arXiv subjects

Kyle Fredrickson

Publications and source records attributed to Kyle Fredrickson.

2 recordsLinked to original sources

arXiv2026

Effective Interventions Against AI-Enhanced Scams

In 2025, scams were responsible for an estimated $442 billion in direct losses globally. In the United States, reported losses increased by nearly 400% between 2020 and 2025. Though AI in scamming is a relatively new phenomenon, its use significantly changes the economics of scams as well as the bottlenecks in scam operations. In this paper I investigate what interventions will remain effective under this new AI-driven scamming regime. I develop a simple model of scam profits to understand how different interventions asymptotically affect scam operations. I find that three levers--reporting rate, centralization of reporting, and report accuracy--multiply in their effect on expected victims per scam channel, reducing revenue per scam channel while increasing costs. Because effects multiply, interventions affecting all three could have a significant effect on the profitability of the scam business model. My analysis suggests that even modest reporting rates against high-value scam infrastructure could have significant impacts on scam profitability.

cs.CR↗

arXiv2021

A Multiple Snapshot Attack on Deniable Storage Systems

While disk encryption is suitable for use in most situations where confidentiality of disks is required, stronger guarantees are required in situations where adversaries may employ coercive tactics to gain access to cryptographic keys. Deniable volumes are one such solution in which the security goal is to prevent an adversary from discovering that there is an encrypted volume. Multiple snapshot attacks, where an adversary is able to gain access to two or more images of a disk, have often been proposed in the deniable storage system literature; however, there have been no concrete attacks proposed or carried out. We present the first multiple snapshot attack, and we find that it is applicable to most, if not all, implemented deniable storage systems. Our attack leverages the pattern of consecutive block changes an adversary would have access to with two snapshots, and demonstrate that with high probability it detects moderately sized and large hidden volumes, while maintaining a low false positive rate.

cs.CR↗