Lately, the volume of data that is being collected from numerous businesses is increasing exponentially. Furthermore, with the evolution of technologies such as IoT and cloud, the data captured are driven with big data issues and can be extended to even broader levels. Any attempt that is made towards a secure environment requires impenetrable cybersecurity framework, with fivefold security stages and secured protocol. Moreover, with security breach as a critical concern, authentication is still a vital topic for the researchers, and there is a huge requirement for high-end security algorithm for data processing and transfer.
To analyze the risks involved in data analytics issues, several big data-driven technologies along with machine learning and data mining algorithms are developed and classified on the basis of applications, its performance analysis in a real-time scenario. The batch processing technologies such as Hadoop, Spark are found to be more suitable to achieve high throughput in real-time data processing.
With the deployment of IoT in real-time applications such as medical industry, banking, and financial sectors, several advantages can be achieved, but they are limited to certain risk factors, which should be ascertained during the design and development stage of the module. The primary risk aspect observed during the data processing stage is authentication. The system should be encrypted with a strong authentication protocol to secure data during transmission or whenever connected to the mutual network-based service.
Since integration amongst numerous IoT devices is not provided with the authentication protocol, the data transferred may not remain confidential. This is generally observed while authorizing the public Wi-Fi networks. Moreover, during data transmission, businesses should ensure that the decryption code is provided only to the authorized user, and periodic password change should be ensured to avoid risks from fraudsters. Furthermore, in mutual data transmission, the integrity amongst the number of users and pairing is difficult to control in Bluetooth-enabled devices, since the person authorizing the data is unknown to the master user. This way, the possibility of the data being accessed by a fraudster is more and can lead to critical risks.
With advancement in technologies, certain universal standards are developed to protect the data transferred through IoT platforms. The frequent innovations in the IoT space have led companies to know about potential risks and be aware of the security breaches to achieve highly authenticated data transmission with high processing speed and low power utilization.
