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Kei Suzuki

2 papers indexed

arxivcs.LGcs.AIcs.CLcs.CR2026-07-23

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models

Shoya Otsu, Kei Suzuki, Toshiaki Koike-Akino, Jing Liu, Ye Wang

Advanced Persistent Threats (APTs) remain difficult to detect because only a small fraction of events in large-scale logs are attack-related, and investigation is expensive and hard to scale. Prior machine-learning approaches can reduce analyst workload, but they often rely on he…

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crossrefSensors2025-09-04

Machine Learning-Based Alexithymia Assessment Using Resting-State Default Mode Network Functional Connectivity

Kei Suzuki, Midori Sugaya

Alexithymia is regarded as one of the risk factors for several prevalent mental disorders, and there is a growing need for convenient and objective methods to assess alexithymia. Therefore, this study proposes a method for constructing models to assess alexithymia using machine l…

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