Machine-Learning Algorithms Improve Detection Time For Modern Threats

Artificial intelligence and machine learning have become key drivers of innovation. Machine-learning algorithms significantly improve detection time for modern threats, as they can analyze large amounts of data significantly faster than any human could. 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, offering protection even from previously unknown samples – advanced persistent threats, 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.

For its part, Bitdefender invests a quarter of its R&D budget in disruptive ideas, boosting its number of patents. From a total of 72 patents, Bitdefender has had 42 patents issued for core technologies in the past three years. In addition, 35 more are currently filed for examination. With almost 10% of Bitdefender’s 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.

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. The company has been working on machine-learning algorithms since 2009, 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.

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

Bitdefender started integrating machine-learning technologies into its detection systems seven years ago, and its recent patents continue to help it achieve a high detection rate for new malware released in the wild.