Adaptive Honeypot Deployment in Virtual Networks
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Solution Overview
Problem
Deploying honeypots that are not easily detectable by malicious users is a challenging and time-consuming task, especially for users lacking sophistication or resources, as attackers can quickly identify non-customized honeypots and recognize patterns that give away their presence.
Innovation Solution
A system for adaptively configuring and deploying honeypots in virtual networks that analyzes the user's network configuration, selects preconfigured honeypot templates matching the existing devices, and configures them to resemble the user's network, including similar operating systems, applications, and network configurations, to avoid detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If honeypots are deployed with generic or non-customized configurations, then deployment time and resources are reduced, but attackers can quickly identify and recognize patterns that give away their presence
Solution Approach 1:
The system dynamically changes honeypot configuration parameters such as operating system type, application versions, and network settings to match the victim's environment. This allows the same honeypot template to adapt its parameters based on the target, making each deployment unique and undetectable while using pre-configured base templates for efficiency
Solution Approach 2:
The system performs preliminary analysis of the victim's network environment before deploying honeypots. By gathering intelligence about the target's OS, applications, and configuration patterns in advance, the system can pre-configure honeypots with matching characteristics, reducing deployment time while ensuring undetectability
2Difficulty of detecting and measuring
If honeypots are customized to match the user's network configuration, then detectability by attackers is reduced, but the complexity and resources required for deployment increase
Solution Approach 1:
The system creates copies of the victim's network configuration characteristics and applies them to honeypot deployments. By copying OS types, application versions, and network settings from the target environment, the system achieves realistic customization without manually configuring each honeypot from scratch, thus reducing complexity
Solution Approach 2:
The system develops universal honeypot templates that can function across multiple target environments. These templates are designed to be multi-functional, supporting various OS and application configurations through parameter adjustment, allowing a single template to serve multiple customization needs without increasing deployment complexity
3Reliability
If honeypots are customized to match the user's network configuration, then the effectiveness in drawing attacker attention is improved, but the resources and expertise required for configuration increase
Solution Approach 1:
The system performs self-service by automatically analyzing the victim's network environment and configuring honeypots without requiring manual intervention. The automated configuration process gathers target intelligence, selects appropriate templates, and adjusts parameters independently, eliminating the need for expert operators while maintaining high effectiveness
Solution Approach 2:
The system uses feedback from the victim's network environment to automatically adjust honeypot configurations. By continuously monitoring target characteristics and feeding this information back into the configuration process, the system adapts honeypot settings to match the target, achieving high effectiveness through automated feedback loops rather than manual tuning
Data Source
AI summary
Systems and methods are provided for adaptively configuring and deploying honeypots in user compute resources. The methods select, based at least in part on a profile associated with a user account, a virtual machine image having a type and associated with a countermeasure. Cause a virtual machine to be launched in connection with a virtual network associated with the user account.