Medical knowledge extraction scheme for cloudlet-based healthcare system to avoid malicious attacks. (14th January 2020)

• Record Type: Journal Article
• Authors: Chandavale, Anjali; Gade, Anuja; Dixit, Abhijeet
• Is Part Of: International journal of cloud computing. Volume 8:Number 4(2019)
• Page Start: 319
• Page End: 331
• Publication Date: 2020-01-14
• Subjects: healthcare -- number theory research unit -- NTRU -- decision making system -- proficiency score -- reliable -- collaborative intrusion detection system -- intrusion detection -- medical knowledge extraction -- MKE -- cloudlet -- healthcare system -- information security -- malicious attacks; Cloud computing -- Periodicals; 004.678205
• Languages: English
• ISSNs: 2043-9989

Abstract

The medical information sharing involves information collection, information storage, and sharing of this information. Protection to medical information against malicious attacks is an important concern due to its storage on remote cloud. In current online question answering system for health-related issues, extraction of medical knowledge from the clamorous question- answers pair is a challenge. To overcome these challenges, medical knowledge extraction scheme for cloudlet based healthcare system is proposed. The proposed and developed medical knowledge extraction (MKE) scheme finds valid remedial Triples from clamorous question-answer (Q-A) pairs and evaluate the reliability along with doctor's proficiency using truth discovery method the modified number theory research unit algorithm (NTRU) and collaborative intrusion detection system (CIDS) is used to avoid and detect malicious attacks. The response time of the proposed system is 6 to 8 seconds which results in a substantial reduction in time and cost for the end-user.