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In this paper, we exploit the Autoencoder neural network model to detect variants of a very famous attack discovered in 2014, namely Heartbleed. The attack was ...
In this paper, we exploit the Autoencoder neural network model to detect variants of a very famous attack discovered in 2014, namely Heartbleed.
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How can AI detect anomalies using AI?
How can AI-based anomaly detection techniques be used in software engineering to increase system security?
Jan 26, 2024 · In this review, we provide a systematic review for AI-based anomaly detection techniques over encrypted traffic.
Dec 2, 2021 · tl;dr. An approach to detecting suspicious TLS certificates using an incremental anomaly detection model is discussed.
In this review, we provide a systematic review for AI-based anomaly detection techniques over encrypted traffic.
Aug 3, 2023 · This research was conducted to detect malware in encrypted network traffic without decryption. The existing solution involves bulk decryption, analysis, and re ...
We reviewed the selected research in terms of dataset, feature extraction, feature selection, preprocessing, anomaly detection algorithm, and ...
By analyzing telemetry data using machine learning techniques (artificial intelligence), Kaspersky MLAD detects signs of an abnormal situation before it is ...
Anomaly detection in AI is a technique used to identify unusual patterns or outliers in a dataset that deviate from a normal baseline.
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Built machine learning models can be also helpful in detecting zero- day attacks, because malicious traffic samples are not required for the learning phase. It ...