Nowadays, threats and attacks increase quickly together with the innovation of IT networks. Due to the complexity and volume of reported malware attacks, bigger problems have come up. For standard analytic tools, it will be tough to spot and recognize these threats because they evolve as technology develops more.
An insufficiently protected system is highly-susceptible to unknown breaches. Whitelist systems execute various solutions on collected data, protecting them from further malware attacks and real-time threats. However, the so-called “goodware”, at some point, may change and become utilized for malicious purposes. Virtually, it would be impossible for a system to react since the software is already whitelisted. It then becomes very essential to observe software activity at all times, monitoring it and preventing any suspicious type of action.
The Essence of Modern Tools in the Modern Times
Many companies have to shield their systems from all kinds of attacks. However, only one successful attempt from an attacker is needed to have access in everything they’re hiding. Devices that are protected by “traditional” methods are more likely to be victims of unknown attacks. As technology advances, threats are able to find their way quickly to our systems. Modern times require modern tools, and this is where Big Data comes in handy.
Real-Time Threat Detection with Big Data
As sad as it may seem, most companies tend to cling on to what is “tried and tested” when it comes to cybersecurity. This action inhibits them from discovering a wider and even more effective method of protecting their systems, while cybercriminals continue to thrive on the matter. Every security officer needs to realize that protection is an active system and not just a stagnant method in order to put it into effect.
An effective EPP solution should be able to detect changes in data activities at all times. Such activities include user activity, logjams, network events, and the like. But this can only be possible with advanced data analysis, and of course, the probability of collecting a ton of data. Unlike traditional antivirus solutions, modern alternatives such as Big Data utilize advanced algorithms to enhance their tasks.
The effectiveness of such solutions is almost fool-proof, as it can anticipate both internal and external attacks, and produce automatic workflows to guarantee protection.
Anti-virus and Big Data for Advanced Security
To get rid of the older Antivirus methods’ inefficiencies, next-gen security methods must automate malware analysis instead of simply depending on previous samples taken from past occurrences. These solutions are constructed on a multi-layered and dispersed cloud environment. This implies that antivirus engines would no longer be responsive to only one client, and would instead be sited on the cloud, avoiding any manipulation of any system’s best antivirus software.
When these multiple detection engines are able to work despite being connected to different client computers, the speed of analysis for received data would greatly improve. Constant study of data’s behavioral patterns makes it feasible for security officers to analyze patterns just before the attack actually happens.
In order to successfully conduct the data-visualization process, heaps of data are required. This is made available only because the cloud network is connected in real-time. This is when big data analytics comes in. It helps to recognize and block online threats before a breach has a chance to happen and compromise a system.
Big Data in Enhancing Antivirus Performance
Cybersecurity Analysts are more and more convinced that vendors are no longer focused on the thought of threats coming in “one at a time”. They are now starting to gather data and look at broader trends over time.
Big Data, with its wide array of uses not just in improving an institution’s profit, has great benefits for antivirus performance and online security. Knowing exactly what’s happening with your data in real-time, and looking deeper into malware activity can avoid greater problems in the future.
As threats widen, so do the methods of averting them. The different tools used to gather and evaluate security data have improved greatly over the years. There is now a deeper and more in-depth intelligence when it comes to this matter. These days, utilizing Big Data as the ground for defending systems against new threats can mean the difference between a company’s success and downfall. An institution’s stability relies on proper security, and proper security relies greatly on having full control over every facet of your network.
