That’s how one customer described the importance of Automated Malware Analysis technologies in their security workflow. After months of demonstrations, reference calls, and analysis we are thrilled that The Forrester Wave™: Automated Malware Analysis, Q2 2016 is live! Many clients we talked to used multiple vendors to analyze malware in order to maximize analysis results.
The underlying mechanisms for automated malware analysis are fascinating for the technophile - combining content security, hypervisor-driven execution, behavioral analytics, and algorithmic API analysis. Incredibly sophisticated software engineering and statistical modeling adds another layer of intrigue. Mix those together with evasive adversaries attempting to bypass the technology and it's an intense discussion!
We used the importance of AMA solutions as the dominant element of detection and prevention in client environments to inform our assessment.
Here’s an overview of our approach:
Visibility is a cornerstone of detection and protection. In order to detect it, you must see it in the first place.
Flexible deployment models are key to dynamic production environments. If it is hardware or on-premise only, then it only fits in environments that match the form factor.
Scalability avoids creating a problem as the environment grows. Scalable infrastructure allows the business to orchestrate workloads based on need and priority, AMA solutions should offer the same capabilities to better align with technology needs.
Data management history has shown, it is not what you buy; it is how you are able to use it that makes a difference. According to survey results from the Q4 2012 Forrsights BI/Big Data Survey, this is a story that is again ringing true as big data changes the data management landscape.
Overall . . .
Big technology adoption across various capabilities ranges from 8% to just over 25%.
Plans to implement big data technology across various capabilities is as high as 31%.
Pilot projects are the preferred method to get started.
However . . .
High-performing organizations (15%-plus annual growth) are expanding big data investments by one to two times in many big data areas compared with other organizations.
The key takeaway . . .
For most organizations, big data projects aren't leaving the pilot stage and aren't failing to attain strong return on investment (ROI).