Intrusion detection systems and multisensor data fusion
By Tim Bass. CACM, 2000
628 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Networks and Communications, Hardware and Architecture
View Paper: https://www.semanticscholar.org/paper/870af53ecedc252413a6cf57439c33771f951275
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Juan Domingo Velásquez
- Alejandro Cesar Orgambide Frery
- Azzedine F. M. Boukerche
- Stefano Zanero
- Antonio Alfredo Ferreira Loureiro
- Sergio M. Savaresi
- Jorge A. Balazs
- Eduardo Freire Nakamura
In Computer Networks and Communications
- Horácio Oliveira
- Azzedine F. M. Boukerche
- Antonio Alfredo Ferreira Loureiro
- Eduardo Freire Nakamura
- Juan Domingo Velásquez
- Alejandro Cesar Orgambide Frery
- Stefano Zanero
- Sergio M. Savaresi
In Hardware and Architecture
- Juan Domingo Velásquez
- Alejandro Cesar Orgambide Frery
- Stefano Zanero
- Antonio Alfredo Ferreira Loureiro
- Sergio M. Savaresi
- Jorge A. Balazs
- Eduardo Freire Nakamura
Citations in the corpus
- Vehicular Ad Hoc Networks: A New Challenge for Localization-Based Systems (2008, background): “Lately, these mechanisms have been used in previously unpredicted applications such as intrusion detection [45] and Denial of Service (DoS) detection [46].”
- Opinion Mining and Information Fusion: A survey (2016, methodology): “The JDL Fusion Model was originally designed for addressing the combined effects of different levels of abstraction and problem-space complexity, and was divided in 5 levels at which fusion could be performed [137, 138].”
- Information fusion for wireless sensor networks: Methods, models, and classifications (2007, methodology): “Lately, these mechanisms have been used in new applications such as intrusion detection [Bass 2000] and Denial of Service (DoS) detection [Siaterlis and Maglaris 2004].”
- Unsupervised learning techniques for an intrusion detection system (2004, background): “It is important to note that, since failures and strengths of such approaches are symmetric, some systems try to integrate different approaches [26], but there are difficult and intriguing problems of metrics, fusion and normalization when working on data coming from different sources, somehow tied ”