User and Entity Behaviour Analytics (UEBA) is an Automated Threat Hunter and it helps to detect users or entities within the corporate network who could compromise systems.
We have already observed that the adoption of digital transformation across all industrial sectors has been further accelerated with the onset of the Covid-19 pandemic. Unfortunately, the expanding network of digital assets and processes has also broadened the security threat landscape, compelling organisations of all sizes across India to re-look into the cyber-security strategy and associated priorities.
Corporate India’s Business, IT, and Security leaders are exploring various methods and technologies that help in identifying and securing every touch-point across the organisation. Whether the organisation is sufficiently equipped with tools to mitigate risks and necessary measures put in place, besides being compliant with all applicable regulations and laws are some of the key boardroom concerns. The leadership team wants to develop an organisational culture of shared cyber responsibility so that every employee is made aware of the risks of security breaches and benefits of security measures. Other areas that also need emphasis are security in the remote working environments, supply chain ecosystem security, and cyber-security priorities.
[box type=”info” align=”” class=”” width=””]A recent survey conducted by Price Waterhouse Coopers ‘The future ahead: Evolving cyber priorities in India’, reveals ‘Proactive monitoring through User and Entity Behaviour Analytics’ among the top 6 focus areas or cyber-security priorities. [/box]
User and Entity Behaviour Analytics plays the role of a clever detective for insider threats
Yes, UEBA is an Automated Threat Hunter and it helps to detect users or entities within the corporate network who could compromise systems. Cyber-criminals, among other ways of attacking networks and systems and steal data, sometimes bribe employees at the organisations to gain access to business-critical data and cause financial as well as reputation damage. In some cases, a negligent user’s credentials can be easily stolen to get into the system stealthily and exfiltrate data. UEBA, operates in real-time, using machine learning, behavior-based security analytics and artificial intelligence. It detects threats based on contextual information and enforces immediate remediation actions.
[box type=”warning” align=”” class=”” width=””]Whenever there is a slight deviation in the user’s normal behaviour within a network, UEBA starts to sound alerts for the immediate next course of action that should be taken by the team. Rogue employees or teams trying to steal data leading to data breaches or policy violations can be detected easily with UEBA. Many a time, employees can unwittingly be responsible for compromised accounts, and these need to be eliminated before causing further harm to the organisation’s network. [/box]
UEBA tools and techniques complement security monitoring solutions
The limitations of traditional techniques are that they cannot adapt to address the continuously evolving new-age threats and system behaviour. The advanced analytics tools used in UEBA are what that help to identify abnormal user behaviour without the need to understand known patterns.
Technologies and methodologies used in UEBA help to tighten the organisations overall security posture. AI and ML and advanced statistical analysis of data are leveraged to strengthen cyber-security by monitoring users and detecting anomalies in their behaviour patterns and thereby prevent security breaches. Normal human behaviour is analysed and application of algorithms and statistical analysis are done for any detection deviation. Financial frauds and targeted threats can be addressed too, with UEBA tools that leverage new-age technologies.
Supervised Machine Learning are different sets of known good and bad behaviours that are fed into the system. The tool learns to analyse and categorise the user’s behaviour accordingly.
In Unsupervised Learning, the system learns normal behaviour and thereby detects or alerts abnormal behaviour, which is a deviation from the normal.
Deep Learning is also leveraged where the system learns about data sets, security alerts and triage outcomes and will predict the same for new data sets.
Risk scores are computed where security alerts are set when the score exceeds the threshold level. Intelligent incident response mechanism and programming for continuous threat detection and effective remediation are few of the other measures used in UEBA.
UEBA solutions can be deployed in hybrid environments – both on-premises and on cloud, across industrial sectors, including, BFSI, Healthcare, Retail, IT and Telecom, Power and Government among others.
Recent reports say there will be significant growth in the global UEBA market size, including India, in the coming years. Several factors contribute to the high rate of growth of the market, such as, increasing need to stop insider threats, growing adoption of user-centric approaches, advancements in ML and Analytics and the shortage of trained cyber-security professionals.
ProcessIT Global, an IT Services and Solutions’ organisation supports customers to fast track their Digital Transformation efforts so that they become future ready. It also helps organisations to achieve highest standards of Cyber-security, AIOPs and Automation. The organisation’s Cyber-security services are based on NIST 1-1 Framework. ProcessIT Global’s services include, Advisory and Consulting, and Design and Implementation in addition to Support, Operations, and Maintenance services.