Cybertech Tokyo 2017
Cybertech's first event in Japan - A one-day conference and exhibition on cyber solutions, innovations, and technologies
Machine-learning algorithms surface, within seconds, targeted threats that conventional solutions fail to identify.
Detect, analyze and respond to threats by means of big-data, forensics and hunting tools, providing rapid access to pre-processed granular data for superior visibility and rapid hunting.
Save hours to days of analyst work. Eliminate over 80% of the manual analysis process by viewing the entire incident storyline to reveal root cause and proceed to response and prevention.
Cyberbit EDR prioritizes threats, filters out false positives, and produces the results of an automated threat hunt, so your team to focus on responding to the most relevant threats efficiently, with minimal distraction.
Danielle VanZandt, Research Analyst, Frost & Sullivan
Unlike conventional solutions that rely on IOCs (Indicators of Compromise) and fail to identify unknown threats, Cyberbit uses a hybrid of machine learning and behavioral analysis to identify new and unknown malicious behavior in real-time, eliminating the need for the analysts to know what they’re looking for.
Analysts often work with fragments of the story to seek traces of attacks hidden in data. Cyberbit’s EDR platform assists analysts by automating much of this hunting process saving up to weeks of investigative effort.
Cyberbit EDR enables analysts to easily and rapidly execute endpoint specific or network wide response measures related to memory, file, registry, processes and network. The platform detects and blocks ransomware automatically, prevents encryption and backs up valuable data before damage is done.
Cyberbit provides SDKs for you to add custom analyses, REST APIs to visualize your data in any web interface, and APIs for importing and exporting data to your 3rd party tool of choice.
Read how HP Vertica and Cyberbit leverage big-data analytics to detect and hunt for unknown threats
Whitelisting can delay or interfere with attackers’ actions; however, it is often bypassed by attackers
and cannot serve as the standalone measure for security
Detect unknown attacks using machine learning and behavioral analytics