Secured big data based on ocular recognition

Abstract

In the last few decades, technology has played a main role in developing the electronic devices sharing data, such as sensors, actuators, individual archives, cloud and social networks. Managing this variety of large data called as big data efficiently is a challenging task. The critical challenge in handling big data is security and privacy. At any stage privacy may not be disclosed. Various existing techniques based on encryption and anonymization for security is not perfectly suitable for the unstructured, high speed, large volume big data. In this paper, analysis and discussion is done on how biometric verification and authentication secures big data. Fingerprint being the well-known biometric, ocular recognition is the most reliable biometric technique compared to iris recognition. The unique feature of human iris is its pattern and color which is identified by the type and amount of the pigment in it. The proposed method combines both iris and retinal authentication technique to provide better security for the big data in the emerging field of Internet of Things (IOT).