Abstract: 

With more edge devices becoming internet-connected, the demand for real-time, no-delay data processing on edge nodes has increased, as it allows systems to process data effectively while consuming less internet bandwidth, and a lot of data can be processed at or near the source. Edge computing is a distributed open architecture that enables systems to process data closer to the information source instead of sending it to the cloud. Edge is defined as the communication that unites the physical and digital worlds.

Security risks occur when data is sent to the cloud through IoT devices. Every change the data undergoes might lead to a security lapse. Information transmission across borders is being restricted by tightening privacy restrictions. Edge computing, which stores and analyzes data at the point of origin, is a valuable method for avoiding security problems. A strict governance plan might inhibit innovation, while inadequate or insufficient data governance could expose the company to market disruptions. By minimizing data disruption and analyzing data to improve privacy, decrease data breaches, and promote usability using edge computing for data management. An organization’s primary goal is to safeguard the personal information of users, clients, and workers. Data masking has become essential for many firms to protect sensitive information. Companies must have policies for identifying sensitive data, selecting appropriate data masking techniques, and conducting frequent data assurance audits.

Keywords: Edge Computing, IoT, Data integrity, Edge Nodes, PII