Custom machine learning architectures: towards realtime anomaly detection for flight testing.
Di WuZhanrui SunYongxin ZhuLi TianHanlin ZhuPeng XiongZihao CaoMenglin WangYu ZhengChao XiongHao JiangKuen Hung TsoiXinyu NiuWei MaoCan FengXiaowen ZhaGuobao DengWayne LukPublished in: IPDPS Workshops (2018)
Keyphrases
- anomaly detection
- machine learning
- network anomaly detection
- intrusion detection
- detecting anomalies
- network traffic
- unsupervised anomaly detection
- anomalous behavior
- network intrusion detection
- unsupervised learning
- behavior analysis
- intrusion detection system
- computer security
- pattern recognition
- data mining
- detect anomalies
- detecting anomalous
- negative selection algorithm
- one class support vector machines
- learning algorithm
- computer vision
- text mining
- data analysis
- cumulative sum
- supervised learning
- decision trees
- feature selection
- learning problems
- network security
- reinforcement learning
- model selection
- text classification
- computational intelligence
- natural language processing
- knowledge discovery