Takeshi Takahashi

CR
h-index21
7papers
122citations
Novelty40%
AI Score48

7 Papers

39.5CRJun 3
NLLog: Lightweight, Explainable SOC Anomaly Detection via Log-to-Language Rewriting

Samuel Ndichu, Tao Ban, Seiichi Ozawa et al.

System-generated logs underpin security monitoring, yet their rigid template-based format hinders both automated analysis and human comprehension. We present NLLog (Natural-Language Log), a lightweight pipeline that deterministically rewrites parsed templates into WHO-WHAT-SEVERITY sentences, pools them with term-frequency-inverse-document-frequency weighting, classifies sessions with tree ensembles, and back-projects evidence with TreeSHAP for analyst review. On Hadoop Distributed File System (HDFS) and Blue Gene/L (BGL) corpora, NLLog exceeds two reproduced matched-protocol baselines; across HDFS, BGL, and the AIT Alert Data Set, it sustains low false-positive rates with commodity-hardware latency suitable for security operations center triage. Coverage, sparse-versus-dense, faithfulness, and adversarial ablations show that fallback sufficiency is corpus-dependent, that an enrollment-time coverage check can surface refinement requirements before deployment, and that an auditable deterministic rewrite combined with lightweight dense encoding provides a measurable representation layer for log-anomaly detection and triage.

8.6CRMay 21
PACT: Reducing Alert Fatigue in Low-Prevalence SOC Streams with Triggered Active Learning

Samuel Ndichu, Tao Ban, Seiichi Ozawa et al.

Security operations centers face persistent alert fatigue: in low-prevalence streams, even low false-positive rates generate substantial investigation load, while aggregate F1 scores obscure analyst burden. We introduce PACT, a Pareto-aware controller for triggered active learning, which wraps an already-deployed frozen XGBoost-Focal screener with an adaptive windowing score-shift trigger and a hybrid acquisition rule combining threshold-relative uncertainty with high-score sampling. On two public low-prevalence benchmarks, AIT-ADS (AIT Alert Data Set), and BOTSv1 (Boss of the SOC version 1), PACT attains the lowest benign-normalized false-positive (FP) burden among the adaptive methods tested. It reduces burden by 43% and 21%, respectively, relative to a frozen baseline, while using 3.8x and 5.2x fewer analyst queries than periodic uniform-random updating. A matched-trigger ablation controls trigger timing and shows that acquisition contributes beyond timing alone, at the cost of approximately ten percentage points of positive-window recall under free-running triggers. A frozen threshold-only baseline pushes FP lower still but collapses BOTSv1 recall by 55 percentage points. Under the evaluated workload assumptions, pure FP minimization trades unacceptable recall for that lower burden.

37.9CRMay 8
AI-Driven Security Alert Screening and Alert Fatigue Mitigation in Security Operations Centers: A Comprehensive Survey

Samuel Ndichu, Akira Yamada, Tao Ban et al.

Security alert screening is the downstream task of filtering, prioritizing, correlating, and contextualizing alerts for analyst attention in Security Operations Centers. This survey reviews artificial-intelligence-driven alert screening and alert-fatigue mitigation from 2015 to 2026. We synthesize 119 records, including 87 core studies, into a four-stage workflow taxonomy covering filtering, triage, correlation, and generative augmentation. We find persistent gaps in deployment realism, adversarial robustness, cross-environment validation, and evaluation practice. The survey concludes with a research agenda toward trustworthy Cognitive Security Operations Centers.

AIOct 14, 2025
Clutch Control: An Attention-based Combinatorial Bandit for Efficient Mutation in JavaScript Engine Fuzzing

Myles Foley, Sergio Maffeis, Muhammad Fakhrur Rozi et al.

JavaScript engines are widely used in web browsers, PDF readers, and server-side applications. The rise in concern over their security has led to the development of several targeted fuzzing techniques. However, existing approaches use random selection to determine where to perform mutations in JavaScript code. We postulate that the problem of selecting better mutation targets is suitable for combinatorial bandits with a volatile number of arms. Thus, we propose CLUTCH, a novel deep combinatorial bandit that can observe variable length JavaScript test case representations, using an attention mechanism from deep learning. Furthermore, using Concrete Dropout, CLUTCH can dynamically adapt its exploration. We show that CLUTCH increases efficiency in JavaScript fuzzing compared to three state-of-the-art solutions by increasing the number of valid test cases and coverage-per-testcase by, respectively, 20.3% and 8.9% on average. In volatile and combinatorial settings we show that CLUTCH outperforms state-of-the-art bandits, achieving at least 78.1% and 4.1% less regret in volatile and combinatorial settings, respectively.

CRApr 1, 2014
Ontological Approach toward Cybersecurity in Cloud Computing

Takeshi Takahashi, Youki Kadobayashi, Hiroyuki Fujiwara

Widespread deployment of the Internet enabled building of an emerging IT delivery model, i.e., cloud computing. Albeit cloud computing-based services have rapidly developed, their security aspects are still at the initial stage of development. In order to preserve cybersecurity in cloud computing, cybersecurity information that will be exchanged within it needs to be identified and discussed. For this purpose, we propose an ontological approach to cybersecurity in cloud computing. We build an ontology for cybersecurity operational information based on actual cybersecurity operations mainly focused on non-cloud computing. In order to discuss necessary cybersecurity information in cloud computing, we apply the ontology to cloud computing. Through the discussion, we identify essential changes in cloud computing such as data-asset decoupling and clarify the cybersecurity information required by the changes such as data provenance and resource dependency information.

NIMar 27, 2014
Building Secure and Anonymous Communication Channel: Formal Model and its Prototype Implementation

Keita Emura, Akira Kanaoka, Satoshi Ohta et al.

Various techniques need to be combined to realize anonymously authenticated communication. Cryptographic tools enable anonymous user authentication while anonymous communication protocols hide users' IP addresses from service providers. One simple approach for realizing anonymously authenticated communication is their simple combination, but this gives rise to another issue; how to build a secure channel. The current public key infrastructure cannot be used since the user's public key identifies the user. To cope with this issue, we propose a protocol that uses identity-based encryption for packet encryption without sacrificing anonymity, and group signature for anonymous user authentication. Communications in the protocol take place through proxy entities that conceal users' IP addresses from service providers. The underlying group signature is customized to meet our objective and improve its efficiency. We also introduce a proof-of-concept implementation to demonstrate the protocol's feasibility. We compare its performance to SSL communication and demonstrate its practicality, and conclude that the protocol realizes secure, anonymous, and authenticated communication between users and service providers with practical performance.

CRMar 26, 2014
Tailored Security: Building Nonrepudiable Security Service-Level Agreements

Takeshi Takahashi, Jarmo Harju, Joona Kannisto et al.

The security features of current digital services are mostly defined and dictated by the service provider (SP). A user can always decline to use a service whose terms do not fulfill the expected criteria, but in many cases, even a simple negotiation might result in a more satisfying outcome. This article aims at building nonrepudiable security service-level agreements (SSLAs) between a user and an SP. The proposed mechanism provides a means to describe security requirements and capabilities in different dimensions, from overall targets and risks to technical specifications, and it also helps in translating between the dimensions. A negotiation protocol and a decision algorithm are then used to let the parties agree on the security features used in the service. This article demonstrates the feasibility and usability of the mechanism by describing its usage scenario and proof-of-concept implementation and analyzes its nonrepudiability and security aspects.