Questions IT and Development

What are the challenges in big data security and privacy?

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Airtract

Poonam Sharma

Create your own magic

The 21st century witnessed some of the craziest life-changing advancements, including the development of AI and Virtual Reality. All these changes are driven by data, loads and loads of data. At this point of time, data is the most crucial component for the make or break of an organization, and hence, it becomes essential to keep all those data well protected from all sorts of attacks.

In this module, we’ll be discussing some of the challenges faced in big data security and privacy.

  • Fake data generation

    One of the most common issues faced in big data security is fake data generation. The cybercriminals can infiltrate your system and modify it to produce fake results. For example, you have a system that determines the quality of your production process. The attackers can modify it to produce fake results, which ultimately hampers your production process and quality control.

  • Lack of proper encryption

    Encrypting and decrypting big chunks of data is a lengthy and tiresome process. Most of the organization skips this process because of this, and stores the data into the cloud unprotected. This gives easy access to the criminals to extract those data and use it for unethical purposes.

  • Unreliable Mapping

    Big data after collection, is subjected to parallel processing like the MapReduce paradigm. In this process, the bulk data is broken down into smaller components, and a mapper process then selects storage for the data. The cybercriminals can modify your data by accessing these mappers' code and can extract sensitive data for illegal purposes.

  • Data Provenance

    Data Provenance refers to the collection of all the past data. It is a massive collection of data, and it becomes challenging to secure that information as any slight changes in these data can cause misleading of information, and any undetectable data source can make it more difficult to trace the source of a data breach and fake data manipulation.

Read more:  What is digital privacy?

Airtract

richard devis

Tagline Not available

Over the years, enterprises have been using big data analytics to enhance their employee performance, make better decisions, and identify better business opportunities. This exhaustive data consumption leads to various big data security and privacy challenges.

Let’s take a look at these challenges.  

Distributed Data

Most businesses rely on the available big data frameworks in the market that distribute data processing tasks across many systems for their faster analysis of crucial data. Indeed, this reduces the workload but ultimately results in user privacy and security issues.

Non-Relational Databases

These databases focus more on flexibility and scalability in comparison to other traditional and relational alternatives. As performance is favored over security, such databases need a high-end environment backed by potential security measures.

Endpoint Vulnerabilities 

There’s a high possibility that your endpoint devices get manipulated by cybercriminals followed by false data generation and transmission. This creates doubt on the authenticity of such endpoints and hampers enterprise IT security.

Data Mining 

Many big data environments rely on data mining tools that identify specific patterns in unstructured data. However, the personal and financial information wrapped within gets exposed to internal/ external digital threats.

Access Controls

Restricting unauthorized access to sensitive data and information like medical records is a practice followed by companies. But sometimes people who don’t have the access. still need to use this information which results in complications as big data-enabled technology solutions are not designed to accomplish granular access. 

However, you can easily address and overcome these big data security and privacy challenges by implementing robust security solutions that include Big Data Encryption tools, User Access Control, Intrusion Detection & Prevention system, Centralized Key Management, Fraud Detection technologies, etc.   

You can also choose our Enterprise Mobility Services to advance your existing system and minimize the associated IT risk.


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