Network anomaly detection: methods, systems and tools
MH Bhuyan, DK Bhattacharyya… - … surveys & tutorials, 2013 - ieeexplore.ieee.org
Network anomaly detection is an important and dynamic research area. Many network
intrusion detection methods and systems (NIDS) have been proposed in the literature. In this …
intrusion detection methods and systems (NIDS) have been proposed in the literature. In this …
[图书][B] Network anomaly detection: A machine learning perspective
DK Bhattacharyya, JK Kalita - 2013 - books.google.com
With the rapid rise in the ubiquity and sophistication of Internet technology and the
accompanying growth in the number of network attacks, network intrusion detection has …
accompanying growth in the number of network attacks, network intrusion detection has …
Rough computing—A review of abstraction, hybridization and extent of applications
DP Acharjya, A Abraham - Engineering Applications of Artificial Intelligence, 2020 - Elsevier
The rapid growth of information and communication technology captured common man and
various organizations and influenced each individual's life, work, and study. It leads to a data …
various organizations and influenced each individual's life, work, and study. It leads to a data …
Processing of massive audit data streams for real-time anomaly intrusion detection
Intrusion detection is an important technique in the defense-in-depth network security
framework. Most current intrusion detection models lack the ability to process massive audit …
framework. Most current intrusion detection models lack the ability to process massive audit …
Profiling program behavior for anomaly intrusion detection based on the transition and frequency property of computer audit data
Intrusion detection is an important technique in the defense-in-depth network security
framework. In recent years, it has been a widely studied topic in computer network security …
framework. In recent years, it has been a widely studied topic in computer network security …
Modeling program behaviors by hidden Markov models for intrusion detection
Intrusion detection is an important technique in the defense-in-depth network security
framework and a hot topic in computer network security in recent years. In this paper, a new …
framework and a hot topic in computer network security in recent years. In this paper, a new …
Fast intrusion detection based on a non-negative matrix factorization model
In this paper, we present an efficient fast anomaly intrusion detection model incorporating a
large amount of data from various data sources. A novel method based on non-negative …
large amount of data from various data sources. A novel method based on non-negative …
Network traffic anomaly detection techniques and systems
To develop a network traffic anomaly detection technique and system, it is indeed necessary
to know the basic properties of network-wide traffic. This chapter starts with a discussion of …
to know the basic properties of network-wide traffic. This chapter starts with a discussion of …
Searching of Potentially Anomalous Signals in Cosmic-Ray Particle Tracks Images Using Rough k-Means Clustering Combined with Eigendecomposition-Derived …
Our work presents the application of the rough sets method in the field of astrophysics for the
analysis of observational data recorded by the Cosmic Ray Extremely Distributed …
analysis of observational data recorded by the Cosmic Ray Extremely Distributed …
Machine learning approach for determining feasible plans of a remanufacturing system
Resource planning for a complex remanufacturing system is in general extremely difficult in
terms of, eg, problem size and uncertainties. In many cases, simulation is the only way to …
terms of, eg, problem size and uncertainties. In many cases, simulation is the only way to …