With so many internet security packages available, each offering antivirus, anti-malware and real-time protection, it’s often difficult to choose between the various products. While product details from vendor websites and online reviews from independent magazines will provide you with top-line information about what each package offers, these days you really need to dig a little deeper into the technology to truly understand what makes one security product stand out from another.

In its annual comparison of the most recognized packages on the market, AV-Comparatives, a leading independent testing organization, rated Bitdefender 2015 as Product of the Year. The security software obtained top marks in four categories – Malware Detection, Real-World Protection and Malware Removal and Best System Speed, following up strong performance by Bitdefender in PC Advisor’s own recent tests.

In this article, we’ll explain how Bitdefender’s security-based AI helps the company provide the best security on the market.

The Rising Threat

Considering that more than 140 million new malware samples were reported in 2014 alone, compared with around 80 million in 2013, security vendors need to move away from focusing on traditional security and consider the proactive and self-learning technologies designed to correctly and quickly identify the rising number of new and unknown threats. Bitdefender has managed to harness these technologies to ensure the best protection against all e-threats.

The first implementation of ‘Machine Learning’ in Bitdefender dates back to 2009, but since then the company has continuously and considerably fine-tuned its neural network algorithms to obtain a low false positive rate with maximum malware detection.

Bitdefender brings more fire-power in the fight against zero-day threats and APTs (Advanced Persistent Threats). The security technology company is actively implementing security-driven 'artificial intelligence' features inside its protection engines, by developing and using machine learning algorithms and techniques that provide new intelligence for its protective cloud infrastructure and increased protection for users. These technologies enable Bitdefender to outrun its competition and win the Product of the Year award from leading independent institution, AV-Comparatives.

What is Machine Learning?

Machine Learning is a type of artificial intelligence that gives computer programs the ability to learn and adapt when exposed to data. Specifically, Bitdefender uses security-centric Machine Learning algorithms to uncover new and unknown threats.

Applying Machine Learning in Software Security Products

When developing security-centric Machine Learning algorithms, it is vital to build models from example inputs and use that to make predictions or decisions, rather than follow static program instructions. They detect patterns in data, specifically online threats and malware, to improve their own understanding of how current threats behave and learn what new ones will look like.

The Key to Catching Unknown Threats

Bitdefender’s approach towards this new challenge is the use of cloud-based Machine Learning technologies that can identify new malware, malicious URLs and other online threats by processing and analyzing Big Data to obtain behavioral patterns and predict future advanced threats.

The use of advanced clustering and data mining techniques increases the speed and efficiency of malware analysis, boosting accuracy to almost 99% when specifically dealing with never-before-seen threats. These technologies not only ensure a low number of false-positives, but also enhance proactive security.

Machine Learning in AV - Fast Reaction

In a world where new threats occur daily, a fast response time is key. Built on top of a highly scalable Cloud infrastructure, Bitdefender instantly enforces protection to all internet-connected worldwide users against even the newest threats. For instance, protection against a threat newly found online only takes around 3 seconds to circle the globe and reach all users, keeping them safe even before a potential outbreak reaches their geographic location.

Machine Learning in AV - The Future of Security

All the above-mentioned Machine Learning technologies not only constantly work together, but are also trained to predict the characteristics of future malware by analyzing what we already know about how current threats behave. This constant additive knowledge enables Machine Learning algorithms to infer information from various data streams to find and detect new threat patterns. In essence, the more they learn about threats, the more accurate they become in predicting new ones.

The immediate benefits, such as increased threat detection and low false positives, are by far outweighed by the technology’s ability to learn how to proactively combat never-before-seen threats while globally safeguarding users from online perils in a matter of seconds.

This article is brought to you in association with Bitdefender.