The security of computer networks plays a strategic role in modern computer systems. In order to enforce high protection levels against threats, a number of software tools are currently developed. Intrusion Detection Systems aim at detecting intruder who eluded the "first line" protection. In this paper, a pattern recognition approach to network intrusion detection based on ensemble learning paradigms is proposed. The potentialities of such an approach for data fusion and some open issues are outline
Undoubtedly, the advancements in Machine Learning (ML) and especially ensemble learning models enabl...
In order to adapt to the rapid development of network technology and network security detection in d...
Of late, Network Security Research is taking center stage given the vulnerability of computing ecosy...
The security of computer networks plays a strategic role in modern computer systems. In order to en...
Undoubtedly, the advancements in Machine Learning (ML) and especially ensemble learning models enabl...
AbstractThe master thesis focuses on ensemble approaches applied to intrusion detection systems (IDS...
AbstractThe master thesis focuses on ensemble approaches applied to intrusion detection systems (IDS...
Proper security solutions in the cyber world are crucial for enforcing network security by providing...
Proper security solutions in the cyber world are crucial for enforcing network security by providing...
Dottorato di Ricerca in Information and Communication Engineering For Pervasive Intelligent Environm...
Abstract—The paper discusses intrusion detection systems built using ensemble approaches, i.e., by c...
Due to the extensive use of computer networks, new risks have arisen, and improving the speed and ac...
Due to the extensive use of computer networks, new risks have arisen, and improving the speed and ac...
In this paper we describe the main ensemble learning techniques and their application in the cyberse...
To achieve high accuracy while lowering false alarm rates are major challenges in designing an intru...
Undoubtedly, the advancements in Machine Learning (ML) and especially ensemble learning models enabl...
In order to adapt to the rapid development of network technology and network security detection in d...
Of late, Network Security Research is taking center stage given the vulnerability of computing ecosy...
The security of computer networks plays a strategic role in modern computer systems. In order to en...
Undoubtedly, the advancements in Machine Learning (ML) and especially ensemble learning models enabl...
AbstractThe master thesis focuses on ensemble approaches applied to intrusion detection systems (IDS...
AbstractThe master thesis focuses on ensemble approaches applied to intrusion detection systems (IDS...
Proper security solutions in the cyber world are crucial for enforcing network security by providing...
Proper security solutions in the cyber world are crucial for enforcing network security by providing...
Dottorato di Ricerca in Information and Communication Engineering For Pervasive Intelligent Environm...
Abstract—The paper discusses intrusion detection systems built using ensemble approaches, i.e., by c...
Due to the extensive use of computer networks, new risks have arisen, and improving the speed and ac...
Due to the extensive use of computer networks, new risks have arisen, and improving the speed and ac...
In this paper we describe the main ensemble learning techniques and their application in the cyberse...
To achieve high accuracy while lowering false alarm rates are major challenges in designing an intru...
Undoubtedly, the advancements in Machine Learning (ML) and especially ensemble learning models enabl...
In order to adapt to the rapid development of network technology and network security detection in d...
Of late, Network Security Research is taking center stage given the vulnerability of computing ecosy...
Add to ORKG