The National Science Foundation awarded a $299,389 Project Grant to Mississippi State University under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The grant will fund research to develop new scalable defenses against Sybil attacks in dynamic computer networks. Sybil attacks involve an adversary impersonating multiple identities to disrupt a network. Existing defenses require constant resource burning by legitimate participants regardless of attack activity.
The research aims to design defenses where the amount of required resource burning grows slowly as a function of resources expended by attackers and rate of legitimate participant turnover. A novel framework will estimate adversarial activity levels and charge participants an appropriate resource burning cost. Machine learning may help with estimation. Theoretical work will be complemented by empirical evaluations. Outcomes have potential to secure peer-to-peer networks, e-commerce review systems, and public-access servers against Sybil attacks through more efficient participant maintenance and spam/denial-of-service defenses. Workshops and student research opportunities will foster collaboration between cybersecurity practitioners and academia.
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