
Cloud Data Security Model Using Modified Decoy Technique In Fog Computing For E-Healthcare
Author(s) -
P. Maragathavalli,
S. Atchaya,
N. Kaliyaperumal,
S. Saranya
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1065/1/012044
Subject(s) - cloud computing , computer science , computer security , big data , authentication (law) , key (lock) , block (permutation group theory) , data mining , operating system , geometry , mathematics
In recent years, the cloud provides the facility of storing the possible files to a remote database which can be retrieved on demand. Healthcare cloud infrastructure is used to store the medical records which in turn help in managing and tracking the records of the user. The primary care providers use Electronic Medical Record (EMR) for diagnosing and evaluating medical data. Big data analytics is an important technology in enormous business areas which includes banking, social media, machine sensor data and medical welfare. Healthcare cloud provides various storage facilities such as Google drive, dropbox business and one drive in which security issues like data theft attacks to be considered as the serious security breaches of the cloud. In this paper, a modified decoy technique is proposed in order to ensure more security for the user’s Medical Big Data (MBD). The tri-party authentication key uses key agreement protocol which is modelled by bilinear pairing cryptography. The proposed system detects the attacker and sends the information such as IP address, access time and date to the user. It also provides the facility to block the account from further access. Using the triple-des algorithm in bilinear pairing the parameters like throughput is increased and computational complexity is decreased.