Anomaly Detection and Preprocessing
نویسنده
چکیده
منابع مشابه
Data preprocessing for anomaly based network intrusion detection: A review
Data preprocessing is widely recognized as an important stage in anomaly detection. This paper reviews the data preprocessing techniques used by anomaly-based network intrusion detection systems (NIDS), concentrating on which aspects of the network traffic are analyzed, and what feature construction and selection methods have been used. Motivation for the paper comes from the large impact data ...
متن کاملSecuring Cluster-heads in Wireless Sensor Networks by a Hybrid Intrusion Detection System Based on Data Mining
Cluster-based Wireless Sensor Network (CWSN) is a kind of WSNs that because of avoiding long distance communications, preserve the energy of nodes and so is attractive for related applications. The criticality of most applications of WSNs and also their unattended nature, makes sensor nodes often susceptible to many types of attacks. Based on this fact, it is clear that cluster heads (CHs) are ...
متن کاملFinding the Vocabulary of Program Behavior Data for Anomaly Detection
Application-based anomaly detectors construct a baseline model of normal application behavior, and deviations from that behavior are interpreted as signs of a possible intrusion. But current anomaly detectors monitor application behavior at a high level of detail, and many irrelevant variations in that behavior can cause false alarms. This paper discusses the preprocessing of audit data ultimat...
متن کاملRobust Keystroke Biometric Anomaly Detection
The Keystroke Biometrics Ongoing Competition (KBOC) presented an anomaly detection challenge with a public keystroke dataset containing a large number of subjects and real-world aspects. Over 300 subjects typed case-insensitive repetitions of their first and last name, and as a result, keystroke sequences could vary in length and order depending on the usage of modifier keys. To deal with this,...
متن کاملA Hierarchical Anomaly Network Intrusion Detection System using Neural Network Classification
In this paper, we introduce a hierarchical anomaly network intrusion detection system, which is capable of detecting network–based attacks using statistical preprocessing models and neural network classification. The sample network used has a three-tier hierarchy, where the lower tier detectors report to the higher tiers. The statistical preprocessor converts network traffic sample information ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2015