Cloud computing continues to transform the way organizations use, store, and share data, applications, and workloads. It has also introduced a host of new security threats and challenges. With so much data going into the cloud—and into public in particular—these resources become natural targets for bad actors.
“The volume of public cloud utilization is growing rapidly, so that inevitably leads to a greater body of sensitive stuff that is potentially at risk,” says Jay Heiser, vice president and lead at Gartner, Inc.
Contrary to what many might think, the main responsibility for protecting corporate data lies not with the service provider but with the customer. “We are in a cloud-security transition period in which focus is shifting from the provider to the customer,” Heiser says. “Enterprises are learning that huge amounts of time spent trying to figure out if any particular service provider is ‘secure’ or not has virtually no payback.”
To provide organizations with an up-to-date understanding of security concerns so they can make educated decisions regarding cloud adoption strategies, the Cloud-Security Alliance (CSA) has created the latest version of its Treacherous 12 Top Threats to Cloud-Computing Plus: Industry Insights report.
The report reflects the current consensus among security experts in the CSA community about the most significant security issues. While there are many security concerns, CSA says, this list focuses on 12 specifically related to the shared, on-demand nature of cloud computing. A follow-up report, Top Threats to Cloud-Computing: Deep Dive, explores case studies for most of the 12 threats.
This article originally appeared on csoonline.com To read the full article, click here.
Nastel Technologies uses machine learning to detect anomalies, behavior and sentiment, accelerate decisions, satisfy customers, innovate continuously. To answer business-centric questions and provide actionable guidance for decision-makers, Nastel’s AutoPilot® for Analytics fuses:
- Advanced predictive anomaly detection, Bayesian Classification and other machine learning algorithms
- Raw information handling and analytics speed
- End-to-end business transaction tracking that spans technologies, tiers, and organizations
- Intuitive, easy-to-use data visualizations and dashboards
If you would like to learn more, click here.