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Version: 7.4

Denial-of-Service

Denial-of-Service (DoS) attacks, where attackers aim to make a network service unavailable to its intended users by overwhelming it with a flood of internet traffic, are a significant threat in the digital landscape. These attacks can cripple network infrastructure, disrupt service operations, and cause substantial downtime, leading to financial losses and damage to an organization's reputation. Identifying these attacks promptly is crucial as it allows for swift defensive actions to mitigate the attack's impact and maintain service continuity. Early detection is key in preserving the integrity and availability of network services.

ElastiFlow provides a collection of anomaly detection jobs designed to identify DoS attacks is an essential tool in this early detection and response strategy. These jobs are tailored to monitor various network parameters and traffic patterns, using sophisticated algorithms to detect anomalies that signify a potential DoS attack.

Downloads​

SchemaLink
CODEXAll Denial-of-Service ML Jobs for CODEX Schema
ECSAll Denial-of-Service ML Jobs for ECS Schema

By implementing this collection of anomaly detection jobs, organizations can rapidly recognize the onset of a DoS attack, allowing network administrators to take immediate action. This can include measures such as traffic filtering, rate limiting, or engaging with upstream providers for assistance. Early detection and response are critical in minimizing the impact of DoS attacks, ensuring network services remain available and reliable for users. This proactive approach is a key aspect of modern network security strategies, guarding against one of the most disruptive forms of cyber threats.