Digital Guardian and Kaspersky Anti-Targeted Attack Platform are two powerful security solutions. Kaspersky seems to have the upper hand due to its advanced threat detection capabilities, deemed worth the higher cost.
Features: Digital Guardian offers robust data loss prevention, endpoint detection and response, and data-centric security. Kaspersky Anti-Targeted Attack Platform provides advanced threat detection, machine learning algorithms, and comprehensive threat intelligence.
Room for Improvement: Users suggest Digital Guardian could benefit from a more intuitive management console, better integration options, and usability improvements. Kaspersky needs better deployment flexibility, reducing false positives, and enhanced operational efficiency.
Ease of Deployment and Customer Service: Digital Guardian has a straightforward deployment process with solid customer support. Kaspersky’s deployment is more complex but manageable with comprehensive support resources.
Pricing and ROI: Digital Guardian is cost-effective, providing good value for protecting sensitive data. Kaspersky is more costly but worth the investment due to its superior threat detection and intelligence capabilities.
Digital Guardian is proud to be part of Fortra’s comprehensive cybersecurity portfolio, and one of the Data Protection family of products. Fortra simplifies today’s complex cybersecurity landscape by bringing complementary products together to solve problems in innovative ways. These integrated, scalable solutions address the fast-changing challenges you face in safeguarding your organization. With the help of the powerful protection from Digital Guardian and others, Fortra is your relentless ally, here for you every step of the way throughout your cybersecurity journey.
Today’s cybercriminals constantly design unique and innovative methods of penetration and compromise. To avoid perimeter prevention technologies they use social engineering, non-malware and supply chain attacks to operate under the radar of security designed to catch ‘bad’ traces. It’s not enough to just ‘know’ what’s bad or dangerous – enterprises need to understand what’s normal, and use AI-driven techniques that simplify and automate this process. Targeted Attack Analyzer is a machine learning engine that involves self-learning to establish the baseline of normal, legitimate activities of an entire network. Through continuous network telemetry collection it finds deviations, detects suspicious activities and predicts further malicious actions at the initial stages of multilayered attacks.
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