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  2. List of datasets in computer vision and image processing

    en.wikipedia.org/wiki/List_of_datasets_in...

    RAWPED is a dataset for detection of pedestrians in the context of railways. The dataset is labeled box-wise. 26000 Images Object recognition and classification 2020 [70] [71] Tugce Toprak, Burak Belenlioglu, Burak Aydın, Cuneyt Guzelis, M. Alper Selver OSDaR23 OSDaR23 is a multi-sensory dataset for detection of objects in the context of railways.

  3. Network behavior anomaly detection - Wikipedia

    en.wikipedia.org/wiki/Network_Behavior_Anomaly...

    Network behavior anomaly detection (NBAD) is a security technique that provides network security threat detection. It is a complementary technology to systems that detect security threats based on packet signatures. [1] NBAD is the continuous monitoring of a network for unusual events or trends.

  4. Anomaly detection - Wikipedia

    en.wikipedia.org/wiki/Anomaly_detection

    Three broad categories of anomaly detection techniques exist. [1] Supervised anomaly detection techniques require a data set that has been labeled as "normal" and "abnormal" and involves training a classifier. However, this approach is rarely used in anomaly detection due to the general unavailability of labelled data and the inherent ...

  5. Anomaly-based intrusion detection system - Wikipedia

    en.wikipedia.org/wiki/Anomaly-based_intrusion...

    Anomaly-based Intrusion Detection at both the network and host levels have a few shortcomings; namely a high false-positive rate and the ability to be fooled by a correctly delivered attack. [3] Attempts have been made to address these issues through techniques used by PAYL [ 5 ] and MCPAD.

  6. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Anomaly detection: 2016 (continually updated) [328] Numenta Skoltech Anomaly Benchmark (SKAB) Each file represents a single experiment and contains a single anomaly. The dataset represents a multivariate time series collected from the sensors installed on the testbed.

  7. Security information and event management - Wikipedia

    en.wikipedia.org/wiki/Security_information_and...

    SIEM visibility and anomaly detection could help detect zero-days or polymorphic code. Primarily due to low rates of anti-virus detection against this type of rapidly changing malware. Parsing, log normalization and categorization can occur automatically, regardless of the type of computer or network device, as long as it can send a log.

  8. Local outlier factor - Wikipedia

    en.wikipedia.org/wiki/Local_outlier_factor

    In anomaly detection, the local outlier factor (LOF) is an algorithm proposed by Markus M. Breunig, Hans-Peter Kriegel, Raymond T. Ng and Jörg Sander in 2000 for finding anomalous data points by measuring the local deviation of a given data point with respect to its neighbours.

  9. NodeXL - Wikipedia

    en.wikipedia.org/wiki/NodeXL

    NodeXL is a network analysis and visualization software package for Microsoft Excel 2007/2010/2013/2016. [2] [3] The package is similar to other network visualization tools such as Pajek, UCINet, and Gephi. [4] It is widely applied in ring, mapping of vertex and edge, and customizable visual attributes and tags.