An Efficient Fine Grained Keyword Based Search Scheme in Fog Computing
PVN Rajeswari1, Chadalawada Lakshmi Janaki2

1PVN Rajeswari, Associate Professor, Dept. of CSE, PBR VITS, Kavali, AP, India.
2Chadalawada Lakshmi Janaki, M. Tech, Dept. of CSE, PBR VITS, Kavali, AP, India.
Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 602-606 | Volume-8 Issue-5, January 2020. | Retrieval Number: E5095018520/2020©BEIESP | DOI: 10.35940/ijrte.E5095.018520

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Abstract—In fog computing outsources the encoded information to many mist hubs on the border of the internet of things (IOT) to reduce delay and network congestion. However, the existing cipher text recovery plan infrequently focus on the fog computing area and most of them still enforce high computational and capacity burden on asset constrained clients.In this writing paper, we tend to better recommended a lightweight small-grained cipher texts search (LFGS) framework in fog calculation by extending cipher text-policy attribute-based encryption (CP-ABE) and searchable encryption (SE) technologies, which can accomplish small-grained fingerprint plus key-word search concurrently. The LFGS can transfer semi calculation and storage burden from clients to picked fog nodes. Furthermore, the fundamental LFGS framework is enhanced to cope with conjunctive keyword search and attribute revise to keep away from returning unrelated search outcomes and unauthorized accesses.
Keywords: Internet of Things, Fog Calculating, Cloud Computing.
Scope of the Article: Cloud Computing.