Secure Healthcare Data Aggregation and Deduplication Scheme for FoG-Orineted IoT

Data aggregation scheme for IOT based wireless sensor network through optimal clustering method

Introduction: Nowadays, fog computing has emerged as a promising solution for handling the prompt processing of tasks in Internet of Things (IoT)-based applications. One of the key advantages of fog computing is that it reduces service completion time by offloading tasks from IoT devices to the fog server. Therefore, scheduling of tasks becomes vital, where emergency and non-emergency tasks can be prioritized to offload data to the nearby fog servers, which improves the Quality of Service (QoS). Due to the dynamic nature of the IoT environment, traffic load varies over time, making it difficult to select the optimal fog server for task offloading. Objectives: This research introduces a novel task offloading for the Fog Cloud scenario using the improved Coati Optimization Algorithm based on Genetic Operators (ICOA-GO) algorithm. Methods: Initially, the Delay aware Four Queue model with Fuzzy logic (DFQM-Fuzz) is designed to queue incoming tasks into four different priorities. In the DFQM-Fuzz, Highly urgent (HU) and Urgent (U) tasks are considered as first and second priorities and those tasks are offloaded through the Fog Server. The Non Urgent (NU) and No Deadline (ND) tasks are offloaded through the Cloud Server. Furthermore, when there is no resource to offload through the Fog Server, the task is offloaded through the Cloud Server. Results: The proposed improved Coati Optimization Algorithm based on Genetic Operators (ICOA-GO) algorithm optimizes the selection of Cloud and Fog Servers. The analysis based on Energy Utilization, Task Rejection Ratio, and Makespan yielded values of 93.589, 1, and 1.96073. Conclusions: By integrating the DFQM-Fuzz and ICOA-GO improves task prioritizing and offloading efficiency while reducing execution time, energy consumption, and cost.

With its advantages are gradually emerging, the Internet of Things (IoT) is profoundly changing the way people work and live. Among all IoT applications, medical IoT is partic-ularly important, in which the user can communicate with smart medical device through the hospital gateway node. However, due to the inherent defects of these smart devices and the openness of wireless networks, medical IoT is vulnerable to kinds of attacks, such as impersonation attack and password guessing attack. Unfortunately, there are few authentication schemes for medical IoT at present, while existing three-party schemes have various weakness and are not suitable for medical IoT. Given the sensitivity of patient data and the deadly consequences of attacks on medical devices, there is an urgent need to develop a suitable authentication scheme in Medical IoT Network with high security. To alleviate the above problems, a robust ECC based three-party authentication and key agreement scheme for medical IoT(RAKI) has been proposed, which is secure with random oracle model and the informal security analysis. Besides, the performance comparisons against existing competing three-party schemes indicate that our scheme is efficient for medical IoT.

The Internet of Things (IoT) technology has revolutionized the world where anything is smartly connected and is accessible. The IoT makes use of cloud computing for processing and storing huge amounts of data. In some way, the concept of fog computing has emerged between cloud and IoT devices to address the issue of latency. When a fog node exchanges data for completing a particular task, there are many security and privacy risks. For example, offloading data to a rogue fog node might result in an illegal gathering or modification of users' private data. In this paper, we rely on trust to detect and detach bad fog nodes. We use a Mamdani fuzzy method and we consider a hospital scenario with many fog servers. The aim is to identify the malicious fog node. Metrics such as latency and distance are used in evaluating the trustworthiness of each fog server. The main contribution of this study is identifying how fuzzy logic configuration could alter the trust value of fog nodes. The experimental results show that our method detects the bad fog device and establishes its trustworthiness in the given scenario.

Guaranteeing quality of service (QoS) to transmit real time applications which are delay sensitive is of utmost importance in Internet of Things (IoT) environment. This paper presents a dynamic Markov Chain based scheduling scheme for ensuring QoS for the delay sensitive traffic in IoT. The traffic is classified into prioritized and non- prioritized traffic. By estimating previous bandwidth allocated to prioritized traffic and the amount of decrease/increase in probability of average queue length of prioritized packets in consecutive cycles, the scheduler dynamically adjusts the percentage of link bandwidth allocated to it in each cycle. This helps in providing guaranteed services to real time traffic in IoT applications and simultaneously provide better throughput for non real time traffic as well. The proposed QoS- alert scheduling mechanism is able to optimize the desired performance in IoT network. For different experiments the simulation is performed which verifies and satisfies the blocking probability requirements of prioritized traffic for IoT data.

Purpose – The purpose of this paper is to study lightweight security scheme for Internet of Things (IoT) applications using Constrained Application Protocol (CoAP). Resource-constrained characteristics of IoT systems have ushered in compelling requirements for lightweight application protocol and security suites. CoAP has already been established as the candidate protocol for IoT systems. However, low overhead security scheme for CoAP is still an open problem. Existing security solutions like Datagram Transport Layer Security (DTLS) is not suitable, particularly due to its expensive handshaking, public key infrastructure (PKI)-based authentication and lengthy ciphersuite agreement process. Design/methodology/approach – This paper proposes a lightweight security scheme in CoAP using Advanced Encryption Standard (AES) 128 symmetric key algorithm. The paper presents an object security (payload embedded)-based robust authentication mechanism with integrated key management. The paper introduces few unique modifications to CoAP header to optimize security operation and minimize communication cost. Findings – It is resilient to number of security attacks like replay attack, meet-in-the-middle attack and secure under chosen plaintext attack. This scheme is generic in nature, applicable for gamut of IoT applications. The paper proves efficacy of our proposed scheme for vehicle tracking application in emulated laboratory setup. Specifically, it compares with DTLS-enabled CoAP to establish the lightweight feature of our proposed solution. Research limitations/implications – This paper mainly focuses on implementing in-vehicle tracking systems as an IoT application and used CoAP as the application protocol. Practical implications – Such a lightweight security scheme would provide immense benefit in IoT systems so that resource constraint-sensing devices and nodes can be made secure. This would impact IoT eco systems to a large extent. Originality/value – Such kind of security suite that provides both robustness and lightweight feature is hitherto not known to the authors, particularly in CoAP for IoT applications.

The Internet of Things (IoT) is a disruptive technology that underpins Industry 5.0 by integrating various service technologies to enable intelligent connectivity among smart objects. These technologies enhance the convergence of Information Technology (IT), Operational Technology (OT), Core Technology (CT), and Data Technology (DT) networks, improving automation and decision-making capabilities. While cloud computing has become a mainstream technology across multiple domains, it struggles to efficiently manage the massive volume of OT data generated by IoT devices due to high latency, data transfer costs, limited resilience, and insufficient context awareness. Fog computing has emerged as a viable solution, extending cloud capabilities to the edge through a distributed peer-to-peer (P2P) network, enabling decentralized data processing and management. However, IoT networks still face critical challenges, including connectivity, heterogeneity, scalability, interoperability, security, and real-time decision-making constraints. Security is a key challenge in IoT implementations, including secure data communication, IoT edge and fog device identity, end-to-end authentication, and secure storage. This paper presents an efficient blockchain-based framework that creates a secure end-to-end communication cooperative flow IoT network. The framework utilizes a hybrid blockchain network that collaborates to offer a collaborative flow of end-to-end secure communication from end devices to cloud storage. The fog servers will maintain a private blockchain as a next-generation public key infrastructure to identify and authenticate the IoT’s edge devices. The consortium blockchain will be maintained in the cloud and integrated with the permission blockchain system. This system ensures secure cloud storage, authorization, efficient key exchange, and remote protection (encryption) of all sensitive information. To improve the synchronization and block generation, reduce overhead, and ensure scalable IoT network operation, we proposed the threshold signature-based Proof of Stake and Validation (PoSV) consensus. Additionally, lightweight authentication protects resource-constrained IoT nodes using an aggregate signature, ensuring security and performance in real-time scenarios. The proposed system is implemented, and its performance is evaluated using key metrics such as cryptographic processing overhead, consensus efficiency, block acceptance time, and transaction delay. The findings show that threshold signature-based Proof of Stake and Validation (PoSV) consensus, reduces the computational burden of individual signature verification, which results in an optimized transaction latency of 80–150 ms, compared to the previous 100–200 ms without Non-PoSV. Additionally, aggregating multiple signatures from different authentication events reduces signing time by 1.98 ms compared to the individual signature time of 2.72 ms and the overhead of verifying multiple individual transactions is 2.87 ms is significantly reduced to1.46 ms along with authentication delay ranges between 95–180 ms. Hence, the proposed framework improves over existing approaches regarding linear computing complexity, increased cryptographic methods, and a more efficient consensus process.

The IoT is innovative and important phenomenon prone to several services and applications such as the blockchain, but it should consider the legal issues related to the data protection law. We should be taken into account the legal issues related to the data protection and privacy law. Technological solutions are welcome, but it is necessary, before developing applications, to consider the risks which we cannot dismiss. Personal data is a value. It is important to evaluate the European Regulation n. 679/2016, European General Data Protection Regulation (GDPR) that will enter into force on 25 May 2018. The GDPR introduces Data Protection by Design and by Default, Data Protection Impact Assessment (DPIA), data breach notification and significant administrative fines in respect of infringements of the Regulation. It is fundamental to evaluate the legal issues and prevent them, adopting in each project the Data Protection by Design approach. Regarding the data protection and security risks, there are some issues with potential consequences for data and liability. A correct law analysis allows evaluating risks preventing the wrong use of personal data. The contribution describes the main legal issues related to privacy and data protection focusing on the Privacy by Design approach, according to the GDPR.

The Internet of Things (IoT) becomes the future of a global data field in which the embedded devices communicate with each other, exchange data and making decisions through the Internet. IoT could improve the quality of life in smart cities, but a massive amount of data from different smart devices could slow down or crash database systems. In addition, IoT data transfer to Cloud for monitoring information and generating feedback that will lead to high delay in infrastructure level. Fog Computing can help by offering services closer to edge devices. In this paper, we propose an efficient system architecture to mitigate the problem of delay. We provide performance analysis like response time, throughput and packet loss for MQTT (Message Queue Telemetry Transport) and HTTP (Hyper Text Transfer Protocol) protocols based on Cloud or Fog servers with large volume of data from emulated traffic generator working alongside one real sensor . We implement both protocols in the same architecture, with low cost embedded devices to local and Cloud servers with different platforms. The results show that HTTP response time is 12.1 and 4.76 times higher than MQTT Fog and Cloud based located in the same geographical area of the sensors respectively. The worst case in performance is observed when the Cloud is public and outside the country region. The results obtained for throughput shows that MQTT has the capability to carry the data with available bandwidth and lowest percentage of packet loss. We also prove that the proposed Fog architecture is an efficient way to reduce latency and enhance performance in Cloud based IoT.

The devices of Internet of Things (IoT) will grow rapidly in the near future, and the power consumption and radio spectrum management will become the most critical issues in the IoT networks. Long Term Evolution (LTE) technology will become a promising technology used in IoT networks due to its flat architecture, all-IP network, and greater spectrum efficiency. The 3rd Generation Partnership Project (3GPP) specified the Discontinuous Reception (DRX) to reduce device’s power consumption. However, the DRX may pose unexpected communication delay due to missing Physical Downlink Control Channel (PDCCH) information in sleep mode. Recent studies mainly focus on optimizing DRX parameters to manage the tradeoff between the energy consumption and communication latency. In this paper, we proposed a fuzzy-based power saving scheduling scheme for IoT over the LTE/LTE-Advanced networks to deal with the issues of the radio resource management and power consumption from the scheduling and resource allocation perspective. The proposed scheme considers not only individual IoT device’s real-time requirement but also the overall network performance. The simulation results show that our proposed scheme can meet the requirements of the DRX cycle and scheduling latency and can save about half of energy consumption for IoT devices compared to conventional approaches.

The Internet of Things (IoT) with cloud services are important functionalities in the latest IoT systems for providing various convenient services. These cloud-enabled IoT environments collect, analyze, and monitor surrounding data, resulting in the most effective handling of large amounts of heterogeneous data. In these environments, secure authentication with a key agreement mechanism is essential to ensure user and data privacy when transmitting data between the cloud server and IoT nodes. In this study, we prove that the previous scheme contains various security threats, and hence cannot guarantee essential security requirements. To overcome these security threats, we propose an improved authentication and key agreement scheme for cloud-enabled IoT using PUF. Furthermore, we evaluate its security by performing informal, formal (mathematical), and simulation analyses using the AVISPA tool and ROR model. The performance and security properties of our scheme are subsequently compared with those of other related schemes. The comparison confirms that our scheme is suitable for a practical cloud-enabled IoT environment because it provides a superior security level and is more efficient than contemporary schemes.

Modeling a complete Internet of Things (IoT) infrastructure is crucial to assess its availability and security characteristics. However, modern IoT infrastructures often consist of a complex and heterogeneous architecture and thus taking into account both architecture and operative details of the IoT infrastructure in a monolithic model is a challenge for system practitioners and developers. In that regard, we propose a hierarchical modeling framework for the availability and security quantification of IoT infrastructures in this paper. The modeling methodology is based on a hierarchical model of three levels including (i) reliability block diagram (RBD) at the top level to capture the overall architecture of the IoT infrastructure, (ii) fault tree (FT) at the middle level to elaborate system architectures of the member systems in the IoT infrastructure, and (iii) continuous time Markov chain (CTMC) at the bottom level to capture detailed operative states and transitions of the bottom subsystems in the IoT infrastructure. We consider a specific case-study of IoT smart factory infrastructure to demonstrate the feasibility of the modeling framework. The IoT smart factory infrastructure is composed of integrated cloud, fog, and edge computing paradigms. A complete hierarchical model of RBD, FT, and CTMC is developed. A variety of availability and security measures are computed and analyzed. The investigation of the case-study’s analysis results shows that more frequent failures in cloud cause more severe decreases of overall availability, while faster recovery of edge enhances the availability of the IoT smart factory infrastructure. On the other hand, the analysis results of the case-study also reveal that cloud servers’ virtual machine monitor (VMM) and virtual machine (VM), and fog server’s operating system (OS) are the most vulnerable components to cyber-security attack intensity. The proposed modeling and analysis framework coupled with further investigation on the analysis results in this study help develop and operate the IoT infrastructure in order to gain the highest values of availability and security measures and to provide development guidelines in decision-making processes in practice.

The Internet of Things (IoT) has attracted much attention in many fields, such as healthcare, transportation, finance and other critical infrastructures. But how to ensure the security of whole IoT system and the privacy of users has always been a challenge. Physical layer as the cornerstone of IoT, appears to be a promising direction for enhancing the security of IoT. As a consequence, we propose a novel chaotic physical layer security transmission scheme in the OFDM-based IoT transmission system. By encrypting the Discrete Fourier Transform (DFT) matrix, the proposed scheme not only provides the confidentiality of physical layer information transmission, but also effectively addresses the issues on the extreme high PAPR of the OFDM symbols. Moreover, it does not require any additional sideband information and has low computational complexity in theory. Compared with other existing schemes, the proposed scheme achieves the higher confidentiality of information transmission with the capability to resist chosen-plaintext attacks, statistical-attacks, and brute-force attacks simultaneously.

A secure and efficient authentication and data sharing scheme for Internet of Things based on blockchain

With the rapid development of information technology, Internet of Things (IoT) is profoundly impacting various fields of the socio-economic landscape, driving the transformation of traditional industries towards intelligence. However, the widespread application of IoT has also led to a surge in electronic evidence, whose importance in the judicial field is increasingly prominent, but its characteristics such as ease of replication and leakage have posed new challenges for privacy protection. This paper focuses on the security and privacy issues of electronic evidence in IoT and proposes an efficient and secure interaction scheme based on chebyshev chaotic map, hash functions and XOR operations. Through a secure two-factor authentication mechanism, this scheme achieves identity verification between the user and the storage center, as well as confidentiality during the data transmission process. This has significant implications for the healthy development of IoT, judicial fairness and personal privacy protection. Experimental and theoretical analysis shows that the proposed scheme not only effectively resists various known attacks, but also performs excellently in terms of communication and computation costs, making it well-suited for IoT.