Summary Insights: Building A Cyber Report Card for the Board
RFG Perspective: With the constant barrage of ransomware attacks highlighting code vulnerabilities throughout DevOps and production pipelines, enterprises and governments are being pressed to prove they have adequately protected their organizations from internal and external threats.
Summary Insights: Building A Cyber Report Card for the Board
Summary Insights: Preventing Cloud Data Exposures
RFG Perspective: There are three types of cloud data exposures that enterprises need to guard against: rogue or ungoverned shadow IT clouds; gaps created by hybrid multi-cloud inconsistencies; and the inability to stop unauthorized users or data from being copied, modified or stored. Data loss prevention (DLP) is, therefore, an important area for improving data-protection policies and guidelines throughout the organization.
Summary Insights: Preventing Cloud Data Exposures
Summary Insights: Data Loss Prevention (DLP) Best Practices
RFG Perspective: Data loss can undermine customer trust, damage an enterprise’s reputation – and ultimately cause a loss of revenue. Even though email remains the top attack vector for security events, followed by Web applications
Summary Insights: Data Loss Prevention Best Practices
Summary Insights: APIs as Potential Gateways for Security Attacks
RFG Perspective: Recent malware attacks have exposed APIs (application programming interfaces) as an important area for security improvement. That is because APIs have become the currency of the digital economy – and, as such, require care and concern regarding their compliance with security policies and risk mitigation.
Summary Insights: APIs as Potential Gateways for Security Attacks
Summary Insights: Considerations for Applying Data Governance to AI
RFG Perspective: Data governance is of paramount importance when it comes to achieving productive analytics – and accurate business outcomes. Applying AI and ML technologies to the task of analyzing terabytes – and even petabytes – of data speeds up the analysis, which results in actionable insights.
Summary Insights: Considerations for Applying Data Governance to AI
Summary Insights: Enhancing Data Quality with AI/ML
Summary Insights: Enhancing Data Quality with AI/ML
RFG Perspective: The sad fact is that the quality of digital data is poor and the vast majority of executives are willing to live with it. Historically, this has been acceptable; however, companies are starting to re-purpose the data for AI/ML analyses.
Summary Insights: Enhancing Data Quality with AI/ML
Summary Insights: Delivering End-to-End Disaster Recovery
RFG Perspective: In the hybrid cloud world, end-to-end Disaster Recovery (DR) will have to be re-invented to cope with the accumulated technology changes. It’s no longer a matter of setting Recovery Time Objective (RTO) and Recovery Point Objective (RPO) policies in a closed network of large enterprise data centers – and sticking to them. What constitutes a disaster has changed – and the ability to recover from these damaging forces needs to be part of the DR plan.
Summary Insights: Delivering End-to-End Disaster Recovery
AI Technology to Implement Secure End-To-End Elections
Wintergreen Research: AI provides the technology to implement secure end-to-end elections. Modern secure systems depend on new technology, new ways of conducting elections, new approaches to getting voters registered, new ways of casting votes, and new ways of getting votes counted. AI has the ability to implement secure systems that go end-to-end to protect the will of the voters and mitigate fraud by making it detectable.
AI Voting Systems - Wintergreen Research
Summary Insights: Continuous Monitoring with NIST & Zero Trust
RFG Perspective: Hackers will always find a way to penetrate one or more flaws in an organization’s security barriers; therefore, it is imperative organizations have in place containment, mitigation, and remediation strategies.
Summary Insights: Continuous Monitoring with NIST & Zero Trust
Summary Insights: Governance Architecture in Agile Context
RFG Perspective: An Agile governance architecture should ensure the alignment of projects within the scope of an organization’s overall governance goals. Moreover, this governance architecture must also support the enterprise’s entire enterprise architecture.
Summary Insights: Governance Architecture in Agile Context