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Encryfuscation: A model for preserving data and location privacy in fog based IoT scenario

2022; Elsevier BV; Volume: 34; Issue: 9 Linguagem: Inglês

10.1016/j.jksuci.2022.03.003

2213-1248

Jasleen Kaur, Alka Agrawal, Raees Ahmad Khan,

Privacy-Preserving Technologies in Data

With the highly escalating digital population, it has become difficult to effectively manage the users’ private data flowing across the web. The introduction of fog computing has solved many issues such as low latency, location awareness, etc. But, on the other hand, it has also raised questions upon users’ privacy as now the data is processed at the network edge; closer to end-user which increases the attack-surface and makes it more vulnerable. In this light, the authors have proposed an encryfuscation model that employs obfuscation and encryption techniques. The selection of the suitable privacy preservation technique for a given service request is done on the basis of offloading decision. The offloading decision is taken as per the severity of the service. Further, two obfuscation techniques for obfuscating data (data privacy) and location (location privacy) are proposed by the researchers. Both the proposed techniques are simulated through MATLAB R2021a. The results obtained have also been compared to earlier approaches. The data obfuscation approach is compared to Base64, Base32, Hexadecimal and MONcrypt while the location obfuscation technique is compared to ESOT and SLOT. The development of suitable encryption approach for the model may be considered as future work.