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Identify new and emerging security risks, and adapt data handling practices

AffectLog's Application Scanner can be used to identify vulnerabilities and potential security risks using machine learning algorithms. This can help identify and address any issues that may compromise the integrity of the data more efficiently and accurately.

Affectlog's Intruder tool uses machine learning algorithms to optimize penetration testing, providing more accurate and efficient results. Repeater tool can use machine learning algorithms to improve manual testing of applications and identify any potential issues that may compromise the integrity of sensitive data. AffectLog's extender feature allows for the integration of various machine learning plugins, such as the deep learning plugin, which can be used to identify and prevent malicious activities based on previous learning.

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Classification model for detecting anomalies in network traffic and application logs

AffectLog leverages research helping develop models that use reinforcement learning techniques to learn from past actions and adapt to new security threats. This type of research has the potential to improve the ability of machine learning systems to detect and respond to new types of cyber attacks. AffectLog platform is powered by Machine learning models is trained to detect known attacks by analyzing web traffic logs and identifying patterns that indicate an attack is taking place.

AffectLog's Machine Learning research in application security is an active field, and new techniques and models are being developed all the time. These developments have the potential to improve the ability of machine learning systems to detect and respond to cyber attacks, thus securing the application development pipeline and different software verticals.

Network
Monitoring

Risk
Scoring

ML-powered
Analysis

Dynamic
Patterns

AffectLog's Machine learning algorithms are being used to perform automated threat hunting, which help identify and respond to advanced persistent threats and other sophisticated attacks. This helps us improve the security posture by identifying and addressing threats that may have been missed by traditional security methods.
Research Director (Finnish ML Research Lab)