Application Sensor-Based Attack Detection and Response
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Solution Overview
Problem
Organizations face challenges in accurately detecting and defending against attacks on vulnerable software applications, which are increasingly complex and interconnected, leading to significant business risks.
Innovation Solution
A computerized method is introduced that modifies application instructions to include sensors to detect attacks, analyzes generated events for attack presence, and invokes response actions, such as logging or redirecting users, to block and mitigate threats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If application software is modified to include sensors for attack detection, then detection accuracy improves, but device complexity increases
Solution Approach 1:
The attack detection system is segmented into independent sensor components that can be individually installed, configured, and managed within the application. Each sensor operates as a separate module that monitors specific aspects of application behavior, allowing granular control over detection capabilities without requiring complete system redesign.
Solution Approach 2:
Sensors act as intermediary components between the application code and the attack detection logic. These sensors intercept and monitor application events without directly modifying core application functionality, providing a buffer layer that enables detection while maintaining application integrity and reducing integration complexity.
2Adaptability or versatility
If multiple sensors are added to detect various attack types, then detection capability improves, but processing time increases
Solution Approach 1:
The system implements partial monitoring by activating only the sensors and detection rules relevant to the current application context and threat landscape. Not all sensors are continuously active; instead, the system selectively enables detection capabilities based on application type, risk assessment, and current threat intelligence, reducing processing overhead while maintaining comprehensive coverage when needed.
Solution Approach 2:
Attack detection operates through periodic event sampling rather than continuous monitoring of all application states. Sensors trigger on specific events and transitions rather than constantly analyzing all data streams, allowing the system to maintain high detection capability while processing events at manageable intervals and reducing overall processing time.
Data Source
AI summary
In one example aspect, a computerized method of automatically detecting and blocking at least one attack on an application includes the step of modifying instructions of the application to include at least one sensor. The at least one sensor generates a set of events related to detecting an attack on the application or a computing system implementing the application. The method includes the step of reviewing, from within the application, the set of events generated by the at least one sensor. The method includes the step of detecting a presence of at least one attack on the application based on the review of the set of events. The method includes the step of invoking an attack response action.