Artificial Neural Network Based IDS
| Title | Artificial Neural Network Based IDS |
| Publication Type | Conference Paper |
| Year of Publication | 2017 |
| Authors | Ádám, Norbert, Madoš, Branislav, Baláž, Anton, Pavlik, Tomáš |
| Conference Name | 2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI) |
| ISBN Number | 978-1-5090-5655-2 |
| Keywords | anomaly based neural network intrusion detection system, anomaly based NIDS, artificial neural network based IDS, Artificial neural networks, Databases, digital signatures, Intrusion detection, Metrics, network intrusion detection systems, neural nets, nMap scanning attack, NNIDS, nonmalicious communication, policy-based governance, Ports (Computers), pubcrawl, resilience, Resiliency, security of data, Sensors, signature based NIDS, Standards, SYN flood attack, telecommunication traffic, UDP flood attack |
| Abstract | The Network Intrusion Detection Systems (NIDS) are either signature based or anomaly based. In this paper presented NIDS system belongs to anomaly based Neural Network Intrusion Detection System (NNIDS). The proposed NNIDS is able to successfully recognize learned malicious activities in a network environment. It was tested for the SYN flood attack, UDP flood attack, nMap scanning attack, and also for non-malicious communication. |
| URL | http://ieeexplore.ieee.org/document/7880294/ |
| DOI | 10.1109/SAMI.2017.7880294 |
| Citation Key | adam_artificial_2017 |
- nonmalicious communication
- UDP flood attack
- telecommunication traffic
- SYN flood attack
- standards
- signature based NIDS
- sensors
- security of data
- Resiliency
- resilience
- pubcrawl
- Ports (Computers)
- policy-based governance
- anomaly based neural network intrusion detection system
- NNIDS
- nMap scanning attack
- neural nets
- network intrusion detection systems
- Metrics
- Intrusion Detection
- digital signatures
- Databases
- Artificial Neural Networks
- artificial neural network based IDS
- anomaly based NIDS