IT networks have grown increasingly sophisticated and complex due to the tremendous digital revolution in the commercial world. Organizations swiftly realize that a reactive strategy is insufficient to handle cyber risk in today’s increasingly digital world. It is where cyber security Analytics comes in!
Nowadays, security teams rely on Cyber Security Analytics solutions to give insights generated from data, detect and examine threat alerts as they happen, and deliver insights. The predicted value of the worldwide cybersecurity market in 2020 was $156.24 billion. According to estimates, the worldwide cybersecurity market will be worth $352.25 billion by 2026 and will increase by 14.5% annually.
Cybersecurity analytics does the aggregation, attribution, and analysis of data for information extraction required for a productive approach to cybersecurity. Because things are continually changing within a network, traditional security information and event management systems (SEIMs) depend on point-in-time testing, which creates room for error.
As a result, evaluating the posture of an organization’s cybersecurity at a specific time is not an accurate representation of its actual ongoing security activities. In order to monitor a network and identify changes in usage patterns or network traffic so that dangers may be instantly handled, security analytics makes use of machine learning capabilities. The average annual income for a Cyber Security analyst in India is INR 5.0 Lakhs.
Security analytics provides enterprises with a solid solution for staying on top of vulnerabilities and one step ahead of cybercriminals. Cyber security threats (phishing, hacking, cyber security attack, etc.) are commonplace and must be dealt with firmly.
The following factors are important for developing security analytics:
Hackers employ various attack techniques that take advantage of the vulnerability in cyber security. Some hazards may go months without being noticed. Security analytics systems can monitor typical attack trends and inform users as soon as an unusual one is found.
Security analytics organizes data in such a way that it provides both a real-time and historical picture of occurrences, creating a unified view of the company. Giving users a consolidated view of risks and security breaches from a single interface enables better planning, quicker problem-solving, and more informed decision-making.
IT teams are under increasing pressure to share outcomes with senior management and stakeholders. Analysts can swiftly identify risks and respond to security breaches thanks to security analytics’ time-to-resolution metrics and lower number of false positives.
Tools for data analytics in cyber security give the additional context and external threat intelligence required to find links between alerts and specific events or changes. Security analytics technologies can function in close to real-time, enabling speedy detection, and can aggregate enormous amounts of data in one location.
In order to make it simple for security teams to decide what has to be fixed first, security analytics solutions can rank warnings according to severity and provide detailed information on potential vulnerabilities.
Because there is so much data accessible, automated threat intelligence is very useful because it reduces the time spent performing manual security chores, increases accuracy, and makes it easier to find network vulnerabilities.
Tools for security analytics integrate recent data with historical analysis to find anomalies or patterns in network traffic and user activity. Security teams can respond to risks in a proactive manner by looking for anomalies in these patterns that may be signs of an impending attack or careless user activity.
Forensic investigations are essential to stop similar occurrences from happening again. Security analytics tools can assist in locating the threat’s origin, the individual accounts or data that were compromised, the attack’s intensity, and other information. Then, based on this data, judgments about the next security initiatives are made.
Some of the most common use cases for security analytics are given below.
An organization can avoid a potentially expensive security breach or cyberattack by using a security analytics program, which offers real-time insight and a historical record of past threats. Having an efficient security analytics system is extremely important for ensuring the security of an organization’s data and IT systems. Also, there has never been a greater need for graduates with degrees in cybersecurity or cyber analytics. Because of the increased demand for qualified workers, earnings have increased, and numerous scholarship opportunities are emerging.