50,102 research outputs found

    Leveraging Secure Multiparty Computation in the Internet of Things

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    Centralized systems in the Internet of Things---be it local middleware or cloud-based services---fail to fundamentally address privacy of the collected data. We propose an architecture featuring secure multiparty computation at its core in order to realize data processing systems which already incorporate support for privacy protection in the architecture

    Privacy in cloud-based computing

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    Cloud computing, internet of things (IoT), edge computing, and fog computing are gaining attention as emerging research topics and computing approaches in recent years. These computing approaches are rather conceptual and contextual strategies rather than being computing technologies themselves, and in practice, they often overlap. For example, an IoT architecture may incorporate cloud computing and fog computing. Cloud computing is a significant concept in contemporary computing and being adopted in almost every means of computing. All computing architectures incorporating cloud computing are termed as cloud-based computing (CbC) in general. However, cloud computing itself is the basis of CbC because it significantly depends on resources that are remote, and the remote resources are often under third-party ownership where the privacy of sensitive data is a big concern. This chapter investigates various privacy issues associated with CbC. The data privacy issues and possible solutions within the context of cloud computing, IoT, edge computing, and fog computing are also explored

    Fog computing, applications , security and challenges, review

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    The internet of things originates a world where on daily basis objects can join the internet and interchange information and in addition process, store, gather them from the nearby environment, and effectively mediate on it. A remarkable number of services might be imagined by abusing the internet of things. Fog computing which is otherwise called edge computing was introduced in 2012 as a considered is a prioritized choice for the internet of things applications. As fog computing extend services of cloud near to the edge of the network and make possible computations, communications, and storage services in proximity to the end user. Fog computing cannot only provide low latency, location awareness but also enhance real-time applications, quality of services, mobility, security and privacy in the internet of things applications scenarios. In this paper, we will summarize and overview fog computing model architecture, characteristic, similar paradigm and various applications in real-time scenarios such as smart grid, traffic control system and augmented reality. Finally, security challenges are presented

    Exploring Data Security and Privacy Issues in Internet of Things Based on Five-Layer Architecture

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    Data Security and privacy is one of the serious issues in internet-based computing like cloud computing, mobile computing and Internet of Things (IoT). This security and privacy become manifolded in IoT because of diversified technologies and the interaction of Cyber Physical Systems (CPS) used in IoT. IoTs are being adapted in academics and in many organizations without fully protecting their assets and also without realizing that the traditional security solutions cannot be applied to IoT environment. This paper explores a comprehensive survey of IoT architectures, communication technologies and the security and privacy issues of them for a new researcher in IoT. This paper also suggests methods to thwart the security and privacy issues in the different layers of IoT architecture

    A Cloud Based Approach for Data Security in IoT

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    The number of connected devices grows rapidly each year as more and more enterprises realize its potentials. Despite the benefits, data privacy and security in Internet of Things (IoT) remain a major issue. IoT devices generates massive data but are limited in resources. The proliferation of IoT devices and the increasing network traffic have heightened the attack surface. Moreover, the susceptibility of transmitted data to eavesdropping and man-in-the-middle attacks is a great concern to users and manufacturers. It is not all IoT devices that utilize encryption. IoT traffic from devices that transmit data in plain text will expose sensitive information if intercepted by an adversary. Such a vulnerability can be exploited to facilitate identity theft and implement other devasting cyber-attacks. This paper presents an implementation of a cloud-based security approach for transmitted data in IoT. The design is based on Lambda architecture using Amazon Web Services. The proposed approach effectively processes and analyzes real-time sensor data as well as historical data from a master database on the cloud. It also ensures the security of user’s information. Keywords: Internet of Things, Cloud computing, Data security, Lambda architecture DOI: 10.7176/CEIS/11-2-03 Publication date: February 29th 202

    Serverless computing for the Internet of Things

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    Cloud-based services have evolved significantly over the years. Cloud computing models such as IaaS, PaaS and SaaS are serving as an alternative to traditional in-house infrastructure-based approach. Furthermore, serverless computing is a cloud computing model for ephemeral, stateless and event-driven applications that scale up and down instantly. In contrast to the infinite resources of cloud computing, the Internet of Things is the network of resource-constrained, heterogeneous and intelligent devices that generate a significant amount of data. Due to the resource-constrained nature of IoT devices, cloud resources are used to process data generated by IoT devices. However, data processing in the cloud also has few limitations such as latency and privacy concerns. These limitations arise a requirement of local processing of data generated by IoT devices. A serverless platform can be deployed on a cluster of IoT devices using software containers to enable local processing of the sensor data. This work proposes a hybrid multi-layered architecture that not only establishes the possibility of local processing of sensor data but also considers the issues such as heterogeneity, resource constraint nature of IoT devices. We use software containers, and multi-layered architecture to provide the high availability and fault tolerance in our proposed solution

    Blockchain-based privacy-preserving healthcare architecture

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    Since the introduction of Internet of Things (IoT), e-health has become one of the main research topics.Due to the sensitivity of patient data,preserving the privacy of patientsappears to be challenging. In healthcare applications, patient data are usually stored in the cloud, which makes it difficult for the users to have enough control over their data. However, due to the General Data Protection Regulation (GDPR), it is the data subject’s right to know where and how hisdata has been stored, who can access hisdata and to what extent. In this paper, we propose a blockchain-based architecture for e-health applications whichprovides an efficient privacy-preserving access control mechanism. We take advantage of Blockchain(BC)special features, i.e., immutability and anonymity of users,whilemodifyingthe classic blockchain structure in order to overcome its challenges in IoT applications(i.e., low throughput, high overhead and latency). To this end, we cluster the miners of BC, store and process data at the nearest clusterto the patient. While our proposal is a work in progress, we provide a security analysis of our proposed architecture
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