Secure Data Analytics

 Secure Data Analytics

It is a fact that increase in network and technology and internet growth has led to the increase in the cyber-attacks. Amidst these cyber-attacks there are also several counter-attack solutions. It is to be considered that the traditional methods of handling these cyber-attacks are quite incapable. As a result, in this era of data and data analytics, Big data is emerging as a solution to these attacks. Using the data analytics, the network managers can monitor the real-time streams of network and track the suspicious patterns. One such example of the use of secure data analytics is given by (Sewell, 2020) where secure data analytics is used for California Consumer Privacy Act (CCPA). What happens when the data is encrypted with a key? In this article, the data in the data base is masked. Which means the ID, name and DOB are all encrypted. Even when the data is stolen, without decryption, the data cannot be used or no information from the data can be derived. 

CYBER-CRIME STATISTICS:

According to statistics we see that in the year 2019 there were 144.91 million of malware incidents(Online, 2020). And in the year 2020 we have already witnessed 38.5 million malware incidents till April 2020. Further it is to be noted that this institute records around 350,000 new programs each day. 

In the year 2017, there was a loss of 780,000 records per day.Around 21% of files are unprotected.The US, UK and China are the three most vulnerable places for crime attack.They have also predicted that by the year 2021the cost of cyber-crime would spike up to $6 trillion.About 300 billion passwords would be created by the year 2020.

SECURE DATA ANALYTICS:

We see that big data mainly means 4 V’s. the 4 V’s can be explained in simple terms as

•   The data quantity (Volume)
•   The types of available data (Variety)
•   The rate at which the data is generated (Velocity)
•   The economic values of the data generated (Value).

The big data is all about the 4 V’s. With the data that is being generated every second, it can either be used constructively or destructively. With billions of devices being used with loads of data being transferred between these devices, it is easy for cyber attackers to attack these devices and data. to avoid this there needs to be a solution which is faster to identify the attack and also accurate in decision making. This is where big data and data analytics come to aid cyber-security against cyber-attackers. In the secure data analytics, the network managers collect data from several sources and analyse these data in big data analytical tools to detect or prevent any threat in real-time. Big data is considered as one of the best solutions against threat since, due to the huge volume of data and the speed of data usage (Angin, Bhargava, & Ranchal, 2019). It is also used to identify the account that might be compromised.

When it comes to security, there are three types of attacks also known as APT (Advanced Persistent Threat).

·       Advanced: This type of attack can be resolved with traditional methods of security

·       Persistent: This type of attack, the attacker has a specific goal.

·      Threat: Here the confidential data is compromised.

Benefits of using Data analytics for cyber-security:

·     Data Privacy and security: The privacy of the data and the security of the data are well preserved using the secure data analytics.

·     Cost efficient: using big data for security cuts down a huge cost to the organisation as this is designed to work on huge data sets derived on a lot.

·     Works fine even when less relevant data collected and sampled.

·     Efficient results are produced with both structured and unstructured data

·     Provides effective security solution on huge data

·     Time efficient: Since the process of analysis is done on large data sets, it consumes less time when compared to the traditional methods.