Self-Service Machine Attack Recognition via Dynamic Field Control
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Solution Overview
Problem
Conventional methods for protecting self-service machines, such as automated teller machines, from attacks by generating a protective electromagnetic field are difficult to align and adjust precisely, often interfering with the actual card reader's functionality and being overly sensitive, thus limiting the machine's usability.
Innovation Solution
A system that models attack patterns using a set of rules, integrates image recognition, and artificial intelligence to classify threats, with a fact adapter linking device drivers and employing encryption for security, monitors various system components, and triggers alarms for suspicious activities, including potential manipulation of the control panel, card readers, and cash dispensing mechanisms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a protective electromagnetic field is generated to block skimming devices, then the read function of the spying device is interfered with, but the actual card reader's functionality is also interfered with by mistake
Solution Approach 1:
The patent applies local quality by creating a protective electromagnetic field with specific spatial characteristics - the field is generated only in the precise location where skimming devices are installed (in front of the card slot), while maintaining normal operation of the actual card reader. This localized approach ensures protection is applied only where needed without interfering with legitimate card reading functions.
Solution Approach 2:
The system dynamically adjusts the protective field parameters based on detected attack patterns. The evaluation unit continuously monitors for skimming attempts and modifies the protective field strength and positioning in real-time, allowing the system to adapt between protective mode (when attacks are detected) and normal operation mode (when no attacks are present), thus resolving the contradiction between protection and ease of operation.
2Reliability
If a protective electromagnetic field is generated to block skimming devices, then data can no longer be read by skimming, but the system reacts too sensitively and limits functionality
Solution Approach 1:
The system incorporates a feedback mechanism where the evaluation unit continuously monitors system states and attack patterns. When legitimate operations are detected, the system receives feedback to maintain normal functionality. When skimming attempts are detected, the feedback triggers activation of the protective field. This closed-loop feedback system prevents over-sensitive reactions and ensures the protective measures are only activated when actually needed, maintaining productivity during normal operations.
Solution Approach 2:
The protective field parameters are dynamically adjusted based on real-time detection of attack patterns versus normal operations. The system transitions between different operational states (protective mode vs. normal mode) based on feedback from the evaluation unit, ensuring that functionality is limited only when necessary and maintained during legitimate use.
3Reliability
If the protective field is positioned precisely in front of the card slot, then skimming is blocked, but alignment and field strength adjustment become complex
Solution Approach 1:
The system performs self-service by automatically detecting the position and strength parameters needed for optimal protective field generation. The evaluation unit monitors system states and attack patterns to self-adjust the field parameters without requiring manual alignment or adjustment by operators. This automated self-service approach simplifies the previously complex alignment and adjustment processes while maintaining protection effectiveness.
Solution Approach 2:
The system automatically changes protective field parameters (position, strength, configuration) based on detected attack patterns and system state. Rather than requiring manual adjustment of these parameters, the system uses the evaluation unit to detect optimal parameter values and self-adjusts the protective field accordingly, reducing device complexity while maintaining effectiveness.
Data Source
AI summary
The invention relates to a method for recognizing attacks on at least one interface of a computer system, particularly a self-service machine, comprising: monitoring the interface in order to detect changes to the interface; if changes occur, the probability of an impermissible attack on the interface is determined based on the nature of the change; if the probability is above a defined threshold value, defensive measures are taken.