684 research outputs found

    Efficient data uncertainty management for health industrial internet of things using machine learning

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    [EN] In modern technologies, the industrial internet of things (IIoT) has gained rapid growth in the fields of medical, transportation, and engineering. It consists of a self-governing configuration and cooperated with sensors to collect, process, and analyze the processes of a real-time system. In the medical system, healthcare IIoT (HIIoT) provides analytics of a huge amount of data and offers low-cost storage systems with the collaboration of cloud systems for the monitoring of patient information. However, it faces certain connectivity, nodes failure, and rapid data delivery challenges in the development of e-health systems. Therefore, to address such concerns, this paper presents an efficient data uncertainty management model for HIIoT using machine learning (EDM-ML) with declining nodes prone and data irregularity. Its aim is to increase the efficacy for the collection and processing of real-time data along with smart functionality against anonymous nodes. It developed an algorithm for improving the health services against disruption of network status and overheads. Also, the multi-objective function decreases the uncertainty in the management of medical data. Furthermore, it expects the routing decisions using a machine learning-based algorithm and increases the uniformity in health operations by balancing the network resources and trust distribution. Finally, it deals with a security algorithm and established control methods to protect the distributed data in the exposed health industry. Extensive simulations are performed, and their results reveal the significant performance of the proposed model in the context of uncertainty and intelligence than benchmark algorithms.This research is supported by Artificial Intelligence & Data Analytics Lab (AIDA) CCIS Prince Sultan University, Riyadh Saudi Arabia. Authors are thankful for the support.Haseeb, K.; Saba, T.; Rehman, A.; Ahmed, I.; Lloret, J. (2021). Efficient data uncertainty management for health industrial internet of things using machine learning. International Journal of Communication Systems. 34(16):1-14. https://doi.org/10.1002/dac.4948114341

    Security and Privacy Issues in Wireless Mesh Networks: A Survey

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    This book chapter identifies various security threats in wireless mesh network (WMN). Keeping in mind the critical requirement of security and user privacy in WMNs, this chapter provides a comprehensive overview of various possible attacks on different layers of the communication protocol stack for WMNs and their corresponding defense mechanisms. First, it identifies the security vulnerabilities in the physical, link, network, transport, application layers. Furthermore, various possible attacks on the key management protocols, user authentication and access control protocols, and user privacy preservation protocols are presented. After enumerating various possible attacks, the chapter provides a detailed discussion on various existing security mechanisms and protocols to defend against and wherever possible prevent the possible attacks. Comparative analyses are also presented on the security schemes with regards to the cryptographic schemes used, key management strategies deployed, use of any trusted third party, computation and communication overhead involved etc. The chapter then presents a brief discussion on various trust management approaches for WMNs since trust and reputation-based schemes are increasingly becoming popular for enforcing security in wireless networks. A number of open problems in security and privacy issues for WMNs are subsequently discussed before the chapter is finally concluded.Comment: 62 pages, 12 figures, 6 tables. This chapter is an extension of the author's previous submission in arXiv submission: arXiv:1102.1226. There are some text overlaps with the previous submissio

    IoT Security Evolution: Challenges and Countermeasures Review

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    Internet of Things (IoT) architecture, technologies, applications and security have been recently addressed by a number of researchers. Basically, IoT adds internet connectivity to a system of intelligent devices, machines, objects and/or people. Devices are allowed to automatically collect and transmit data over the Internet, which exposes them to serious attacks and threats. This paper provides an intensive review of IoT evolution with primary focusing on security issues together with the proposed countermeasures. Thus, it outlines the IoT security challenges as a future roadmap of research for new researchers in this domain

    An authentic-based privacy preservation protocol for smart e-healthcare systems in iot

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    © 2013 IEEE. Emerging technologies rapidly change the essential qualities of modern societies in terms of smart environments. To utilize the surrounding environment data, tiny sensing devices and smart gateways are highly involved. It has been used to collect and analyze the real-time data remotely in all Industrial Internet of Things (IIoT). Since the IIoT environment gathers and transmits the data over insecure public networks, a promising solution known as authentication and key agreement (AKA) is preferred to prevent illegal access. In the medical industry, the Internet of Medical Things (IoM) has become an expert application system. It is used to gather and analyze the physiological parameters of patients. To practically examine the medical sensor-nodes, which are imbedded in the patient\u27s body. It would in turn sense the patient medical information using smart portable devices. Since the patient information is so sensitive to reveal other than a medical professional, the security protection and privacy of medical data are becoming a challenging issue of the IoM. Thus, an anonymity-based user authentication protocol is preferred to resolve the privacy preservation issues in the IoM. In this paper, a Secure and Anonymous Biometric Based User Authentication Scheme (SAB-UAS) is proposed to ensure secure communication in healthcare applications. This paper also proves that an adversary cannot impersonate as a legitimate user to illegally access or revoke the smart handheld card. A formal analysis based on the random-oracle model and resource analysis is provided to show security and resource efficiencies in medical application systems. In addition, the proposed scheme takes a part of the performance analysis to show that it has high-security features to build smart healthcare application systems in the IoM. To this end, experimental analysis has been conducted for the analysis of network parameters using NS3 simulator. The collected results have shown superiority in terms of the packet delivery ratio, end-to-end delay, throughput rates, and routing overhead for the proposed SAB-UAS in comparison to other existing protocols

    Reliable Bidirectional Data Transfer Approach for the Internet of Secured Medical Things Using ZigBee Wireless Network

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    [EN] Nowadays, the Internet of Things (IoT) performs robust services for real-time applications in monitoring communication systems and generating meaningful information. The ZigBee devices offer low latency and manageable costs for wireless communication and support the process of physical data collection. Some biosensing systems comprise IoT-based ZigBee devices to monitor patient healthcare attributes and alert healthcare professionals for needed action. However, most of them still face unstable and frequent data interruption issues due to transmission service intrusions. Moreover, the medical data is publicly available using cloud services, and communicated through the smart devices to specialists for evaluation and disease diagnosis. Therefore, the applicable security analysis is another key factor for any medical system. This work proposed an approach for reliable network supervision with the internet of secured medical things using ZigBee networks for a smart healthcare system (RNM-SC). It aims to improve data systems with manageable congestion through load-balanced devices. Moreover, it also increases security performance in the presence of anomalies and offers data routing using the bidirectional heuristics technique. In addition, it deals with more realistic algorithm to associate only authorized devices and avoid the chances of compromising data. In the end, the communication between cloud and network applications is also protected from hostile actions, and only certified end-users can access the data. The proposed approach was tested and analyzed in Network Simulator (NS-3), and, compared to existing solutions, demonstrated significant and reliable performance improvements in terms of network throughput by 12%, energy consumption by 17%, packet drop ratio by 37%, end-to-end delay by 18%, routing complexity by 37%, and tampered packets by 37%.This research is supported by Artificial Intelligence & Data Analytics Lab (AIDA) CCIS Prince Sultan University, Riyadh, Saudi Arabia. Authors are thankful for the support.Rehman, A.; Haseeb, K.; Fati, SM.; Lloret, J.; Peñalver Herrero, ML. (2021). Reliable Bidirectional Data Transfer Approach for the Internet of Secured Medical Things Using ZigBee Wireless Network. Applied Sciences. 11(21):1-16. https://doi.org/10.3390/app11219947S116112

    Lightweight and Practical Anonymous Authentication Protocol for RFID systems using physically unclonable functions

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    Radio frequency identification (RFID) has been considered one of the imperative requirements for implementation of Internet-of-Things applications. It helps to solve the identification issues of the things in a cost-effective manner, but RFID systems often suffer from various security and privacy issues. To solve those issues for RFID systems, many schemes have been recently proposed by using the cryptographic primitive, called physically uncloneable functions (PUFs), which can ensure a tamper-evident feature. However, to the best of our knowledge, none of them has succeeded to address the problem of privacy preservation with the resistance of DoS attacks in a practical way. For instance, existing schemes need to rely on exhaustive search operations to identify a tag, and also suffer from several security and privacy related issues. Furthermore, a tag needs to store some security credentials (e.g., secret shared keys), which may cause several issues such as loss of forward and backward secrecy and large storage costs. Therefore, in this paper, we first propose a lightweight privacy-preserving authentication protocol for the RFID system by considering the ideal PUF environment. Subsequently, we introduce an enhanced protocol which can support the noisy PUF environment. It is argued that both of our protocols can overcome the limitations of existing schemes, and further ensure more security properties. By analyzing the performance, we have shown that the proposed solutions are secure, efficient, practical, and effective for the resource-constraint RFID tag

    Security for networked smart healthcare systems: A systematic review

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    Background and Objectives Smart healthcare systems use technologies such as wearable devices, Internet of Medical Things and mobile internet technologies to dynamically access health information, connect patients to health professionals and health institutions, and to actively manage and respond intelligently to the medical ecosystem's needs. However, smart healthcare systems are affected by many challenges in their implementation and maintenance. Key among these are ensuring the security and privacy of patient health information. To address this challenge, several mitigation measures have been proposed and some have been implemented. Techniques that have been used include data encryption and biometric access. In addition, blockchain is an emerging security technology that is expected to address the security issues due to its distributed and decentralized architecture which is similar to that of smart healthcare systems. This study reviewed articles that identified security requirements and risks, proposed potential solutions, and explained the effectiveness of these solutions in addressing security problems in smart healthcare systems. Methods This review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines and was framed using the Problem, Intervention, Comparator, and Outcome (PICO) approach to investigate and analyse the concepts of interest. However, the comparator is not applicable because this review focuses on the security measures available and in this case no comparable solutions were considered since the concept of smart healthcare systems is an emerging one and there are therefore, no existing security solutions that have been used before. The search strategy involved the identification of studies from several databases including the Cumulative Index of Nursing and Allied Health Literature (CINAL), Scopus, PubMed, Web of Science, Medline, Excerpta Medical database (EMBASE), Ebscohost and the Cochrane Library for articles that focused on the security for smart healthcare systems. The selection process involved removing duplicate studies, and excluding studies after reading the titles, abstracts, and full texts. Studies whose records could not be retrieved using a predefined selection criterion for inclusion and exclusion were excluded. The remaining articles were then screened for eligibility. A data extraction form was used to capture details of the screened studies after reading the full text. Of the searched databases, only three yielded results when the search strategy was applied, i.e., Scopus, Web of science and Medline, giving a total of 1742 articles. 436 duplicate studies were removed. Of the remaining articles, 801 were excluded after reading the title, after which 342 after were excluded after reading the abstract, leaving 163, of which 4 studies could not be retrieved. 159 articles were therefore screened for eligibility after reading the full text. Of these, 14 studies were included for detailed review using the formulated research questions and the PICO framework. Each of the 14 included articles presented a description of a smart healthcare system and identified the security requirements, risks and solutions to mitigate the risks. Each article also summarized the effectiveness of the proposed security solution. Results The key security requirements reported were data confidentiality, integrity and availability of data within the system, with authorisation and authentication used to support these key security requirements. The identified security risks include loss of data confidentiality due to eavesdropping in wireless communication mediums, authentication vulnerabilities in user devices and storage servers, data fabrication and message modification attacks during transmission as well as while the data is at rest in databases and other storage devices. The proposed mitigation measures included the use of biometric accessing devices; data encryption for protecting the confidentiality and integrity of data; blockchain technology to address confidentiality, integrity, and availability of data; network slicing techniques to provide isolation of patient health data in 5G mobile systems; and multi-factor authentication when accessing IoT devices, servers, and other components of the smart healthcare systems. The effectiveness of the proposed solutions was demonstrated through their ability to provide a high level of data security in smart healthcare systems. For example, proposed encryption algorithms demonstrated better energy efficiency, and improved operational speed; reduced computational overhead, better scalability, efficiency in data processing, and better ease of deployment. Conclusion This systematic review has shown that the use of blockchain technology, biometrics (fingerprints), data encryption techniques, multifactor authentication and network slicing in the case of 5G smart healthcare systems has the potential to alleviate possible security risks in smart healthcare systems. The benefits of these solutions include a high level of security and privacy for Electronic Health Records (EHRs) systems; improved speed of data transaction without the need for a decentralized third party, enabled by the use of blockchain. However, the proposed solutions do not address data protection in cases where an intruder has already accessed the system. This may be potential avenues for further research and inquiry

    Tactical approach to identify and quarantine spurious node participation request in sensory application

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    Securing Wireless Sensor Network (WSN) from variable forms of adversary is still an open end challenge. Review of diversified security apprroaches towards such problems that they are highly symptomatic with respect to resiliency strength against attack. Therefore, the proposed system highlights a novel and effective solution that is capable of identify the spurios request for participating in teh network building process from attacker and in return could deviate the route of attacker to some virtual nodes and links. A simple trust based mechanism is constructed for validating the legitimacy of such request generated from adversary node. The proposed system not only presents a security solution but also assists in enhancing the routing process significantly. The simulated outcome of the study shows that proposed system offers significantly good energy conservation, satisfactory data forwarding performance, reduced processing time in contrast to existing standard security practices

    AUTHENTICATED KEY ESTABLISHMENT PROTOCOL FOR CONSTRAINED SMART HEALTHCARE SYSTEMS BASED ON PHYSICAL UNCLONABLE FUNCTION

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    Smart healthcare systems are one of the critical applications of the internet of things. They benefit many categories of the population and provide significant improvement to healthcare services. Smart healthcare systems are also susceptible to many threats and exploits because they run without supervision for long periods of time and communicate via open channels. Moreover, in many implementations, healthcare sensor nodes are implanted or miniaturized and are resource-constrained. The potential risks on patients/individuals’ life from the threats necessitate that securing the connections in these systems is of utmost importance. This thesis provides a solution to secure end-to-end communications in such systems by proposing an authenticated key establishment protocol. The main objective of the protocol is to examine how physical unclonable functions could be utilized as a lightweight root of trust. The protocol’s design is based on rigid security requirements and inspired by the vulnerability of physical unclonable function to machine learning modeling attacks as well as the use of a ratchet technique. The proposed protocol verification and analysis revealed that it is a suitable candidate for resource-constrained smart healthcare systems. The proposed protocol’s design also has an impact on other important aspects such as anonymity of sensor nodes and gateway-lose scenario
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