Networking and Communication Engineering

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

An Analysis on Mobile Visualization Connectionist IDS


Affiliations
1 Bharathiar University, Coimbatore, India
2 School of Computer Studies (PG), RVS College of Arts and Science, Coimbatore, India
     

   Subscribe/Renew Journal


This study introduces and describes a novel Intrusion Detection System (IDS) called MOVCIDS (Mobile Visualization Connectionist IDS). By its advanced visualization facilities, the proposed IDS allows providing an overview of the network traffic as well as identifying anomalous situations tackled by computer networks, responding to the challenges presented by volume, dynamics and diversity of the traffic, including novel (0-day) attacks. MOVCIDS splits massive traffic data into segments and analyze them, thereby providing administrators with an intuitive snapshot to analyze the kinds of events taking place on the computer network. IDS have been probed through several real anomalous situations related to the Simple Network Management Protocol as it is potentially dangerous. GICAP-IDS dataset is used to protect from the external attacks. The main experimental study of MOVCIDS makes use of this dataset.
User
Subscription Login to verify subscription
Notifications
Font Size

Abstract Views: 180

PDF Views: 2




  • An Analysis on Mobile Visualization Connectionist IDS

Abstract Views: 180  |  PDF Views: 2

Authors

K. Poongodi
Bharathiar University, Coimbatore, India
B. Rosiline Jeetha
School of Computer Studies (PG), RVS College of Arts and Science, Coimbatore, India

Abstract


This study introduces and describes a novel Intrusion Detection System (IDS) called MOVCIDS (Mobile Visualization Connectionist IDS). By its advanced visualization facilities, the proposed IDS allows providing an overview of the network traffic as well as identifying anomalous situations tackled by computer networks, responding to the challenges presented by volume, dynamics and diversity of the traffic, including novel (0-day) attacks. MOVCIDS splits massive traffic data into segments and analyze them, thereby providing administrators with an intuitive snapshot to analyze the kinds of events taking place on the computer network. IDS have been probed through several real anomalous situations related to the Simple Network Management Protocol as it is potentially dangerous. GICAP-IDS dataset is used to protect from the external attacks. The main experimental study of MOVCIDS makes use of this dataset.