In traditional cybersecurity arrangements, data had little to no role to play. It was managed in an ad hoc manner and manually handled by security analysts. However, as cybersecurity attacks increased in volume and complexity, such conventional approaches met limitations in mitigating threats and reducing their risks to businesses and organizations.
As a result, the cybersecurity systems of today and tomorrow have become more flexible and efficient mechanisms to responding to and mitigating threats. In order to develop these sophisticated security solutions, businesses have had to think about analyzing massive amounts of data generated from various sources, including cybersecurity solutions, to generate security policies and rules with minimal human intervention using automation.
This is only one of the many things data can do to strengthen the cybersecurity posture of an organization. Here are some more useful tips coming from TEHTRIS SOC and TEHTRIS R&D.
Today, our lives depend on technology to learn, work and interact. Unfortunately, this reliance makes technology a massive target for someone wanting to disrupt the normal course of people’s lives.
Attackers are using the coronavirus pandemic to trigger cyberattacks aimed at confusing and hindering healthcare systems from working to save human lives. We are witnessing a staggering 667% increase in phishing attacks owing to the pandemic this year.
There is an increasing trend of attacks targeted at healthcare organizations, even the World Health Organization was not forgiven. While coronavirus will cost the global economy a whopping $2 trillion, cybercrime might triple that amount by 2021 to $6 trillion.
The only way to curb this growing threat is to take a data-driven approach to cybersecurity. Data-driven cybersecurity is an arrangement where big data is used to make informed decisions about the cybersecurity practices in a company. It provides an action plan in the face of a security event and an action plan to safeguard data and applications.
When data lies at the core of its strategy, it becomes a data-driven cybersecurity approach.
Data often shows and knows what we do not. Big data analytics refers to analyzing large, varied volumes of data often untouched by regular analytics software. The data can be structured, unstructured, or a mixture of both. This data can be used to analyze historical patterns and come up with better security threat controls.
Through a combination of big data, machine learning, and artificial intelligence, businesses can perform a thorough analysis of current and past data and determine what is “normal”. Based on the results of these findings, organizations can strengthen their cybersecurity arrangements to raise flags when there is a deviation from the expected and the normal.
For instance, if an organization tracks running software on employees’ devices, it will detect patterns such as normal time frames when employees works and normal binaries that are commonly used. If a program follows a phishing link, the system can ward it off and flag it with the knowledge of the time and the URL address that was used. This is how we work at TEHTRIS, by smoothly breaking the digital frontier between a machine learning process, with the needed operating system’s behaviors recorded, and the cybersecurity world.
Indeed, data-driven security is a viable, feasible and necessary solution for businesses that want to solidify their cybersecurity posture and safeguard their infrastructure.
If a company has been a victim of a cyberattack, following the anomalies that ultimately led to the event through data analysis can help identify the patterns used by the hackers before they gained access to the network. The company can then make use of machine learning to ensure the same event does not occur again.
However, data-led security does not stop there. The next step is to automate the process as much as possible so that deviations can be picked up faster and threats can be mitigated quicker.
According to CSO Online, 84% of businesses use Big data to block cyber-attacks. These companies also reported a handsome decline in breaches after introducing big data analytics to their security operations.
Data-led cybersecurity can allow organizations to gain significant insights into their overall cybersecurity posture, and specifically leads to:
Data-driven cybersecurity also lies at the heart of artificial intelligence in threat prevention and detection. AI has several use cases for cybersecurity, some of which are currently being used by sophisticated cybersecurity solutions such as TEHTRIS XDR.
Learn more about data-driven cybersecurity in our next posts. Subscribe to the series by following us on Linkedin.