Businesses today operate in a sophisticated IT environment involving cloud and many other technologies to keep ahead of the competition. However, operating in such an environment requires every business to be capable of identifying security threats, or any security-related events for that matter, to minimize the impact should anything bad happen.
Where cyber security of business stand today
Verizon’s 2017 Data Breach Investigations Report says cyber-attackers employ a variety of techniques during their campaigns – close to 62% attacks were linked to hacking, while 51% used malware. 14% of attacks were due to mistakes from employees that led to exploitable security gaps.
Now that AI has started dominating, cyber-attackers can use it as well – from identifying security vulnerabilities to scaling their attacks and personalizing phishing mails. All of this demand businesses to have stringent security measures in place. They will have to constantly keep both eyes on the network for a wide range of potential threats that resemble conventional cyber-attack patterns.
Fortunately, the massive amounts of real-time and historical security event data of a business can help it prepare for almost all kinds of security threats. Then, the challenge would be to make sense of such large volumes of data. The business would then need the right tools to analyze and correlate the data. Advanced analytics techniques thus become critical for modern-day businesses to defend against complex cyber-attacks.
What they can do
In case of a suspicious event, information security department of the enterprise along with the threat response team can run queries in real-time against their large datasets so as to verify the impact and duration of the potential threat. Analysts can then either confirm the threat and proceed with investigating it or discount it as just an anomaly.
But in order to this, they are obviously going to need serious hardware power and fast analysis capabilities, not to mention accurate and consistent data. Security teams of most businesses might be capable of handling such a gargantuan task with cutting-edge digital solutions. But not all such solutions were designed with big data in mind.
Big data – cyber security in practice
Most such solutions were designed for on-premise environments, and processing huge amounts of data in real-time might require the business to scale their infrastructure which can be costly. Storing such data can be an expensive challenge as well.
One feasible option is keep historical data accessible to the security team for a certain period of time. As soon as an event occurs, analysts can analyze the historical data and investigate the depth of an attack. However, this approach limits the effectiveness of the security team over long periods of time.
Fortunately, again, the cloud can address this particular challenge effectively by overcoming cost-prohibition and similar challenging economics associated with data processing and analyses. Cloud storage solutions make big data more acceptable in an enterprise. Enhancing existing security solutions so they can work with big data platforms is also a nice approach which can make the entire system capable of exploring massive datasets at scale, subsequently improving the overall security aspect.
In practice, all this can be overwhelming for the security team of a big enterprise. But that kind of fatigue can be alleviated with the use of machine learning and AI. With AI, the organization can prioritize specific security alerts and automate responses and procedures reducing the security team’s effort significantly. As a matter of fact, ML-based systems can be trained to spot suspicious behavior patterns that pre-defined security policies may miss. But this approach requires the business to invest significantly in data science skillsets.
If a combination of all of these technologies are to deliver great results, there should be adequate collaboration between the human resources. Security teams comprising of threat response units, forensic analysts, and IT professionals should be able to collaborate in a data environment which can streamline and speed up the processes involved.
Ultimately, the big data approach is the right way to augment cyber-security enough to withstand the risks of this age. For this approach to be effective, however, it should be complemented by other powerful technologies that can shield an organization from cyber-attacks or at least let the organization know if there’s a chance for something bad to happen.
The cloud, machine learning, AI, and collaboration solutions combined can help big data deliver optimal results for enterprises concerned about cyber-threats. Choosing the right platforms can make all the difference in securing enterprises.
If you still have queries related to cyber-security and what technologies like the cloud and big data can do for your organization’s cyber-security, AoT may have all the answers you need. Drop us a message to explore your options and understand how we can help you with this particular challenge.