Adaptive Cyber Deception Through Decoy File Placement
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Solution Overview
Problem
Existing cyber-deception strategies fail to effectively deter Advanced Persistent Threats (APTs) while minimizing disruption to legitimate network users and resources, as they do not account for evolving network conditions and adversary tactics.
Innovation Solution
A system and method that utilizes surveillance services, user-defined parameters, and machine learning algorithms to generate decoy file content and placement strategies, applying game theoretic optimization to maximize attacker costs and minimize network impact, with continuous deception operations to adapt to changing threats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If deception objects are deployed strategically within the network to maximize the probability that an APT will steal deception objects rather than legitimate files, then the effectiveness of cyber deception increases, but the complexity of deployment and strategy generation increases
Solution Approach 1:
The system dynamically changes parameters such as decoy file locations, content, and placement strategies based on evolving network conditions and adversary tactics. Surveillance services continuously monitor the network state, and the system adjusts deception parameters in real-time to maintain effectiveness without requiring manual reconfiguration of the entire deception infrastructure.
Solution Approach 2:
The deception strategy is made dynamic rather than static. The system continuously adapts its deception objects and placement strategies in response to changing network conditions and observed adversary behavior. This dynamic approach allows the system to maintain high effectiveness while the automation handles the complexity of continuous adaptation.
2Reliability
If deterrence schemes are implemented to effectively deter cyber-attacks, then security improvement is achieved, but disruption or frustration to legitimate uses of the computing network may increase
Solution Approach 1:
The system applies deception selectively to specific network locations and files rather than implementing blanket security measures across the entire network. By placing decoy objects strategically in specific directories and files based on surveillance data and risk assessment, the system provides targeted security improvement while minimizing impact on legitimate user operations in other parts of the network.
3Adaptability or versatility
If deception strategies are updated continuously to adapt to changing threats, then the ability to frustrate APTs increases, but the computational resources and time required for strategy generation increase
Solution Approach 1:
The system performs preliminary actions by pre-generating multiple candidate deception strategies and evaluating them using game theoretic models before deployment. Surveillance services continuously monitor the network and pre-compute response strategies, so when an adversary action is detected, the system can quickly select and deploy an appropriate pre-evaluated strategy rather than generating strategies from scratch in real-time.
Solution Approach 2:
The system implements continuous feedback loops where surveillance services monitor both legitimate network operations and adversary activities, feeding this information back to the deception strategy generator. This feedback mechanism allows the system to adapt to changing threats efficiently by learning from observed patterns, reducing the computational burden of generating strategies for every possible scenario.
Data Source
AI summary
Described herein are systems and methods for generating a cyber-deception strategy that adaptively implement a decoy file placement strategy for thwarting malicious activity on a computing network. The systems and methods can include a plurality of surveillance services that can monitor the evolving conditions and states of a target computing network. The information from the external surveillance services can be combined with one or more user defined parameters to serve as inputs to a system that can use the input data to generate a decoy file content and placement strategy so as to effect a cyber-deception strategy. In one or more examples, can identify one or more target objects to use as decoys and use the identified targeted objects as well as information about the target network, to generate a high-level guidelines that will be used to generate one or more deception plans for implementation on the target network.