TY - JOUR
T1 - Neural network based attack detection algorithm
AU - Barradas-Acosta, Araceli
AU - Anaya, Eleazar Aguirre
AU - Nakano-Miyatake, Mariko
AU - Perez-Meana, Hector
PY - 2009/9/3
Y1 - 2009/9/3
N2 - The influence of computer technology on the human activities has greatly increased during the last three decades, due to major developments in the VLSI technology. However this widespread use of computer equipments has generated computer a considerable increase of computer crimes. To reduce this problem it is necessary to carried out a network analysis using the computer network traffic. However the increase of network traffic is huge, doing the analysis of traffic data complicated. Thus it is required to develop an effective and automatic algorithm to carry out the traffic network analysis, facilitating I such way the expert forensic work. This paper proposes a network analysis algorithm using recurrent neural network that can analyze computer network attacks facilitating the evidence extraction. Proposed algorithm can reduce time and cost of forensic.
AB - The influence of computer technology on the human activities has greatly increased during the last three decades, due to major developments in the VLSI technology. However this widespread use of computer equipments has generated computer a considerable increase of computer crimes. To reduce this problem it is necessary to carried out a network analysis using the computer network traffic. However the increase of network traffic is huge, doing the analysis of traffic data complicated. Thus it is required to develop an effective and automatic algorithm to carry out the traffic network analysis, facilitating I such way the expert forensic work. This paper proposes a network analysis algorithm using recurrent neural network that can analyze computer network attacks facilitating the evidence extraction. Proposed algorithm can reduce time and cost of forensic.
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M3 - Article
SP - 905
EP - 915
JO - WSEAS Transactions on Computers
JF - WSEAS Transactions on Computers
SN - 1109-2750
ER -