CRDec 6, 2021

Review of Data Integrity Attacks and Mitigation Methods in Edge computing

arXiv:2112.02757v13 citations
Originality Synthesis-oriented
AI Analysis

It addresses data integrity issues for edge computing systems, which is an incremental contribution as it builds on existing security reviews by specifically targeting integrity threats.

This paper reviews data integrity attacks and mitigation methods in edge computing, focusing on threats that directly impact edge data analysis, and identifies shortcomings in existing work with research directions.

In recent years, edge computing has emerged as a promising technology due to its unique feature of real-time computing and parallel processing. They provide computing and storage capacity closer to the data source and bypass the distant links to the cloud. The edge data analytics process the ubiquitous data on the edge layer to offer real-time interactions for the application. However, this process can be prone to security threats like gaining malicious access or manipulating sensitive data. This can lead to the intruder's control, alter, or add erroneous data affecting the integrity and data analysis efficiency. Due to the lack of transparency of stakeholders processing edge data, it is challenging to identify the vulnerabilities. Many reviews are available on data security issues on the edge layer; however, they do not address integrity issues exclusively. Therefore, this paper concentrates only on data integrity threats that directly influence edge data analysis. Further shortcomings in existing work are identified with few research directions.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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