Isolation forest
PulseAugur coverage of Isolation forest — every cluster mentioning Isolation forest across labs, papers, and developer communities, ranked by signal.
5 day(s) with sentiment data
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Syscall-based HIDS generalization to unseen CVEs shows mixed results
Researchers explored the generalization capabilities of system-call based Host Intrusion Detection Systems (HIDS). They investigated whether a HIDS trained on normal behavior for specific Common Vulnerabilities and Expo…
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Syscall-based HIDS generalisation tested across CVEs and CWEs
Researchers have investigated the generalizability of Host Intrusion Detection Systems (HIDS) that utilize syscall traces. The study empirically tested whether anomaly detectors trained on known Common Vulnerabilities a…
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New P$^2$CE algorithm generates plausible counterfactual explanations for AI
Researchers have developed P$^2$CE, a new algorithm designed to generate plausible Pareto-optimal counterfactual explanations for machine learning models. This method aims to provide users with a range of optimal trade-…
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New HDC Framework Enhances Anomaly Detection for Edge AI
Researchers have introduced D2H-AD, a novel anomaly detection framework that leverages Hyperdimensional Computing (HDC). This brain-inspired approach uses high-dimensional vectors to represent information, integrating d…
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New research tackles multivariate time series anomaly detection
Two new research papers explore advanced techniques for anomaly detection in multivariate time series data. The first paper introduces CRAFTIIF, a framework designed to identify four distinct types of anomalies (point, …
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New MADQI metric improves unsupervised maritime anomaly detection
Researchers have introduced a new evaluation metric called the Maritime Anomaly Detection Quality Index (MADQI) for unsupervised learning models used in detecting anomalies in maritime Automatic Identification System (A…
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New SilIF Algorithm Enhances Unsupervised Fraud Detection
Researchers have developed SilIF, a novel enhancement to the Isolation Forest algorithm for unsupervised transaction fraud detection. SilIF incorporates a silhouette-based scoring layer, which analyzes the representatio…
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AI framework detects foot anomalies to aid diabetic ulcer prevention
Researchers have developed a baseline feasibility study for an unsupervised anomaly detection framework using wearable foot sensors to help prevent diabetic foot ulcers. The study applied Isolation Forest and K-Nearest …
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New unsupervised method segments multilingual laughter in audio
Researchers have developed a new unsupervised method for segmenting acoustic laughter across multiple languages. This approach treats laughter detection as an anomaly detection problem on audio sequences, utilizing an I…
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AI framework SLEID enhances illicit account detection in Ethereum DeFi
Researchers have developed SLEID, a novel framework designed to detect illicit accounts within Ethereum's Decentralized Finance (DeFi) ecosystem. This self-learning ensemble-based system utilizes an Isolation Forest mod…
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Unsupervised ML detects heavy metal soil contamination for environmental risk assessment
Researchers have developed an unsupervised machine learning framework to identify heavy metal contamination in soils, focusing on urbanizing regions in Ghana. The study analyzed eight metals and health risk indices acro…