Anomaly Based Distributed Denial of Service Attack Detection and Prevention with Machine Learning
| Title | Anomaly Based Distributed Denial of Service Attack Detection and Prevention with Machine Learning |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Dincalp, Uygar, Güzel, Mehmet Serdar, Sevine, Omer, Bostanci, Erkan, Askerzade, Iman |
| Conference Name | 2018 2nd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) |
| Date Published | Oct. 2018 |
| Publisher | IEEE |
| ISBN Number | 978-1-5386-4184-2 |
| Keywords | anomaly based distributed denial of service attack detection, attack vectors, clustering algorithm, Clustering algorithms, composability, Computer crime, computer network security, DBSCAN, DDoS Attack, DDoS Attack Prevention, DoS-DDoS attacks, feature extraction, Human Behavior, learning (artificial intelligence), machine learning, Measurement, Metrics, network traffic, Particle separators, pattern clustering, pubcrawl, resilience, Resiliency, service attack detection, telecommunication traffic |
| Abstract | Everyday., the DoS/DDoS attacks are increasing all over the world and the ways attackers are using changing continuously. This increase and variety on the attacks are affecting the governments, institutions, organizations and corporations in a bad way. Every successful attack is causing them to lose money and lose reputation in return. This paper presents an introduction to a method which can show what the attack and where the attack based on. This is tried to be achieved with using clustering algorithm DBSCAN on network traffic because of the change and variety in attack vectors. |
| URL | https://ieeexplore.ieee.org/document/8567252 |
| DOI | 10.1109/ISMSIT.2018.8567252 |
| Citation Key | dincalp_anomaly_2018 |
- Human behavior
- telecommunication traffic
- service attack detection
- Resiliency
- resilience
- pubcrawl
- pattern clustering
- Particle separators
- network traffic
- Metrics
- Measurement
- machine learning
- learning (artificial intelligence)
- anomaly based distributed denial of service attack detection
- feature extraction
- DoS-DDoS attacks
- DDoS Attack Prevention
- DDoS Attack
- DBSCAN
- computer network security
- Computer crime
- composability
- Clustering algorithms
- clustering algorithm
- Attack vectors