Radware Cloud Native Protector vs. Darktrace / NETWORK

Leveraging public cloud services can expose workloads to specific threats that are inherent to cloud-native environments, differing from those found in traditional on-premise systems. To proficiently detect and counteract malicious actions within cloud infrastructures, Radware provides a comprehensive array of Cloud Threat Detection and Response (CTDR) tools. This suite allows organizations to identify and analyze suspicious behaviors in their cloud settings, while also linking these events into unified attack narratives that illustrate the progression of threats over time. By offering this level of insight, Radware enables organizations to take proactive measures, thereby reducing the risk of incidents turning into major data breaches. The platform incorporates tailored Malicious Behavior Indicators (MBIs), which are crafted to tackle the specific vulnerabilities that exist in cloud environments. Furthermore, Radware’s solutions go beyond simple detection; they systematically integrate isolated events over time and across multiple threat surfaces and resources, creating a thorough perspective on potential attacks. This all-encompassing strategy not only aids in identifying patterns but also significantly boosts an organization's ability to respond swiftly to new and emerging threats. Ultimately, this proactive stance fosters a more secure cloud environment for all users.

Darktrace / NETWORK is a cutting-edge AI-powered platform specifically engineered for network detection and response, with the goal of preventing, identifying, examining, and managing both established and emerging threats in today's digital landscapes. By leveraging its Self-Learning AI, the platform engages directly with an organization’s data, adjusting to the normal behaviors of individual devices, users, connections, and attack methods, thus enabling the detection of anomalies without the dependence on prior attack data, established signatures, or broad models. This solution provides extensive visibility across a range of environments, including on-premises, virtual, cloud, hybrid networks, remote endpoints, operational technology (OT) devices, and zero-trust network access (ZTNA), while also monitoring traffic in both encrypted and decrypted states. In addition, it continuously enhances its detection abilities to improve accuracy and reduce alert fatigue, all without the necessity for manual rule adjustments. The Cyber AI Analyst performs in-depth investigations at scale, generating hypotheses, drawing conclusions, prioritizing incidents based on their potential impact on the business, and correlating events across network, endpoint, cloud, identity, OT, email, and remote systems, which fortifies the defense against cyber threats. Consequently, organizations can achieve a proactive security stance that adapts alongside evolving challenges and threats in the digital world. This adaptive approach ensures that security measures remain effective and relevant in the face of ever-changing threat landscapes.