Big data privacy and security challenges

Before we can understand the big data privacy concerns, its is important to understand what big data is?

Big Data Definition

Big data is a field that treats ways to analyze, systematically extract information from, or otherwise, deal with data sets that are too large or complex to be dealt with by traditional data-processing application software.

As per analyst and author Doug Laney , big data is defined by three Vs: volume, velocity and variety.

There’s lots of it flowing in at great speeds from numerous sources. And its impact is immense, regardless of industry.

Some of the big Data Examples are as under:

  • Prediction of user demand  by ridesharing companies
  • Tool for fuel Optimization for the transportation industry
  • Analyzing Health conditions through data from wearables
  • Live road mapping for autonomous vehicles

So it is obvious that big data is playing a key role in our everyday life.

What is Big Data Privacy ?

Big data privacy includes managing big data properly to mitigate risk and protect sensitive data. Because big data contains large and complex datasets, many traditional data protection processes cannot handle the scale and speed required. To protect big data and make it available for analysis, a  privacy framework is to be created that can handle the amount, speed, diversity, and value of big data as it travels between environments, is analyzed, and is shared.

What are key big data privacy and security issues ?

As discussed Big Data is a new and emerging technology with wide applictaions which are  enabling organizations to make reliable decisions for their business.

But the huge volume of data in big data systems itself make it a potential target for hackers. Thus it becomes imperative that this data must be protected, and handled as per highest security and regulatory obligations including those related to privacy laws like GDPR, CCPA , LGPD, HIPAA, UK DPA etc.

The features of Volume, Velocity and Variety Big Data makes for its biggest privacy concerns as well . Keeping secure the huge volume of data flowing in at great speeds from numerous sources and preventing privacy breaches and violations is a huge challenge.

How could big data privacy risks be eliminated or minimized ?

 

Real time monitoring of threats  and risk – Implementing solutions that monitor large amounts of data in real time can help you understand potential data breaches and implement your data protection strategies faster and more efficiently.

Data Encryption – Encryption is also a solution for privacy and security issue in big data. Its just that it works with the help of complex algorithm like Homorphic Encryption algorithm, Verifiable computation algorithm (outsource computing), Message digest algorithm, Key rotation algorithm, DES Algorithm and Rijndael Encryption Algorithm which also make it difficult for criminals to decode the data.

Data Mapping – The Data collected and stored must be indexed and proper inventory, and mapping of it with the data subjects should be effectuated to support data access rights and notifications.

Collect only relevant data – Only necessary variables of data which are important for the purpose of providing services should be collected. Collecting unnecessary data not only increases your volume but also increases your privacy and security obligations.

Internal Risk Mitigation – The biggest ransomware attacks happen because of human error.  It is thus important that the teams in your organization must be aptly trained to follow optimum information security and privacy practices.

Adopt and maintain optimum Information Security Practices–  Adopting the best information security protocols like SOC2 and ISO 27001  prepares for handling data in a secure manner and establishes right practices .

Comply with applicable privacy regulations – Comply with applicable privacy regulations which you would be expected to comply with as per your business and users or target users’ location.

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