Published Paper Details:

The Army record maintenance is sensitive and crucial task in Military Sectors. The Soldiers records are stored in a huge data set; it can be stored, maintained and traced every day. The objective of this project is to store soldiers reports safely. In Existing, Cryptographic-based encryption is to encrypt data into unreadable code; it is more likely to attract the attacker's attention. Once these ciphertext is intercepted, the attacker will try to decrypt these ciphertext to obtain some useful information, so as to carry out some illegal activities. Some Military information not only have high requirements for privacy protection, but also want to be able to express their preference in the decision-making of privacy protection, so they may want to define what information is sensitive to them and what is not. The proposed model can classify the data into sensitive data and non-sensitive data according to the user's preferences with SVM (Support Vector Machine) based machine learning classification. Since non-sensitive data pose no threat to user privacy, it can be transmitted directly on ordinary channels without being processed. While, sensitive data need to be processed before it can be transmitted. In terms of sensitive data processing, here proposes a method of combining data encryption with information hiding. Sensitive data are encrypted using Advanced Encryption Standard (AES) encryption algorithm before it can be transmitted, making it to unreadable code. Then, a novel information hiding method proposed, named the Modified LSB (MLSB) information hiding method is used to provide a second guarantee for the security of sensitive data. In other words, the sensitive information is hidden in the multimedia carrier, so that the adversary cannot notice the existence of sensitive information.