S3CDM: A secret-sharing-scheme-based cyberattack detection model and its simulation implementation
Chi Sing Chum, Jia Lu, Claire Tang, Xiaowen Zhang

TL;DR
This paper introduces S3CDM, a cyberattack detection model based on secret sharing schemes, enhancing security and insider attack detection in large organizational networks through practical implementation on Google Cloud Platform.
Contribution
The paper presents a novel secret-sharing-scheme-based detection model with a flexible multi-factor authentication and demonstrates its feasibility via cloud-based implementation.
Findings
The model effectively detects unauthorized activities and insider attacks.
Implementation on Google Cloud Platform shows practical deployment feasibility.
Probability analysis indicates increased resistance against cyberattacks.
Abstract
We design and develop a secret-sharing-scheme-based cyberattack detection model(S3CDM)that can detect unauthorized or illegal activities (especially insider attacks) and protect sensitive information within complex network infrastructures of large organizations. The model splits a secret among a group of legitimate participants or components for authentication, integration and detection of unauthorized activities. Traditional Shamir's polynomial interpolation based and our own hash function based schemes are utilized in the model, they both are practical and efficient to make sure the communications between different components are secure and any unauthorized activities can be detected. The model offers a flexible multi-factor authentication method to enhance the overall system security. Probability analysis [3] shows that multiple component model is more resistant against cyberattacks…
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