised by Wang et al.’s scheme. we assess the security of the proposed scheme by using informal and formal security analyses, such as AVISPA simulation and the ROR oracle model. Furthermore, we present the testbed experiments using Raspberry PI 4 based on MIRACL Crypto SDK. Then, we show the performance of the enhanced scheme compared with related schemes based on testbed experiments. Consequently, our scheme is better suited for practical WMSN-based medical systems because it provides greater security and efficiency than competing schemes.

Smart grid (SG) has been received significant attention due to various services such as renewable energy and demand response. However, SG is fragile to various security attacks because an adversary can eavesdrop, insert, delete, or intercept the exchanged messages over an open channel. Thus, secure and lightweight authentication and key agreement (AKA) scheme for SG to ensure the necessary security requirements. Recently, the existing schemes designed a secure and efficient AKA protocol for industrial SG using cryptographic primitives to ensure reliable energy services. However, we prove that existing schemes for industrial SG are vulnerable to potential security attacks and do not guarantee the necessary security requirements. To enhance the security flaws of the existing schemes, we design a secure and lightweight AKA scheme for SG using fuzzy extractor, called ISG-SLAS. ISG-SLAS resists various security attacks and provides security functionalities. We evaluate the security of the ISG-SLAS using ROR model and AVISPA simulation. Moreover, we present the testbed experiments using MIRACL based on Raspberry PI 4. We then present a comparative analysis between ISG-SLAS and related schemes. Consequently, ISG-SLAS better ensures security and efficiency compared with related schemes and is more suitable than related schemes for practical SG.

With the rapid development of micro-electronics and Information and Communication Technology (ICT), users can utilize various service such as Internet of Things(IoT), smart-healthcare and smart-home using wearable devices. However, the sensitive information of user are revealed by attackers because the medical services are provided through open channel. Therefore, secure mutual authentication and key establishment are essential to provide secure services for legitimate users in Wireless Body Area Networks(WBAN). In 2019, Gupta et al. proposed a lightweight anonymous user authentication and key establishment scheme for wearable devices. We demonstrate that their scheme cannot withstand user impersonation, session key disclosure and wearable device stolen attacks. We also propose a secure and lightweight mutual authentication and key establishment scheme using wearable devices to resolve the security shortcomings of Gupta et al.'s scheme. The proposed scheme can be suitable to resource-limited environments.

With the development of internet of things (IoT) and communication technology, the sensors and embedded devices collect a large amount of data and handle it. However, IoT environment cannot efficiently treat the big data and is vulnerable to various attacks because IoT is comprised of resource limited devices and provides a service through a open channel. In 2018, Sharma and Kalra proposed a lightweight multi-factor authentication protocol for cloud-IoT environment to overcome this problems. We demonstrate that Sharma and Kalra's scheme is vulnerable to identity and password guessing, replay and session key disclosure attacks. We also propose a secure multifactor authentication protocol to resolve the security problems of Sharma and Kalra's scheme, and then we analyze the security using informal analysis and compare the performance with Sharma and Kalra's scheme. The proposed scheme can be applied to real cloud-IoT environment securely.