Variant Payload Prevention: Applying Data Science to Stop the Stealthiest Threats
Cybereason’s Variant Payload Prevention employs a new proprietary algorithm for fuzzy similarity called Binary Similarity Analysis (BSA).
Lital Asher-Dotan
Domain Generation Algorithm (DGA)-based malware, like GameOver Zeus and CryptoLocker botnets, introduces a massive threat, not only because of the vast financial implications they impose, but also because of how difficult they are to detect. Even the FBI's efforts to stop a DGA-based operation were ineffective, as was lately discussed in a post by Lotem Guy.
In order to make a stand against complex malware, like DGA-based malware, there is a need to employ new dynamic detection approaches.
Our latest eBook offers a new approach for the detection of attacks employing Domain Generation Algorithm (DGA) techniques. Download the eBook to learn:
Lital is a Marketing Team Leader, Storyteller, Technology Marketing Expert. She joined Cybereason as the first marketing hire and built a full marketing department. Specializing in brand building, product marketing, communication and content. Passionate about building ROI-driven marketing teams.
Cybereason’s Variant Payload Prevention employs a new proprietary algorithm for fuzzy similarity called Binary Similarity Analysis (BSA).
The MalOp Severity Score and Extended Response enable threat detection in less than 1 minute, triage in less than 5 minutes, and remediation in less than 30 minutes. ..
Cybereason’s Variant Payload Prevention employs a new proprietary algorithm for fuzzy similarity called Binary Similarity Analysis (BSA).
The MalOp Severity Score and Extended Response enable threat detection in less than 1 minute, triage in less than 5 minutes, and remediation in less than 30 minutes. ..
Get the latest research, expert insights, and security industry news.
Subscribe