Privacy Threats and Privacy Preservation Techniques for Farmer Data Collections Based on Data Shuffling

Aside from smart technologies, farm data collection is also important for farms including environment and farmer survey collection. With collection, we observe that it generally proposed to utilize in systems. However, can be released use the outside scope of collecting organization an appropriate business reason such as improving system, product quality, customer service. Moreover, often includes sensitive data, private farmers. Thus, could lead privacy violation issues when released. To address these anatomization model protect users' available proposed. still has disorganized table must addressed. rid vulnerabilities models, a new preservation based on shuffing this work. evaluated by conducting extensive experiments. The experimental results indicate more efficient than That is, adversary have confidence re-identifying every after satisfied constraint at most 1/l. Furthermore, satisfies model, does not considering values.