[Paper Review] TRIDEnT: Building Decentralized Incentives for Collaborative Security

Νικόλαος Αλεξόπουλος, Emmanouil Vasilomanolakis+3 more|arXiv (Cornell University)|May 9, 2019

Network Security and Intrusion Detection42 references4 citations

TL;DR

TRIDEnT proposes a decentralized marketplace for peer-to-peer sharing of network security alerts using Ethereum smart contracts, enabling trustless, incentivized collaboration among potentially competitive organizations. It demonstrates through a game-theoretic model that collaboration occurs infinitely often and implements a fully functional prototype, validating its feasibility and incentive structure.

ABSTRACT

Sophisticated mass attacks, especially when exploiting zero-day vulnerabilities, have the potential to cause destructive damage to organizations and critical infrastructure. To timely detect and contain such attacks, collaboration among the defenders is critical. By correlating real-time detection information (alerts) from multiple sources (collaborative intrusion detection), defenders can detect attacks and take the appropriate defensive measures in time. However, although the technical tools to facilitate collaboration exist, real-world adoption of such collaborative security mechanisms is still underwhelming. This is largely due to a lack of trust and participation incentives for companies and organizations. This paper proposes TRIDEnT, a novel collaborative platform that aims to enable and incentivize parties to exchange network alert data, thus increasing their overall detection capabilities. TRIDEnT allows parties that may be in a competitive relationship, to selectively advertise, sell and acquire security alerts in the form of (near) real-time peer-to-peer streams. To validate the basic principles behind TRIDEnT, we present an intuitive game-theoretic model of alert sharing, that is of independent interest, and show that collaboration is bound to take place infinitely often. Furthermore, to demonstrate the feasibility of our approach, we instantiate our design in a decentralized manner using Ethereum smart contracts and provide a fully functional prototype.

Motivation & Objective

• To address the lack of incentives and trust that hinder real-world adoption of collaborative intrusion detection systems (CIDS).
• To design a decentralized platform allowing organizations to selectively advertise, buy, and sell security alerts in real time.
• To model and validate the economic incentives for long-term collaboration using game theory, showing that cooperation is sustainable.
• To implement a fully functional prototype using Ethereum smart contracts to demonstrate feasibility.
• To position TRIDEnT as an underlying incentives layer for existing threat intelligence platforms like MISP.

Proposed method

• Designing a peer-to-peer streaming marketplace for security alerts using Ethereum smart contracts to enforce trustless transactions.
• Implementing a game-theoretic model of alert sharing to analyze strategic incentives and show that collaboration occurs infinitely often under rational behavior.
• Using a reputation system and stream reselling mitigation to ensure alert quality and prevent abuse.
• Integrating with existing platforms like MISP as an overlay for real-world deployment.
• Employing data sanitization techniques to protect sensitive information such as IP addresses.
• Designing a modular architecture that supports various alert types, including Snort rules, bloom filters, and machine learning models.

Experimental results

Research questions

• RQ1 Can a decentralized, trustless marketplace for security alerts sustain long-term collaboration among competing organizations?
• RQ2 How can economic incentives be designed to prevent free-riding and ensure active participation in alert sharing?
• RQ3 What game-theoretic conditions ensure that rational participants will engage in repeated collaboration rather than defect?
• RQ4 How can alert quality and trust be maintained in a decentralized system without a central authority?
• RQ5 Can a smart contract-based system effectively manage real-time, peer-to-peer exchange of security alerts at scale?

Key findings

• The game-theoretic model proves that collaboration in alert sharing is bound to occur infinitely often under rational, self-interested behavior, validating the long-term sustainability of the incentive mechanism.
• The prototype implementation using Ethereum smart contracts demonstrates the technical feasibility of TRIDEnT’s design for real-time, decentralized alert exchange.
• TRIDEnT enables selective, peer-to-peer sharing of alerts without requiring a central authority, reducing trust and privacy concerns.
• The system supports various alert formats, including Snort-style rules, bloom filters, and machine learning models, enhancing detection capabilities.
• The platform can be integrated as an incentives layer atop existing threat intelligence platforms like MISP, enhancing their adoption without replacing core functionality.
• The model identifies potential risks such as stream reselling, which may require additional mitigation strategies in production environments.