Dark Reading is part of the Informa Tech Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them.Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.

Partner Perspectives //

bitdefender

12/12/2016
10:00 AM
Razvan Muresan
Razvan Muresan
Partner Perspectives
50%
50%

Machine-Learning Algorithms Improve Detection Time For Modern Threats

Artificial intelligence and machine learning are essential to combat a threat landscape that is larger and more sophisticated than ever.

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.

Razvan, a security specialist at Bitdefender, is passionate about supporting SMEs in building communities and exchanging knowledge on entrepreneurship. A former business journalist, he enjoys taking innovative approaches to hot topics and believes that the massive amount of ... View Full Bio
Comment  | 
Print  | 
More Insights
Comments
Threaded  |  Newest First  |  Oldest First
MoviePass Leaves Credit Card Numbers, Personal Data Exposed Online
Kelly Sheridan, Staff Editor, Dark Reading,  8/21/2019
New FISMA Report Shows Progress, Gaps in Federal Cybersecurity
Curtis Franklin Jr., Senior Editor at Dark Reading,  8/21/2019
Register for Dark Reading Newsletters
White Papers
Video
Cartoon
Current Issue
7 Threats & Disruptive Forces Changing the Face of Cybersecurity
This Dark Reading Tech Digest gives an in-depth look at the biggest emerging threats and disruptive forces that are changing the face of cybersecurity today.
Flash Poll
Twitter Feed
Dark Reading - Bug Report
Bug Report
Enterprise Vulnerabilities
From DHS/US-CERT's National Vulnerability Database
CVE-2019-13139
PUBLISHED: 2019-08-22
In Docker before 18.09.4, an attacker who is capable of supplying or manipulating the build path for the "docker build" command would be able to gain command execution. An issue exists in the way "docker build" processes remote git URLs, and results in command injection into the ...
CVE-2019-15325
PUBLISHED: 2019-08-22
In GalliumOS 3.0, CONFIG_SECURITY_YAMA is disabled but /etc/sysctl.d/10-ptrace.conf tries to set /proc/sys/kernel/yama/ptrace_scope to 1, which might increase risk because of the appearance that a protection mechanism is present when actually it is not.
CVE-2019-15326
PUBLISHED: 2019-08-22
The import-users-from-csv-with-meta plugin before 1.14.2.1 for WordPress has directory traversal.
CVE-2019-15327
PUBLISHED: 2019-08-22
The import-users-from-csv-with-meta plugin before 1.14.1.3 for WordPress has XSS via imported data.
CVE-2019-15328
PUBLISHED: 2019-08-22
The import-users-from-csv-with-meta plugin before 1.14.0.3 for WordPress has XSS.