… anomalies and can detect zero-day vulnerability. Because our work centers on anomaly
detection … Discrete events anomaly detection is context-based (relies on the construction of …

… anomaly detection model that uses intra-trace and inter-trace … the challenge of online
anomaly detection in cyber-physical … [16] built an anomaly detection framework called Deeplog …

… feature-based anomaly detection framework called PESKEA, … in the execution traces of an
embedded OS to perform trace … traces, and we derive the features of our anomaly framework …

… framework for unsupervised anomaly detection, which are algorithms that are designed to
process unlabeled data. In our framework… spectrum kernel which we apply to system call traces…

… for anomaly detection in which we transform the content of system call traces into traces of
kernel … of normal behavior for Firefox 3.5 by executing seven different testing frameworks (test …

… framework consists of multiple components: trace data extraction, preprocessing and
normalization, feature selection, and anomaly detection… calls using the Linux kernel tracing. Then, …

… In this work, we propose an anomaly detection framework … problems by highlighting
anomalous parts in trace data. Our … kernel events in a trace file and transferring it into the Trace …

… Furthermore, our analysis of the kernel-level event traces of an OS for anomaly detection
presents … conditions, can we build anomaly detection frameworks to detect an aberration in the …

… of states in anomalous traces are within the range of normal traces. For example, 0.15 and
… seven different testing frameworks (test suites) [22]. Each test framework executes different …

… We prove that \(\tilde{M}\) can characterize traces as precise as … trace level while obtaining
the trace incurs the smallest tracing overhead. White-box level traces: all (or a part of) kernel-…