A Machine Learning-Based Method for Automated Blockchain Transaction Signing Including Personalized Anomaly Detection

A Hybrid Machine Learning Method for Intrusion Detection

Data security is an important area of concern for every computer system owner. An intrusion detection system is a device or software application that monitors a network or systems for malicious activity or policy violations. Already various techniques of artificial intelligence have been used for intrusion detection. The main challenge in this area is the running speed of the available implemen...

Machine Learning for Host-based Anomaly Detection

Machine Learning for Host-based Anomaly Detection by Gaurav Tandon Dissertation Advisor: Philip K. Chan, Ph.D. Anomaly detection techniques complement signature based methods for intrusion detection. Machine learning approaches are applied to anomaly detection for automated learning and detection. Traditional host-based anomaly detectors model system call sequences to detect novel attacks. This...

Transaction-based Anomaly Detection

The increasing complexity of both tele and data communication networks yields new demands concerning network security. Especially the task of detecting, repulsing and preventing abuse by inand outsiders is becoming more and more difficult. This paper deals with a new technique that appears to be suitable for solving these issues, i.e. anomaly detection based on the specification of transactions...

Anomaly detection with Machine learning

Behaviour Based Anomaly Detection for Smartphones Using Machine Learning Algorithm

Since the first handheld cellular phone was introduced in 1973, the mobile phones have evolved into immensely popular smartphones. These devices provide all-in-one expediency by integrating traditional mobile phones with handheld computing devices making them more open and general purpose. Smartphones have become hosts for sensitive or personal data and applications. However many smartphones ar...