Bot Management

The Challenge

The use of bots is dramatically increasing and they have learnt how to avoid current detection tools by acting just as humans do when visiting a website.
They carry a large number of threats including, customer account takeover, scraping websites and online fraud. The costs and risks to organisations are notably increasing and in order to combat these rising threats, a fresh approach is needed.

The Solution

At Netacea we introduce a new layer of security dedicated to bot detection and mitigation. Organisations need a solution that is agile, intelligent and one that adapts to the different threat levels facing their online presence.
Our solution is designed to complement existing controls such as WAF rulesets, rate limiting and threat databases, to provide deep analysis of all website visitors.

Adaptive Approach

Under the Hood

The core of our approach is an adaptive model for machine learning, that automatically learns from your web estate according to your business priorities and the actual threats themselves.

Rather than building one data model and applying it to every situation, our machine learning module learns from your environment and then adapts its algorithms so it’s truly tailored for your own unique set of requirements and critical paths. This data model gives huge power and flexibility to ensure that even the most complex of visitor requirements can be elegantly and reliable handled at volume.

Adaptive Behavioural Engine

At the heart of the adaptive machine learning is the behavioural engine, that learns from your environment and guided learning, and adapts its own mitigations according to the threat levels from your own visitors. Using our simple visual guided machine learning tool, you set up the core business logic of the behaviour and critical paths that are important to you before the machine learning algorithm run.

This allows us right from the beginning to start generating the right algorithmic feedback for your estate straightaway, and is completely automatic. As you revise settings, or even add specific actions for individual visitors, the machine learning continues to learn from your settings to provide additional behavioural adaptability.

The adaptive model changes in real-time to provide the best possible defence according to the attack type. Existing customers and known bad actors are elegantly handled, and highly suspicious traffic on known critical paths is subject to further examination and protection if necessary.

How We Work & Deploy

THE NETACEA DIFFERENCE

ENTERPRISE GRADE
ACCOUNT TAKE OVER

ENTERPRISE GRADE
ACCOUNT TAKE OVER

ADAPTIVE THREAT
ARCHITECTURE

ADAPTIVE THREAT
ARCHITECTURE

OPEN API's

OPEN API's

EASE OF INTEGRATION

EASE OF INTEGRATION

TRANSPARENT
THREAT INTELLIGENCE

TRANSPARENT
THREAT INTELLIGENCE

CORE BEHAVIOURAL
ANALYSIS

CORE BEHAVIOURAL
ANALYSIS