Time is a big expense when it comes to detecting cyber threats and malware. The proliferation of new malware variants makes it impossible to detect and prevent zero-day threats inreal-time. Sandboxing takes at least 30 minutes to analyze a file and deliver a signature – and by then, threats will have spread to many more endpoints.
However, cybersecurity based on data science, machine learning and behavioral analytics can identify the cyber attackers spying, spreading and stealing inside the perimeter in real-time and automatically correlate these behaviors to the computer being attacked. This approach provides security analysts with actionable insight to stop the attack and to prevent further damage.
Prevention security at the network perimeter provides one imperfect chance to stop an attack. Security professionals need automated real-time malware detection and prioritized risk reporting that show what an attacker is doing in their network and provide multiple opportunities to stop an attack. The Vectra software is the first to bring this level of intelligence and automation. Read this white paper to learn how.
Jerish Parapurath is a cybersecurity and technical training consultant with 20 years of experience in network and cybersecurity, including 8 years of management experience in hiring, mentoring, leading, and team building. He was director of technical product marketing for Vectra and previously was a senior manager of technical marketing at Palo Alto Networks. He received a bachelors degree in electronics and communication from Bangalore University.