HYBRID ENCRYPTION OF BIG DATA SECURITY USING IMPROVED ELLIPTIC CURVE CRYPTOGRAPHY

In terms of identifying the attacker, the Big Data environment helps resolving cyber security problems. There are big data security concerns as well as safety issues that the analyst must understand. The security of confidential data has long been a serious concern, and as a result, data security is in huge demand. Data is considered an important aspect of an asset and must be protected. Data Protection comprises data integrity, data authenticity, data confidentiality, and then some. Data is prone to possible security risks despite several measures for protecting data including encryption, decryption, and compression. Cryptography is an art and science that encodes messages to make them unreadable in order to achieve secrecy. The data is translated from a readable format known as plain text to an unreadable format known as cypher text, and vice versa. Based on various techniques, there are different types of cryptographic algorithms proposed over the years. These methods use different techniques to implement cryptography's fundamental features, i.e. to conceal the data from unauthorised users. A hybrid cryptographic technique is proposed in this paper to enhance data protection during network transmission, and its implementation and results are published. The proposed secure cryptographic technique promises to use the Enhanced ECC and AES technologies to include the highly secure cypher generation technique. Using JAVA technology, the implementation of the proposed technique is given and its efficiency in terms of space and time complexity is calculated and compared with conventional ECC cryptography. During comparative performance analysis, the proposed cryptographic technique established the successful and enhanced cypher text.