There is no one single way to cybersecurity, because the cyber landscape is ever-evolving, continuously in flux…
Most organizations these days face a wider range and greater frequency of cyber threats than ever before. These threats can be from:
• APTs (advanced persistent threats),
• cyberwarfare,
• promiscuous attacks through bots and botnets,
• script kiddies,
• malware-as-a-service via the Dark Web, or
• even internal attacks from entities within your organization, etc
Everything from distributed denial of service attacks (DDoS) to crypto-jacking, from man-in-the-middle attacks to spear phishing, from ransomware to data breaches, all are hitting companies of all sizes and in all industries constantly and every single day.
Most companies wants to improve their overall security response time. In order to achieve this, what do they do?
They deploy perimeter controls, they deploy communication controls, they deploy content-based security controls, thereby they control the access to their IT resources. They try their best to monitor and report all sort of suspicious activities going in and around them.
It’s perfectly normal for them to find it all to be overwhelming!
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Let's get back to the question--
What exactly the Cybersecurity Analytics is?If I could explain it in a single sentence, then I would say that--it is Proactive Context-based Security Intelligence!
Security analytics isn’t about any one particular type of tool or system. It is a way of thinking about cybersecurity proactively. It involves analyzing your network’s data from a multitude of sources in order to produce and maintain security measures. It’s all about aggregating data from EVERY POSSIBLE source. It is not about looking at the trees, rather looking at the forest as a whole.
Security analytics is an approach to cybersecurity that analyzes data to detect -- anomalies, unusual user behavior, and other cyber threats. It aggregates data from across your entire IT ecosystem and turns that data into actionable insights so that your IT teams can proactively act to minimize risks and prevent security incidents.
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When you look at it from that angle, all the following matters a lot to you from analytics point of view:
► Your cloud resources
► User data acquired from the endpoints
► Logs from your network security appliances, such as firewalls, IPS, and IDS, etc
► Your network traffic and its patterns
► Identity and access management logs
► Threat intelligence
► Geolocation data
► Mobile devices and storage mediums connected via WiFi, Ethernet, and USB
► Antivirus applications
► Business specific applications
There are more tools which you should deploy to get better with your Security Analytics:
► Code analysis applications to find vulnerabilities in software and scripting
► File analysis tools to explore files in ways which may go beyond malware detection
► Log analysis applications for firewalls, IDS, IPS, networked print devices, servers, and endpoints
► SOC (security operations center) specific applications to organize data in a way which is useful for their functions
► DLP (data loss prevention) tools
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Great Need Of Security Analytics
Using this analytics approach and the right tools, will allow you to have a look at cyber threat patterns over months or possibly even years, as long as your network data is properly stored and maintained. It will help you to get a “big picture” view of what may be going on with your network.
It can even help you show your organization’s stakeholders and management which security measures and policies are useful and worthy of their investment. When cybersecurity analytics are properly implemented, they can not only improve your network’s security posture, but also help your organization with regulatory compliance needs, such as HIPAA and PCI-DSS etc.
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The role of Artificial Intelligence & ML
Machine and operational logs generated by disparate sources and IT assets (Server, Network Security Devices, Applications) carry a lot of useful information, but analyzing this information manually and individually without missing events of interest poses a unique challenge for the organisation as well as the information security practitioners.
By using a security analytics tool equipped with AI and ML, along with security policies and best practices, organizations can make big strides towards reducing risks across their architecture.
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How does machine learning work with security analytics?Machine learning is a software capability that allows software to improve its own performance at a particular task using relevant data.
Here’s how this works:
1. For machine learning to apply useful security insights, a ML engine needs access to a lake of diverse data drawn from events, applications, network activity, and user behavior across an organization. The best way to fill this big data lake is by integrating security analytics with a unified workspace that contains all the data sources mentioned above. This simplifies the data collection process and helps ensure all data is relevant.
2. Once an organization’s security analytics platform has filled its data lake, the next step is to correlate this data to individual users inside the organization. This is the beginning of the risk profiles that the ML engine will develop later.
3. After this data is correlated to distinct users, the machine learning engine can be applied to develop insights into how those users behave at work. This allows the machine learning technology to gain insights into each user’s normal activity and behavior that the organization would otherwise not be able to obtain.
4. Now that the machine learning engine has developed these actionable insights, it creates specific risk profiles for each user inside the organization. This allows the security analytics tool to continually score the user’s session for risk. If a user began acting suspiciously by deviating from their normal work activity, the security analytics platform would recognize this aberrant behavior immediately thanks to the risk indicators developed by the ML engine.
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Always keep in mind that-- the primary benefit of security analytics is delivering END-TO-END SECURITY VISIBILITY to your IT systems.
Please let me know of what do you think about this in the comment section. You can also share with all if the information shared here helps you in some manner.
Kindly write your comment on the posts or topics, because when you do that you help me greatly in designing new quality article/post on cybersecurity.This Article Was Written & published by Meena R, Senior Manager - IT, at Luminis Consulting Services Pvt. Ltd, India.
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