What makes big data so successful for cybersecurity is also its biggest risks. In large organizations like Facebook or Google, their system collects, stores and analyzes enormous volumes of data. In the right hands, this information can be used to predict trends and improve cybersecurity. However, in the hands of threat actors with malicious intent, big data a prime target for cyber attacks. Here are 3 ways how data analytics help to avoid cyber security.
1. Threat Visualisation
Data analytics softwares and programs help you anticipate, judge and classify intensity of cybersecurity threats. The complexity of a possible cyber attack can be determined by evaluating its data sources and pattern. It is also through the use of data analytics tools that allows you to use the huge amounts of data you own to get an understandings of which trends are acceptable and which requires immediate attention.
2. Predictive Analyses
Intelligent data analytics enables experts to build a predictive model that can issue an alert as soon as it detects a cybersecurity attack. Additionally, machine learning and artificial intelligence can play a major role in developing such systems. Analytics-based solutions empower you to predict and gear up for possible events in your process.
3. Staying Ahead Of Hackers
Network security teams can make use of infrastructure penetration testing to obtain an insight for your business database, process and help keep hackers at bay. It is a simulated malware attack against your computer systems and network to check for exploitable vulnerabilities. Think about white hackers. These people are paid to hack and explore capabilities/loopholes of your existing analytics solutions so that they can be fixed. Therefore, penetration testing has become an essential step to protect IT infrastructure and business data.