In fact, one survey showed application DDoS attacks as the most common malicious bot attack on enterprises. Layer 7 DDoS attacks are also increasingly difficult to detect because bots appear to be making legitimate connections. With content scraping, bots continuously crawl to capture data such as pricing and description, which they then use for fraudulent activities like undercutting prices and creating mirror content to divert user traffic. Website scanning aims to identify app vulnerabilities and exploit them. Other kinds of attacks where malicious actors try to mimic an actual user and evade traditional defenses include website scanning attacks and content scraping. Not surprisingly, the volume of these attacks rises as organizations move to support remote work. With an attack like an account takeover, the attacker comes in as a legitimate user, either by using compromised credentials or by trying common passwords, all while they aren’t detected by regular DDoS mitigation techniques or signature-based detection. ML analytics support fraud-detection capabilities that aren’t possible with other static analysis/signatures, including detecting zero-day attacks. We’ve enhanced application security (Appsec) further by leveraging machine learning models to distinguish human interactions from bot activities and predict traffic behavior. NetScaler Application Delivery ManagementĬitrix application and API security solutions.NetScaler App Delivery and Security Service.

Anormaly detection ddos