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The cyber security key rules that the intelligence and techniques that has been taken cyber- deployment and massive data access all over the world. There are unpredicted issues and challenges that Artificial intelligence(AI) rapidly increases the threats also. Even though the security efficient provided that are incorporated along with machine learning and deep learning a major attacks are even eventually growing faster. Healthcare a foremost region that has to be available, integrity about patient's details and confidential security in data relies on cyber security. Whenever transaction and operation of healthcare data are manipulated and spread all over the research and distributed access the cyber-attacks involved too. The proposed work defines a context based cyber-security using Bio-stimulated cross approach artificial intelligence (CBSCA). The context combines the Deep learning approach method that is mostly applicable forcyber-attacks. Where the privacy and integrity of severe network applications that describes the health care analysis network.
Diversified approaches defined below
- i) Diverse approach for anomaly detection model for protecting the data and security that can be shelter from cyber-attacks that cannot be evaded beyond security measures such as passive attacks. (EG: Antivirus)
ii)Learning ability monitoring for malware detection (LAMD) which fix and separate attacker’s location in executable packets that cannot be undetectable by firewalls.
iii) Data manipulation on SQL preventing system attacks that has to be focused to avoid various SQL injection techniques.
The results show that the proposed system attains more accuracy than the existing works.
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