How User Behavioural Analytics Thwart Complex Cyber Threats

Would it be shocking for you that private firms across the globe spent USD 75 billion plus to safeguard their data assets in 2017 alone? According to Gartner, the number of companies is expected to increase with a ratio of 7% on average annually. However, it does not include the investment incurred by the banks to prevent frauds owing to unexpected expenditures and underreported statistics.

A question arises here that has the spending made by the companies helped them to save their customers’ data? Are consumers safe to share their personal information with private firms globally?

For your information, many analysts answered the questions as NO! However, it doesn’t mean that companies should say goodbye to their strategy for, but they should focus on more improved techniques.es.

Unreported information security hacks in recent years

The dilemma of these attacks is that organizations generally don’t speak about the threats publically. They think that discussing their cyber concerns can discourage potential consumers and investors. However, they focus on better security software and data protection techniques based on user behaviour analytics.

The Ponemon Institute has conducted a survey of around 1,371 end users about the information transparency offered by the companies. To your shock, approximately 62% of people revealed that they could access a chunk of confidential data of the companies while accessing their user account. This information should not be accessible to them because of accessibility rules and regulations.

So, what about information hackers? Put simply; they can quickly get into the systems as companies have a significant loophole in their data repositories.

How you can detect and thwart cyber threats with security analytics

Nevertheless, it takes millions of records to be inspected and scrutinised for determining 2-3 real threats. It is a hectic activity if done manually. However, it is possible to eliminate the time and effort taken for guesswork using advance cyber technology named User and Entity Behaviour Analytics (UEBA). It works on machine learning using the big data to understand normal endpoint behaviours and distinguish the abnormalities on the networks. The process is as given:

Roles are assigned

The data protection process starts from incorporating information into the system in an organised manner. For instance, the user roles are defined based on the titles including admin, HR manager, assistant, etc.

Further, data is correlated and analysed depending on the roles. In this regard, information about geographic locations, user activity patterns and authentication is collected to make identifications.

Data Analysis

After collecting necessary information, the next step is to transact the resources used, duration of sessions, user types, and nature of internet connectivity and typical behaviour of the peer group. The information is used to determine normal behaviour patterns to differentiate anomalous behaviours.

Risk Modeling

The most important task accomplished by the user behavioural analytics is to assess the probability of risks while considering normal usage patterns.

The formula used to analyse the occurrence of anomalies is Risk = Probability x Impact.

Takes Away

It is a well-established fact that with the advancement of technology, security packages have become more sophisticated and so the hackers too. It is the reason that information breaches now a day are more complicated in nature and scope as compared to the past years. It is evident from the fact that many incidents are not reported even.

However, companies can improve their cybersecurity by implementing behavioural analytics which helps them to scrutinise suspected users based on defined patterns and artificial intelligence.

Don’t lag in the race of data protection when you can get advance information security based on threats intelligence and user recognised patterns of behaviours!

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