Everything You Need to Know About Cyber Analytics
The steady advances in technological terminology over the last few years, coined a new buzzword; “Cyber Analytics”. The question, “What is Cyber Analytics”, points out that there is much more going on behind the screen surface of a computer than a mere sequence of numbers. Cyber Analytics is all about those numbers and how they can be organized to initiate a search and analysis process leading to a solution.
No matter if you have a security operation centre or your network is on-premises in the cloud or a hybrid, it has become crucial for every organization to determine which events and indicators correlate with cyber-attacks. There is a wider range and greater frequency of cyber threats in front of organizations than ever before. These threats can be from:
- APTs (advanced persistent threats),
- Promiscuous attacks through bots and botnets,
- Script kiddies
- Malware-as-a-service via the Dark Web
- Or even internal attacks from an entity within your organization.
Breaches like distributed denial of service attacks (DDoS), crypto-jacking, man-in-the-middle attacks, spear phishing, and ransomware are constantly hitting businesses of all sizes and in all industries. You need the right tools and practices that can help you make sense of all the cacophony and this is the part where Cybersecurity Analytics comes into play.
What is “Cyber Analytics”?
Cyber Analytics -often referred to as Security Analytics- is the process using which computer scientists analyse data to create, implement, and maintain digital security. It is carried out by monitoring your network and by identifying the time when it has been compromised. Ideally, the goal is to prevent such attacks from occurring in the first place. But security analytics isn’t just a tool or system, rather it’s a way of proactively thinking about cybersecurity. It involves analysing your network’s data from a multitude of sources to produce and maintain security measures.
The process uses algorithms, behavioural analytics, machine learning, statistical analysis, and other classes of analysis for solving cybersecurity problems and reducing threats in a way that traditional security controls can’t. These analytics are often compared with indicators of compromise (IoCs), but the use of analysis to detect potential and unknown threats that signature-based IoCs miss, is the differentiating factor.
Cyber Analytics: Sources and Tools
There are a lot of data sources that can be used in your cybersecurity analytics practice such as cloud resources, user data acquired from endpoints, logs from network security appliances, etc. These appliances could be firewalls, IPS, and IDS. Other sources are identity and access management logs, network traffic and its patterns, threat intelligence, geolocation data, Ethernet and USB, mobile devices and storage mediums connected via Wi-Fi, antivirus applications, and business-specific applications.
Other tools that your network can deploy related to Cyber Analytics are:
- Code analysis applications that are used to find vulnerabilities in software and scripting.
- File analysis tools to explore files beyond malware detection.
- Security Operations Center (SOC) specific applications needed to organize data in a useful way.
- Data Loss Prevention (DLP) tools.
Cyber Analytics: Use Cases
We can implement Cyber Analytics for a wide variety of use cases starting right from user behaviour monitoring to network traffic analysis. Some of the most common use cases include:
- Detecting patterns that indicate a potential attack by analysing network traffic.
- Monitoring user behaviour and detecting insider threats along with data exfiltration.
- Identifying compromised accounts.
If implemented properly, Cyber Analytics can not only improve your network’s security posture, but it can also help you with your organization with regulatory compliance needs.
- It is ideal for industry-specific regulations like HIPAA and PCI-DSS that require log data collection and activity monitoring.
- It can also help you identify the security measures and policies that are useful and worthy of investment.
Cyber Analytics: What’s the Need?
Cyber Analytics is constantly growing. It is full of potential and offers a robust solution for organizations that are looking to stay on top of vulnerabilities and be always one step ahead of cybercriminals. It’s required for:
- Transitioning from protection to detection: Those trying to hack your system, use a wide range of attack mechanisms to exploit multiple vulnerabilities. Some of those threats can take months to be detected. Hence, you need Cyber Analytics tools that can keep track of common threat patterns and can alert you instantly when an anomaly is discovered.
- A unified view of the enterprise: Cyber Analytics helps you structure data in a way that offers both a real-time and historical view of events. It not only provides you with a unified view of threats and security breaches from a central console but also helps you with smarter planning, faster resolution, and better decision making
- Seeing results and a return on investment: IT teams feel constant pressure while communicating results to senior management and stakeholders. Cyber Analytics helps you by providing time-to-resolution metrics and fewer false positives allowing analysts to quickly identify threats and respond to security breaches accordingly.
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