Toward detecting accidents with already available passive traffic information
RW Thomas, JM Vidal - 2017 IEEE 7th annual computing and …, 2017 - ieeexplore.ieee.org
Traffic accidents occur every day, causing disruptions. The longer disruptions are in place,
the more severe they may become as additional vehicles continue to enter the affected …
the more severe they may become as additional vehicles continue to enter the affected …
[图书][B] Application of machine learning techniques to detecting anomalies in communication networks: Datasets and feature selection algorithms
Detecting, analyzing, and defending against cyber threats is an important topic in cyber
security. Applying machine learning techniques to detect such threats has received …
security. Applying machine learning techniques to detect such threats has received …
Data stream anomaly detection through principal subspace tracking
PH dos Santos Teixeira, RL Milidiú - … of the 2010 ACM Symposium on …, 2010 - dl.acm.org
We consider the problem of anomaly detection in multiple co-evolving data streams. In this
paper, we introduce FRAHST (Fast Rank-Adaptive row-Householder Subspace Tracking). It …
paper, we introduce FRAHST (Fast Rank-Adaptive row-Householder Subspace Tracking). It …
Concise logarithmic loss function for robust training of anomaly detection model
YH Park - arXiv preprint arXiv:2201.05748, 2022 - arxiv.org
Recently, deep learning-based algorithms are widely adopted due to the advantage of being
able to establish anomaly detection models without or with minimal domain knowledge of …
able to establish anomaly detection models without or with minimal domain knowledge of …
Evaluation of support vector machine kernels for detecting network anomalies
Border Gateway Protocol (BGP) is used to exchange routing information across the Internet.
BGP anomalies severely affect network performance and, hence, algorithms for anomaly …
BGP anomalies severely affect network performance and, hence, algorithms for anomaly …
A hybrid method based on genetic algorithm, self-organised feature map, and support vector machine for better network anomaly detection
S Anil, R Remya - 2013 Fourth international conference on …, 2013 - ieeexplore.ieee.org
Anomaly-based network intrusion detection techniques are a valuable technology to shield
our systems and networks against the malicious activities. Anomaly detection is done by soft …
our systems and networks against the malicious activities. Anomaly detection is done by soft …
Big data analytics for classification of network enabled devices
D Arora, KF Li, A Loffler - 2016 30th International Conference …, 2016 - ieeexplore.ieee.org
As information technology (IT) and telecommunication systems continue to grow in size and
complexity, especially with Internet of Things (IoT) gaining popularity, maintaining a secure …
complexity, especially with Internet of Things (IoT) gaining popularity, maintaining a secure …
Feature selection for classification of BGP anomalies using Bayesian models
Traffic anomalies in communication networks greatly degrade network performance. Early
detection of such anomalies alleviates their effect on network performance. A number of …
detection of such anomalies alleviates their effect on network performance. A number of …
Matrix differential decomposition-based anomaly detection and localization in NFV networks
J Chen, M Chen, X Wei, B Chen - IEEE Access, 2019 - ieeexplore.ieee.org
Network function virtualization (NFV) is a promising network paradigm that enables the
design and implementation of novel network services with lower cost, increased agility, and …
design and implementation of novel network services with lower cost, increased agility, and …