We are facing with a torrent of data generated and captured in digital form as a result of the advancement of sciences, engineering and technologies, and various social, economical and human activities. Big data applications provide a great benefit to many large scale and small scale industries. Big Data creates critical information security and privacy problems, at the same time Big Data analytics promises significant opportunities for prevention and detection of advanced cyber-attacks using correlated internal and external security data. We must address several privacy and security challenges to realize true potential of Big Data for information security. The paper analyzes Big Data applications for information security problems, and defines research directions on Big Data analytics for security intelligence. Traditional encryption solutions can protect the data but they can't be used to compute on encrypt data, however a novel encryption scheme, called fully homomorphic encryption (FHE), could compute over encrypted data without decrypting it. Extracting valuable information from attributes by evaluating them is the main goal of analyzing big data which need to be protected. Since, it is impossible to protect all big data, we consider big data as a single object which has its own attributes, and the set of attribute which have a higher relevance is more important than other attributes. A novel keyword search method to enable customers easily searching keywords from encryption-protection data is also discussed in this paper. © International Science Press.