Big Data Security - Quick Tutorial

Currently, data is considered new gold but remember 99% of data still be considered junk. To decide what data is gold and what is junk, big data concepts and technology play a primary role. In this brief tutorial, we will learn what big data is, the concept of big data analytics, the key challenges/threats/concerns of big data security, and the tools that can be used to process big data.

Big Data

As terminology suggests, Big Data is a large volume of data that is generated daily. Big Data may be structured or unstructured. You can take an example of large volumes of log files generated in cloud data centers or data generated by stock exchanges growing with time.

Big Data Analytics

Big Data Analytics is a technology that helps analyze a large quantity of data and based on it, companies decide to target customer groups, marketing strategies, etc.

Big Data Security - Challenges, Threats, Concerns

  • Research is still in progress for big data integrity and confidentiality
  • Encryption techniques work well for small data but they may fail in the case of Big Data
  • Implementation of cybersecurity in data governance
  • Implementation of encryption/key management for securing big data
  • Implementation of tenant data isolation/containerization.

Big Data Security Tools

Below are the key security tools and techniques that can be used to secure big data.

  • Centralized key management - confidentiality and availability of data in need is a major concerns among stakeholders. Key management is the process of protecting the key from loss or misuse.
  • Access Control - This security technique helps in accessing data by authorized users only. This control helps in achieving the confidentiality of data by providing an authentication and authorization mechanism.
  • Secure the perimeter - This security mechanism helps in securely storing big data. Network devices such as routers, firewalls, intrusion prevention systems (IPS), switches, etc., are the key enabler in storing big data securely.
  • Encryption - these security techniques help in achieving confidentiality and integrity.
  • Real-Time Security Monitoring - 24 X 7 network security team takes care of audit logs and act in case of any suspicious activity.
  • Physical Security - It is still the most critical step to secure data centers to secure data.

Big Data Security and Privacy Issues in Healthcare

Security Issues:

  • Need for lightweight but secure off-cloud encryption
  • Homomorphic encryption is not widely recommended yet
  • Need for light and efficient cryptographic techniques, realistic threat models
  • Issues related to ownership of data after the death of an individual
  • The administrator of big data technology has access to data considered as a big risk. The usage of strong encryption and key escrow is recommended
  • Standards for sharing data are still not clear
  • An audit needs to be performed by a qualified professional

Privacy Issues:

  • De-identification of data is still not fully proof
  • The need for Full life cycle data ownership and custody controls
  • logging mechanism and appropriate controls as decided by the state for access to personal information
  • Transparent mechanisms should be available
  • Lack of protection of personal data
  • Need to consider an appropriate procedure for the release of data in the public domain

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If you have any questions, feel free to ask in the comments section below. Nothing gives me greater joy than helping my readers!

Disclaimer: This tutorial is for educational purpose only. Individual is solely responsible for any illegal act.

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