Secure edge computing: An architectural approach and industrial use case (original) (raw)
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An Edge Driven Security Framework For Intelligent Internet Of Things
International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2021
The use of IoT technologies has increased from 13 percent in 2014 to about 25 percent today. And around the world number of IoT-connected devices is expected to increase to 43 billion by 2023, a threefold increase from 2018. IoT will continue to grow in device numbers and use cases, but organizations must reckon with the security and interoperability challenges that have plagued the market since the beginning. Building robust IOT applications by incorporating security features has become a necessity. Thus, in this article, an edge-driven security framework architecture is described for intelligent IoT systems. A security framework contains all standard security features required by an application such as authentication, authorization, secure connection etc. We introduce the architecture of edge-driven intelligent IoT, and present typical edge-driven intelligent IoT applications. Second, we point out the security threats in edge-driven intelligent IoT in terms of attack behaviour of adversaries. Third, we develop a case study of edge-driven intelligent IoT from the security perspective. Our focus is to develop a middleware or framework between the Users and IoT Environment to ensure users are connected to IoT environment upon authentication for a contract session and create secure communication via cloud between the users and IoT environment
Edge Computing Security with an IoT device
2021
Information technologies are changing every aspect of human life day by day. In this context, Edge Computing, Internet of Things, Machine Learning and Big Data Analytics technologies are thought to be a part of this change. Edge computing aims to bring the computing power from the remote cloud environments to the endpoints/edges of networks. Thus, smart applications do not have to send all their data to the cloud and wait for the answers to come back over the same long route. Despite this advantage, there are security risks in the edge computing process. Encryption of information is of great importance especially for IoT devices to perform transactions safely. With a system established in this study, encrypted communication has been tried to be provided on IoT devices performing edge computing. In this way, it is aimed to make the communication secure. Arduino is used as an IoT device. In the encryption process, AES encryption is used with 128-bit and 256-bit key length. Keywords—Ed...
AI4SAFE-IoT: an AI-powered secure architecture for edge layer of Internet of things
Neural Computing and Applications, 2020
With the increasing use of the Internet of things (IoT) in diverse domains, security concerns and IoT threats are constantly rising. The computational and memory limitations of IoT devices have resulted in emerging vulnerabilities in most IoT-run environments. Due to the low processing ability, IoT devices are often not capable of running complex defensive mechanisms. Lack of an architecture for a safer IoT environment is referred to as the most important barrier in developing a secure IoT system. In this paper, we propose a secure architecture for IoT edge layer infrastructure, called AI4SAFE-IoT. This architecture is built upon AI-powered security modules at the edge layer for protecting IoT infrastructure. Cyber threat attribution, intelligent web application firewall, cyber threat hunting, and cyber threat intelligence are the main modules proposed in our architecture. The proposed modules detect, attribute, and further identify the stage of an attack life cycle based on the Cyber Kill Chain model. In the proposed architecture, we define each security module and show its functionality against different threats in real-world applications. Moreover, due to the integration of AI security modules in a different layer of AI4SAFE-IoT, each threat in the edge layer will be handled by its corresponding security module delivered by a service. We compared the proposed architecture with the existing models and discussed our architecture independence of the underlying IoT layer and its comparatively low overhead according to delivering security as service for the edge layer of IoT architecture instead of embed implementation. Overall, we evaluated our proposed architecture based on the IoT service management score. The proposed architecture obtained 84.7 out of 100 which is the highest score among peer IoT edge layer security architectures.
A review of edge computing reference architectures and a new global edge proposal
edge, 2020
h i g h l i g h t s • This article is a review of the Edge Computing technology and its reference architectures. • It presented a proposal for a tiered architecture with a modular approach that allows to manage the complexity of solutions. • The main contributions of the proposed architecture reside in the security and privacy provided by blockchain technologies. • The proposed reference architecture is tested by building an IoT platform in a smart agroindustry scenario. a b s t r a c t Edge Computing represents the activities of IoT (Internet of Things) devices at the border or limit of the network connected to the remote Cloud. The latest research in this field has intended to demonstrate that Edge Computing architectures are the optimal solution to minimising latency, improving privacy and reducing bandwidth costs in IoT-based scenarios. This article is a review of the Edge Computing technology and its reference architectures proposed by the Edge Computing Consortium, Intel-SAP, the FAR-Edge Project and the Industrial Internet Consortium for Industry 4.0. Moreover, this article presents a proposal for a tiered architecture with a modular approach that allows to manage the complexity of solutions not only for Industry 4.0 environments but also for other scenarios such as smart cities, smart energy, healthcare or precision agrotechnology. The main contributions of the proposed architecture reside in the security and privacy provided by blockchain technologies. Finally, the proposed reference architecture is tested by building an IoT platform in a smart agroindustry scenario to reduce bandwidth costs between the Edge and the Cloud.
Enhancing Security and Privacy of Next-Generation Edge Computing Technologies
2019 17th International Conference on Privacy, Security and Trust (PST), 2019
The advent of high performance fog and edge computing and high bandwidth connectivity has brought about changes to Internet-of-Things (IoT) service architectures, allowing for greater quantities of high quality information to be extracted from their environments to be processed. However, recently introduced international regulations, along with heightened awareness among consumers, have strengthened requirements to ensure data security, with significant financial and reputational penalties for organisations who fail to protect customers' data. This paper proposes the leveraging of fog and edge computing to facilitate processing of confidential user data, to reduce the quantity and availability of raw confidential data at various levels of the IoT architecture. This ultimately reduces attack surface area, however it also increases efficiency of the architecture by distributing processing amongst nodes and transmitting only processed data. However, such an approach is vulnerable to device level attacks. To approach this issue, a proposed System Security Manager is used to continuously monitor system resources and ensure confidential data is confined only to parts of the device that require it. In event of an attack, critical data can be isolated and the system informed, to prevent data confidentiality breach.
Survey on Edge Computing Security
2021
It's possible to explain Edge computing (EC) as a distributed system of IT that decentralized the power of processing in which the mobile Internet of Things (IoT) computing would be allowed. In EC, data processed by local tools, computers, or servers, instead of being process and transmitted from the data center. However, with the wider capabilities of EC by increasing the network performance and reducing the latency, security challenges, and the risks will increase with data being stored and used on these devices on the edge or end of the network. This paper first provides a definition of EC and explain the reasons that led to the rapid spread of this type of computing with an explanation of the most important differences between EC and CC, in terms of the resources available for each type, processing, storage, as well as the privacy and security factor. Later, explaining the uses and benefits of this type of computing. However, the challenges are also taken into consideration,...
Edge computing: A technological advancement in Internet of Things and cloud computing
INTERNATIONAL SCIENTIFIC AND PRACTICAL CONFERENCE “TECHNOLOGY IN AGRICULTURE, ENERGY AND ECOLOGY” (TAEE2022)
Internet of Things (IoT) is emerging technologies these days which generates high volume of data. Efficient use of data analytics techniques on discrete data using Cloud Computing provides significant and precise information. In view of the traditional applications, an IoT application such as environmental monitoring, smart navigation and smart healthcare comes with separate requirements such as mobility, quick and real-time response etc. However, the typical cloud computing architecture cannot satisfy and fulfil these requirements due to processing of the data being distributed across the world remotely from physical location of installed IoT devices. Hence, the concept of edge computing emerged to perform data storage and processing at the extreme end of the networks, which is closer to data collection sources than the cloud storage. This makes applications computationally efficient and location-aware. But edge computing brings many security and privacy challenges when applied to data analytics in association with IoT devices.
IEEE Internet of Things Journal, 2018
The Internet of Things (IoT)-Cloud combines the IoT and cloud computing, which not only enhances the IoT's capability but also expands the scope of its applications. However, it exhibits significant security and efficiency problems that must be solved. Internal attacks account for a large fraction of the associated security problems, however, traditional security strategies are not capable of addressing these attacks effectively. Moreover, as repeated/similar service requirements become greater in number, the efficiency of IoT-Cloud services is seriously affected. In this paper, a novel architecture that integrates a trust evaluation mechanism and service template with a balance dynamics based on cloud and edge computing is proposed to overcome these problems. In this architecture, the edge network and the edge platform are designed in such a way as to reduce resource consumption and ensure the extensibility of trust evaluation mechanism, respectively. To improve the efficiency of IoT-Cloud services, the service parameter template is established in the cloud and the service parsing template is established in the edge platform. Moreover, the edge network can assist the edge platform in establishing service parsing templates based on the trust evaluation mechanism and meet special service requirements. The experimental results illustrate that this edge-based architecture can improve both the security and efficiency of IoT-Cloud systems.
Edge Security: Challenges and Issues
Cornell University - arXiv, 2022
Edge computing is a paradigm that shifts data processing services to the network edge, where data are generated. While such an architecture provides faster processing and response, among other benefits, it also raises critical security issues and challenges that must be addressed. This paper discusses the security threats and vulnerabilities emerging from the edge network architecture spanning from the hardware layer to the system layer. We further discuss privacy and regulatory compliance challenges in such networks. Finally, we argue the need for a holistic approach to analyze edge network security posture, which must consider knowledge from each layer. 1 IoTs are being used in manufacturing industry (Industry 4.0 [135]), healthcare, personal health management, agriculture, transportation, and across other sectors [236]. II. BACKGROUND AND OVERVIEW A. Edge Computing Framework
Adaptive Security in Cloud and Edge Networks New IoT Security Approach
2018
Edge and cloud networks have emerged during the rapid evolution of networking in the last years, mainly as part of Internet of Things network. Security has become a key issue for any huge deployment in this network. Moreover, data reliability combined with performance is really a challenging task, particularly to maintain survivability of the network. This paper addresses this task using an Adaptation Security Framework, which is an efficient edge-cloud security deployment capable of trading-off between security and performance. It is based on an autonomic computing security looped system, which fine-tunes security means based on the monitoring of the context. An evaluation of the approach is undergoing in the context of smart city through a simulation tool and real-world large deployment.