Best Practices For Data Loss Protection

India organisations have been witnessing several data breaches over the last few years. Two main reasons behind the breaches are the value of these data and the plethora of unprotected data generating every day. Last year, more than 1.3 million credit and debit card details from Indian banks were sold for $100 per piece. India’s biggest nuclear power plant, ISRO was hacked in September by installing malware on computers.

There are many other such cases that have happened within just a few years, which shook the privacy of millions of users. According to sources, the global average total cost of a data breach for the 2019 study is $3.92 million, a 1.5 per cent increase from the 2018 study. Data Loss Protection (DLP) is a method of using tools and strategies to protect data from being exposed to unwanted and unauthorised parties. This process involves tracking how much data is being used, preventing it from the breachers and other such.


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In this article, we discuss 8 important practices, which can be helpful in data loss protection. 

1| Categorising The Data 

One must categorise data depending on the risks and the vulnerabilities before it gets into wrong hands. The sensitive data such as intellectual property, Personally Identifiable Information (PII), among others, need to be classified by evaluating their risk factors and its vulnerability. Understanding the vulnerabilities, it is important to set policies and methods to protect the data. 

2| Defining The Roles

Organisations must clearly define the roles and responsibilities to the users who will be handling the data. Policies such as users can only get access to the data, which is important to complete their tasks, assigning the responsibilities to alarm the unwanted use of data and other such needs to be followed to prevent data loss.  

3| Understand Data

While working with data, it is important to understand the states and nature of data. In an organisation, loads of data are generated every day, and it is crucial to understand what are the natures of data and how they can be categorised. There are mainly three states of data, which are data at rest, data in motion and data in use. Data at rest is related to the data, which are stored in the database, cloud servers, etc. Data in motion or data in transit is the method of data transportation by means of computer systems or other such. Lastly, the data in use is the data, which is processing or can be accessed currently.  

4| Create Cybersecurity Awareness

Organisations must provide adequate training and knowledge to the users who will be working with the data. Users should be able to ensure the duties and responsibilities regarding the data they are handling. They should be provided with the endpoint solution of data loss prevention.

5| Installing Cybersecurity Defense

To protect data, it is crucial to implement robust security measures such as firewalls. Also, while considering security measures, one must imply proactive security measures rather than reactive security measures. If an organisation is using cloud services for data storage, it is important to evaluate the security measures and other policies of the cloud service vendors. A clearly defined role and responsibility to the users will help an organisation to make a fair DLP strategy.

6| Data Encryption

Data Encryption is one of the most important steps for data in rest or in motion. It is the process of encrypting data into some code, which needs a secret key or a decryption key to decrypt it. There are several cryptographic algorithms, which can be used to encrypt and decrypt data in order to protect it from data loss.

7| Anomaly Detection

With almost all implementations in every domain, machine learning techniques can be used to protect data through anomaly detection. With the help of anomaly detection, organisations can identify malicious and unusual activities of any user, while working or using data. 

8| Stay Away From Unnecessary Data

Holding onto old, unprotected and unused data for a longer period of time not only leads to vulnerability but also consumes a lot of space in the database or cloud storage. One must get rid of excess data, which is going to be of no use in the near future. 

Wrapping Up

Cybercrime like data breaching will continue to grow as the data grows. It is important for organisations to build a Data Loss Prevention (DLP) method. There are a number of data loss prevention tools available online, which includes threat protection, encryption for data, user tracker, data access controller and other such that can be used to protect the data. 

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Ambika Choudhury
A Technical Journalist who loves writing about Machine Learning and Artificial Intelligence. A lover of music, writing and learning something out of the box.

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