NEW YORK – With the rise in malware and new attack vectors, Deep Instinct, the first company to apply deep learning to cybersecurity, has introduced new threat analysis services to provide superior visibility and analysis of new and emerging threats.
Deep Instinct's approach to security predicts and prevents the latest threats before any potential damage can occur. Its new threat analysis services leverage deep learning capabilities to provide better visibility and understanding of threats as they are discovered. This offering features Deep Classification to provide automated, real-time malware classification without human involvement, and an Advanced Threat Analysis to provide a greater level of detail around threat incidents. In addition, the detailed Deep Threat Analysis Report, delivers in-depth findings, insights, statistics, highlights and assessment on the latest threats found in the organization network and adds malware analysis for each malicious campaign found.
Not only can deep learning be used to prevent malicious files from running, it can also provide threat analysis by classifying in real-time what type of malware is targeting the organization. Deep Instinct's Deep Classification capability based on Deep Neural Network (DNN) ensures that any malware, known and unknown, is classified rapidly and autonomously. Once malware is detected, it is scanned again by the classification brain providing results in milliseconds for the file malware family, without any human involvement. The Deep Neural Network brain is able to classify between 7 malware family types: Ransomware, Backdoor, Dropper, Spyware, Virus, Worm and Potential Unwanted Applications (PUAs).
The addition of the Advanced Threat Analysis provides a tool set that performs advanced analysis on top of threats found in the organization, as part of the D-Appliance management console. It includes static analysis, sandboxing analysis, screenshots and network dump of the potential threats.
Deep Instinct has disrupted the traditional cybersecurity market with new levels of accuracy that enable it to predict and prevent new first-seen threats others cannot find. It uses a proprietary artificial neural network inspired by the brain's natural ability to learn and is the first of its kind to be applied to cybersecurity. It scans 100% of the raw data sets with unprecedented, industry leading precision to protect against zero-day threats and Advanced Persistent Threat (APT) attacks, while ensuring lowest false positives and an overall safer organization.