Privacy and Big Data Protection: Comparisons between Data Encryption Methods
Big data revolutionized many industries. Big data security became a challenge that requires constant updates and modifications. For this reason, this study implements encryption and decryption models in data storage phase to protect big data from data breaches. Three encryption algorithms are tested by applying specific dataset. The algorithms are implemented to generate the performance metric. The encryption and decryption times are further analyzed and discussed. Despite obtaining the run time of the encryption methods, it is inferred that these three encryption methods are served for different purposes and the comparison is minimal. Generally, the runtime of the three algorithms increase linearly along the data size. Identity based encryption provides lower computational cost with only a certain level of confidentiality, while attribute based encryption provides higher security level by increasing computational cost without limits. Homomorphic encryption is inferred as the most secure encryption method by assuring no deciphering during all computations.