Machine-learning fuels Bitdefender’s intellectual property program, boosting the number of patents

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“Nowadays, if you stand still you won’t be able to keep your edge in the market or wherever you currently are,” says Florin Talpes, Bitdefender’s CEO and founder. “You have to be restless, in a good way. The moment you start looking for solutions and start to deepen and brush up these solutions, that’s where innovation is born.”

Bitdefender invests a quarter of its R&D budget in disruptive ideas. Artificial intelligence and machine-learning have become key drivers of innovation, boosting the number of patents.

From a total of 72 patents, Bitdefender has 42 patents issued for core technologies in past three years alone. In addition, 35 more are currently filed for examination. With almost 10 percent of Bitdefender patents pertaining to machine-learning algorithms for detecting malware and other online threats, deep learning and anomaly-based detection techniques play a vital role in proactively fighting new and unknown threats.

“There are two types of innovation – catch up, where you need to keep up with major market trends, and pioneering, which requires embracing higher risks,” Bitdefender’s CEO Florin Talpes says. “Bitdefender has successfully adhered to the latter.”

This philosophy fuels Bitdefender and is driving an acceleration in patent submissions.

Bitdefender holds patents in all major areas of interest: machine-learning, antispam/anti-phishing/antifraud, antimalware, virtualization, BOX-functionality, and hardware design, among others. Bitdefender’s team of engineers and researchers reached the 600+ milestone this year.

At Bitdefender, we’ve been working on machine-learning algorithms since 2009, constantly developing and training them to identify new and unknown threats. Artificial Intelligence and machine learning are essential to combat a threat landscape that is larger and more sophisticated than ever. Unlike other vendors, Bitdefender has years of experience in perfecting these technologies, and the results clearly show better detection rates with fewer false positives.

Machine-learning algorithms significantly improve detection time for modern threats, as they can analyze large amounts of data significantly faster than any human would. If trained to accurately detect various types of malware behavior, machine-learning algorithms can have a high detection rate, even on new or unknown samples. The merging of human ingenuity with the speed and relentless data analysis of machine learning significantly accelerates reactions against new malware samples, offering protection even from previously unknown samples – APTs, zero-day attacks, and ransomware. However, it’s not always just a single machine-learning algorithm doing the detection. Detecting ransomware, for example, requires several algorithms, each specialized in detecting specific families with individual behaviors. This significantly increases the chances of detecting similar looking malware samples while reducing the number of false positives.

Many of the patents below hold the secrets to Bitdefender’s most recent innovations - Bitdefender BOX, the breakthrough solution that protects all a user’s connected devices, and Hypervisor Introspection (HVI), a revolutionary framework to secure virtualized environments from advanced targeted cyber-attacks.

Bitdefender started integrating machine-learning technologies in its detection systems seven years ago, and recent patents have helped it achieve the highest detection rate for new malware released in the wild.

“Bitdefender’s culture of innovation built in the past 15 years started in 2002 with the IST Prize – considered the Nobel of Informatics – for MIDAS, the Malware Intrusion Detection Advanced System, a breakthrough technology that was considered at that time a revolution in the security industry,” Florin Talpeș comments. “Ever since then, patents and innovation have been strategic initiatives that are fundamental for our future growth.”

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