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Kamarudin, N.H.; Suhaimi, N.H.S.; Nor Rashid, F.A.; Khalid, M.N.A.; Mohd Ali, F. Authentication Paradigms in the Internet of Things. Encyclopedia. Available online: https://encyclopedia.pub/entry/54852 (accessed on 18 May 2024).
Kamarudin NH, Suhaimi NHS, Nor Rashid FA, Khalid MNA, Mohd Ali F. Authentication Paradigms in the Internet of Things. Encyclopedia. Available at: https://encyclopedia.pub/entry/54852. Accessed May 18, 2024.
Kamarudin, Nazhatul Hafizah, Nur Hanis Sabrina Suhaimi, Fadilla Atyka Nor Rashid, Mohd Nor Akmal Khalid, Fazlina Mohd Ali. "Authentication Paradigms in the Internet of Things" Encyclopedia, https://encyclopedia.pub/entry/54852 (accessed May 18, 2024).
Kamarudin, N.H., Suhaimi, N.H.S., Nor Rashid, F.A., Khalid, M.N.A., & Mohd Ali, F. (2024, February 07). Authentication Paradigms in the Internet of Things. In Encyclopedia. https://encyclopedia.pub/entry/54852
Kamarudin, Nazhatul Hafizah, et al. "Authentication Paradigms in the Internet of Things." Encyclopedia. Web. 07 February, 2024.
Authentication Paradigms in the Internet of Things
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This entry is adapted from the peer-reviewed paper 10.3390/sym16020171

In the rapidly expanding domain of the Internet of Things (IoT), ensuring the implementation of robust security measures such as authentication has become paramount to safeguarding sensitive data and maintaining the integrity of connected devices. Symmetry in the IoT commonly denotes the uniformity or equilibrium in data distribution and processing across devices or nodes in a network. Leveraging symmetric patterns can enhance the robustness and scalability of IoT authentication. 

authentication internet of things network security

1. Introduction

The exponential expansion of linked devices has resulted in the creation of the vast network known as the Internet of Things (IoT). A wide range of industries, including public health, smart grids, smart transportation, waste management, smart homes, smart cities, agriculture, and energy management, are served by this interconnected network, which includes smart devices such as sensors and actuators [1][2][3]. But the requirements and limitations that these connected “things” inherently bring with them present a multitude of difficulties. Connectivity issues arise when billions of devices attempt to communicate with each other, and the need to protect IoT networks from possible threats is ever-present. This urgency is highlighted by a recent Gartner analysis, which found that 20% of firms had experienced at least one IoT attack in the previous three years [4]. Events such as the Mirai botnet [5], in which Internet of Things networks were used as a means of attack, add to the complexity of the security environment. The inherent resource constraints of Internet of Things (IoT) devices compound these issues by making traditional communication protocols and security mechanisms ineffective and, in certain situations, impractical for IoT applications. Because these devices are widely used in important applications, the growing security concerns in the IoT space are especially concerning.
The security prerequisites for an IoT network hinge on the unique applications it supports. The need for confidentiality, integrity, and authentication is closely linked to the security requirements of each application. Authentication, in particular, is considered a crucial element for IoT [6], as the reliability of involved devices is essential for the network’s optimal performance. The compromise of a single node has the potential to turn it into a malicious entity capable of jeopardizing the entire system or triggering catastrophic events [7][8]. Given the distinctive nature of IoT devices, traditional authentication schemes are deemed impractical and unsuitable. Cryptographic methods designed for mains-powered, high-processing, and large-memory devices need to be adapted to be more suitable for resource-limited IoT nodes. This predicament has led to lightweight authentication schemes, some tailored specifically for the context of IoT or Wireless Sensor Networks (WSNs), which are deemed applicable to IoT.

2. Contribution Trends of Authentication in IoT System

Although issues are raised in implementing authentication in the IoT, it has also contributed to research fields. Five significant contribution trends have been identified: lightweight cryptography, blockchain integration, privacy-preserving approaches, efficient encryption, and novel security mechanisms. This section will delve into the five contribution approaches for each domain, and they have been mapped in Table 1.
Table 1. Research clustering on contribution trends in IoT authentication.
Domain Research Clustering on Contribution Trends
Lightweight Cryptography Blockchain Integration Privacy-Preserving Approaches Efficient Encryption Novel Security Mechanisms
Industrial [7][9][10] [11][12] [10][13] [14][15] [12][16]
Healthcare [17][18][19] [20] [20][21] [14] [20][22]
Cloud and Fog [23][24] [23] - - [25][26][27]
Blockchain [28] [29] [30]   [6][30][31][32]
Communication [33] [6] [34] [30] [9][35][36][37][38][39][40][41][42][43][44]
Farming - - [45][46] [46] [45][46]
Network [47][48][49] [50][51] [52] [53] [54]
RFID [55] [56] [57] [58] -
Smart IoT [59] - - - [56][60]
Mobile [61][62] - [62] - [61][62]
No. of Papers 17 9 11 7 29

2.1. Industrial

In the rapidly evolving landscape of Industrial Internet of Things (IIoT) authentication, a synthesis of noteworthy trends has materialized, reflecting a collaborative effort to bolster security, privacy, and efficiency. Embracing lightweight cryptography, Tanveer pioneers’ solutions address privacy concerns and computational constraints, facilitating secure communication in the IIoT [7][13]. The subsequent REAP-IIoT protocol introduces resource-efficient and privacy-preserving authentication. Ali’s contribution centers on an authenticated group shared key (AGSK) mechanism, leveraging hash functions and digital signatures to enhance IIoT network security [63]. Blockchain integration emerges as a pivotal trend, with Sharma proposing a secure authentication and privacy-preserving model [9]. Additionally, Zhang pioneers an IoT-based collaborative processing system on the blockchain, fostering efficiency through Verifiable Random Function (VRF) and reputation voting [16]. Privacy-preserving approaches are evident in Xu’s novel scheme, which employs fuzzy biometric extraction technology [11]. Devi’s efforts enhance IIoT throughput, reduce latency, and preserve privacy through smart contracts [64]. Efficient encryption techniques are pursued by Pu, aiming to optimize IIoT performance [10]. Dohare’s Certificateless Aggregated Signcryption Scheme (CLASS) introduces privacy-preserving data aggregation [15]. Zhang innovates consensus mechanisms in blockchain for IIoT [16].

2.2. Healthcare

Approaches to IoT authentication and several notable contributions in the healthcare domain have surfaced. El-Meniawy [33] addresses security and privacy concerns in medical data transmission within publicly accessible IT infrastructures by proposing a lightweight and secure authentication protocol for Medical Internet of Things (MIoT) networks. The protocol facilitates mutual authentication, real-time patient data monitoring, and access control policies, exhibiting exemplary computational efficiency. Liu [12] introduces a lightweight and secure redactable signature scheme for rapidly disseminating healthcare data in cloud-based IoT systems. The scheme ensures data integrity, authenticity, and privacy in resource-constrained IoT environments, offering solutions for privacy preservation, redaction control, and efficient authentication. Hasan [18] contributes to efficient medical data security by proposing a lightweight encryption technique for medical images in Internet of Medical Things (IoMT) applications. The approach prioritizes the privacy and security of medical data, demonstrating superior efficiency in image encryption execution time compared to conventional methods. Mehbodniya [19] develops a framework utilizing a modified Lamport Merkle Digital Signature method, employing a central healthcare controller (CHC) for signature validation and authentication. This framework achieves cost-effective and faster security compared to existing methods. Vinoth [22] presents a cloud-based session key agreement and data storage scheme with an improved authentication mechanism for MIoT, demonstrating resilience against various security attacks. Das [65] proposes a privacy-preserving mutual authentication scheme tailored for IoT-enabled healthcare systems, emphasizing lightweight and practical authentication for network devices. Deebak [21] introduces a seamless authentication framework with a privacy-preserving (SAF-PP) protocol to address security and privacy challenges in smart eHealth intelligence. The protocol utilizes lightweight cryptosystem operations, including hashing evaluation and MAC verification, to minimize computation and communication overhead.

2.3. Cloud and Fog

One prominent cluster revolves around the integration of lightweight cryptography, as exemplified by Rana’s work [20], which proposes a long-range IoT-based architecture for real-time vehicular pollution monitoring. This approach addresses environmental concerns and incorporates blockchain integration for enhanced information security and transparency. Another noteworthy cluster focuses on privacy-preserving techniques, with specific contributions not explicitly mentioned in the provided text. In efficient encryption, Gupta’s [27] proposal introduces an IoT device-specific, unique identity-based authentication method that utilizes lightweight procedures for identity-based encryption and is capable of detecting Distributed Denial of Service (DDoS) attacks. The cluster related to blockchain integration features Lansky’s [23] work, presenting a lightweight centralized authentication mechanism for IoT driven by Fog computing. This mechanism addresses security risks and privacy concerns while enhancing scalability and response time. Additionally, innovation approaches are evident in Saad’s [66] development of ThingsSentral TM, a lightweight IoT platform designed to provide a standalone cloud-based solution with a RESTful API, SQL-compliant databases, and modular infrastructure. Singh’s proposal [35] emphasizes secure device connections to servers’ mobiles, showcasing efficiency and high-security standards.

2.4. Blockchain

Several distinct clusters of trends emerge in the authentication domain for the Internet of Things (IoT), each contributing to the overarching goal of fortifying security, efficiency, and privacy. One significant cluster centers on the integration of blockchain technology. Anaam [28] delves into the fundamental understanding of how blockchain synergizes with IoT, shedding light on its crucial functions in securing data records within IoT systems. Khashan and Khafajah [31] propose a hybrid authentication architecture that combines centralized and blockchain-based elements to reduce authentication overhead while implementing lightweight encryption methods for constrained IoT devices. Al Ahmed [29] contributes to a decentralized blockchain solution by organizing IoT devices into clusters and employing a hierarchical structure for authentication, showcasing reduced computational loads in simulations. Ismail [67] presents a blockchain-based identity management and secure authentication mechanism for registering and authenticating nodes, ensuring secure wireless sensor network (WSN) communication.
Another cluster focuses on innovative approaches. Mahmoud [32] introduces a novel proof-of-identity algorithm tailored to the computational constraints of IoT devices. Tong [30] addresses cross-domain authentication challenges, offering functionalities such as intra-domain and cross-domain authentication, identity revocation, and pseudonym mechanisms for enhanced privacy protection. Additionally, Liu et al. [6] propose a blockchain-enabled decentralized information-sharing protocol for zero-trust IoT environments, emphasizing mutual authentication, fairness, and autonomy through smart contracts, eliminating the need for a trusted third party.

2.5. Communication

In the rapidly evolving landscape of IoT-based authentication, diverse trends have surfaced, highlighting innovative approaches to bolster security, privacy, and efficiency in this domain. Rangwani [33] leads the way with a Four-Factor Mutual Authentication and Key Agreement Protocol, establishing a foundation for robust security through formal verification and advanced logic models. Expanding into blockchain integration, Liu et al. [6] propose a decentralized information-sharing protocol, reshaping the paradigm by achieving mutual authentication and autonomy through smart contracts and eliminating reliance on trusted third parties.
Privacy-preserving methods find expression in Ataei Nezhad [34], who introduces an authentication-based secure data aggregation that addresses energy consumption and fortifies network security against malicious nodes. Tong’s [24] approach tackles cross-domain authentication challenges, emphasizing device privacy and offering comprehensive functionalities. Chen’s [30] novel authentication and key agreement protocol demonstrate resistance to various attacks and significant security and communication efficiency advantages through performance comparisons. Gong [36] introduces a lightweight authentication and key agreement protocol based on the CoAP framework, ensuring anonymity, robust security, and anti-attack capacity. It stands out for its unique security attributes and resistance to diverse attacks. Jiang’s [37] two private and mutual authentication protocols prioritize privacy protection, with the first employing a three-message key exchange protocol based on attribute-based encryption and the second opting for a one-round key exchange protocol for simplicity and efficiency.
Studies in [38][39][40][68][69][70], use an IoT device authentication scheme based on ambient access points, utilizing broadcast message data for authentication and affirming proximity between devices in an ad hoc IoT network. The authors in [41][42], both present a secure, lightweight authentication and key agreement protocol for IoT environments, achieving semantic security and critical properties like anonymity, robust synchronization, and forward security secrecy without using public-key cryptographic primitives. The authentication framework tailored for IoT-driven critical applications combines identity, password, and a digital signature scheme to save bandwidth and communication energy while reducing computing and communication costs for resource-constrained sensor nodes.

2.6. Farming

In IoT-based authentication tailored for specific applications, Rahimi [71] contributes to the innovation cluster by addressing challenges associated with urbanization, minimal land availability, and rising food demands. Their proposed solution involves designing and implementing an automatic monitoring system for an indoor vertical hydroponic system. This system optimizes land usage and integrates IoT technology to monitor essential plantation requirements efficiently. Carolina [45] adopts the OpenID Connect (OIDC) protocol on the privacy-preserving front, emphasizing secure federated authentication and authorization processes for both users and IoT devices. The protocol generates an ID Token, a JSON Web Token (JWT), housing various claims pertinent to user authentication, including identity and profile information.

2.7. Network

Wu [54] pioneers a game-theoretic approach to Physical Layer Authentication (PLA) for IoT, specifically addressing spoofing detection. Malik’s [47] work emphasizes the necessity for resource-efficient security mechanisms in IoT applications, proposing lightweight ECQV implicit certificates (L-ECQV) to optimize security for constrained devices. Leng [48] contributes with single-frame and multi-frame physical-layer authentication schemes using spreading code watermarking, streamlining authentication without complicated upper-layer protocols. Transitioning to Blockchain Integration, Chanal [49] adopts a Belief-Desire-Intention (BDI) server agency and the Random Forest (RF) algorithm to utilize context information for IoT object authentication. Yuan [50] introduces a hash-chain-based multi-node mutual authentication algorithm, showcasing superior running time and complexity performance in the testing environment.
For privacy-preserving measures, Shilpa’s [51] lightweight encryption algorithm and SEC-RMC protocol offer secure data transmission and mutual authentication in the IoT environment, achieving an impressive 80% reduction in transmission time. In the domain of efficient encryption, Goswami [52] presents an efficient scheme for remote registration and group authentication of IoT devices in 5G cellular networks. Compared to recent proposals, the proposed method seamlessly integrates with 5G-AKA, ensuring security and efficiency. In the field of innovation approaches, Hu’s [54] groundbreaking scheme introduces an elevated level of security while upholding computational efficiency. It represents a significant stride forward by attaining two-factor security and user anonymity amid sensor node-captured attacks, demonstrating a pioneering approach to IoT authentication.

2.8. RFID

In the context of RFID-based IoT authentication, several noteworthy trends are emerging to tackle the distinctive challenges posed by highly constrained devices. Rostampour [55] introduces a novel lightweight authentication protocol based on AEAD encryption schemes specifically designed to secure highly constrained IoT devices. The study showcases the protocol’s efficiency in meeting the lightweight requirements for secure solutions in constrained IoT environments. Contributing to this trend, Alshawish [56] presents an efficient IoT authentication scheme that achieves mutual authentication among three entities within the IoT system: IoT devices, an IoT manufacturer server, and an authentication server. This multi-entity authentication approach adds an extra layer of security to RFID-based IoT systems. Pahlevi [57] explores a secure mutual authentication protocol utilizing two-factor RFID and fingerprint authentication through the MQTT protocol. The protocol attains optimal FAR and FRR at an 80% threshold, demonstrating robust performance with an Equal Error Rate (ERR) of approximately 59.5%.
Moreover, the protocol undergoes testing against brute force and sniffing attacks, highlighting its resilience to various security threats. Ghasemi [58] introduces a new lightweight authentication approach for RFID-based IoT, employing stream ciphering techniques to enhance privacy between legitimate components. The study focuses on providing forward security and resisting various attacks such as eavesdropping, tag tracking, replay, cloning, and DoS attacks. These trends underscore the ongoing endeavors to develop lightweight, efficient, and secure authentication protocols tailored for RFID-based IoT applications.

2.9. Smart IoT

The concept of Smart IoT is being advocated to elevate security measures and enable secure data transmission. Annadurai [59] introduces an innovative technique to enhance the security of biometric authentication systems. This approach integrates biometric authentication, artificial intelligence, and the Internet of Things (IoT) to attain secure data transmission and efficient intruder detection. The proposed approach stands out for its focus on lightweight cryptographic methods, ensuring efficient and secure communication within the biometric authentication framework.
Regarding Efficient Encryption, Annadurai [25] emphasizes the importance of secure data transmission in a biometric authentication system, underscoring the significance of efficient encryption methods to fortify overall system security. Regarding innovation approaches, Chen [48] proposes an authentication scheme tailored for smart IoT applications. This scheme supports mutual authentication among devices, back-end servers, and users’ mobile applications, covering the entire device lifecycle. Additionally, Alshawish [53] contributes to innovation in IoT authentication by presenting an efficient scheme that achieves mutual authentication among various entities within the IoT system.

2.10. Mobile

Two notable trends are emerging to address privacy concerns and enhance user verification in mobile authentication for IoT. Wazzeh [61] introduces a privacy-preserving continuous authentication framework that enables users to verify behavioural data continuously. This is achieved through a novel Federated Learning approach coupled with a warm-up strategy designed to enhance the model weights of clients. The innovation lies in accommodating non-independent and non-identically distributed (non-IID) data, leading to improved performance for authentication models. Gong [60] contributes to the trends by proposing a lightweight cross-domain mutual identity authentication scheme designed explicitly for mobile IoT devices. This scheme surpasses existing methods by leveraging the constrained resources of mobile nodes and authentication servers, ensuring low computation and communication overhead. This innovative approach is tailored for the dynamic and resource-constrained mobile IoT environment.

3. Advantages of Each Type of Authentication in IoT

In the expansive field of Internet of Things (IoT) research, numerous studies spanning diverse domains have presented significant advantages for contemporary researchers delving into the authentication of IoT. The benefits elucidated in most of these research works are systematically categorized as follows:

3.1. Security and Reliability

Most research works, such as [7][25][29][56][59][70], emphasized the authentication schemes for IoT that offer high security and reliability and demonstrate resilience against various attacks. Various techniques applied to boost security and transparency include the integration of hardware with a blockchain network, the authenticated group shared key (AGSK) mechanism, and the public key infrastructure (PKI) digital certificate [20][34][63]. The study [24] prioritized security by providing the capability to track and penalize malicious anonymous devices. These advantages impede the prompt availability of crucial information, potentially influencing decision-making processes.

3.2. Performance Efficiency

A low computation overhead, influenced by factors such as computational cost, storage space, communication cost, and power consumption, as evidenced in [23][60][63] has the potential to result in high-performance efficiency. As noted in [43], employing a predetermined route and hop-by-hop encryption and authentication can decrease the delay in data transmission, thereby reducing end-to-end delay. The high-performance efficiency of the IoT environment holds the potential to attract users for adoption across various applications.

3.3. Decentralization and Fairness

Decentralization is a key advantage offered by the authentication protocol, which functions independently of a trusted third party. This ensures autonomy and eliminates single points of failure, as indicated in [31]. Simultaneously, fairness is ensured through the protocol’s inclusion of a voting mechanism with built-in consensus and penalty capabilities. This enables the detection and filtration of fabricated information, allowing for the penalization and blacklisting of misbehaving users [6][20].

3.4. Privacy Protection

Some research includes [12][13][37][47] introducing protocols for preserving the privacy of IoT devices and environments. For example, a lightweight encryption technique that enhances the privacy of medical images and industrial networks [15][18][33]. Overlooking the safeguarding of privacy aspects in IoT applications may result in the inadvertent leakage of crucial information to unauthorized individuals.

3.5. Real-Time Monitoring

The protocol highlighted in references [20][33][71] introduces a dynamic system that enables real-time monitoring of patient data, vehicular pollution, and the agriculture and forestry sectors. This feature not only reduces patient waiting times, enhancing the overall efficiency of healthcare services, but also contributes to more prompt and responsive medical interventions, plays a crucial role in environmental stewardship, and facilitates easy monitoring of essential plantation necessities.

3.6. Mutual Authentication

The attainment of mutual authentication is crucial to guaranteeing that participant entities remain updated and synchronized at least once upon the completion of a correct session. The research introduces an authentication scheme specifically designed for smart IoT applications. This proposed scheme facilitates mutual authentication among devices, back-end servers, and users’ mobile applications [8][59]. Failure of mutual authentication may lead to a range of consequences, including unauthorized access, data integrity risks, and potential security vulnerabilities within the IoT ecosystem.

3.7. Flexibility and Scalability

Some works are directed towards enhancing flexibility, with a particular focus on the system’s ability to function effectively on embedded devices [43][66]. This signifies a deliberate effort to optimize and adapt the technology for use in resource-constrained environments, such as those commonly found in embedded systems. The deployment of a lightweight centralized authentication mechanism tailored for the Internet of Things (IoT) in Fog computing holds significant promise for improving scalability. By fostering scalability, the utilization of resources can be optimized, and processing delays can be minimized.

3.8. Availability of Source Code

The open-source development of authentication protocols, as exemplified in the case discussed in [57], contributes to simplifying research endeavors. Open-source protocols provide researchers with accessible frameworks, tools, and codebases that can be examined, modified, and built upon for their specific needs and allow for transparency and peer review. Researchers can analyze the code, pinpoint potential vulnerabilities, and suggest enhancements, fostering a collaborative and iterative approach to protocol development. This joint effort contributes to the overall robustness and reliability of authentication mechanisms.

References

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Subjects: Computer Science, Information Systems
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
Nazhatul Hafizah Kamarudin
,
Nur Hanis Sabrina Suhaimi
,
Fadilla Atyka Nor Rashid
,
Mohd Nor Akmal Khalid
,
Fazlina Mohd Ali
View Times: 126
Revisions: 2 times (View History)
Update Date: 08 Feb 2024
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