Abstract
With the rapid growth of Internet of Things (IoT) based models, and the lack amount of data makes cloud computing resources insufficient. Hence, edge computing-based techniques are becoming more popular in present research domains that makes data storage, and processing effective at the network edges. There are several advanced features like parallel processing and data perception are available in edge computing. Still, there are some challenges in providing privacy and data security over networks. To solve the security issues in Edge Computing, Hash-based Message Authentication Code (HMAC) algorithm is used to provide solutions for preserving data from various attacks that happens with the distributed network nature. This paper proposed a Trust Model for Secure Data Sharing (TM-SDS) with HMAC algorithm. Here, data security is ensured with local and global trust levels with the centralized processing of cloud and by conserving resources effectively. Further, the proposed model achieved 84.25% of packet delivery ratio which is better compared to existing models in the resulting phase. The data packets are securely transmitted between entities in the proposed model and results showed that proposed TM-SDS model outperforms the existing models in an efficient manner.
Highlights
Internet of Things (IoT) is the recent advancement in communication, in which data is the valuable resource, providing several intelligent services to the people [1]
Hash-based Message Authentication Code (HMAC) is produced for the ‘encrypted text (ET)’, which effectively controls the impacts of node capture attacks and compromised node attacks in edge computing
For evidencing the model efficiency, the results are compared with Support Vector Machine for attack detection and IoT-Intrusion Detection Model (IDM)
Summary
Internet of Things (IoT) is the recent advancement in communication, in which data is the valuable resource, providing several intelligent services to the people [1]. An effective privacy preserving models and protocols are necessary in edge computing. The conventional privacy and security models in edge computing are ineffective for securing the massive data processing [5]. Secure data processing and privacy preserving problems are effectively important. Major concerns that are faced in edge computing related to data security and privacy-preserving issues are lightweight and fine-grained, distributed access control, limited resources and efficient privacy preservation. Edge computing cannot secure the user data privacy, since new set of attacks with multiple attack models are associated with the heterogeneity of element resources, network measurement and user accessibility [11,12]. The structure of this paper is organized as follows: Section 2 provides the concepts of security management in edge computing that are applied for data security so far.
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