Reducing Data Complexity in Feature Extraction and Feature Selection for Big Data Security Analytics
| Title | Reducing Data Complexity in Feature Extraction and Feature Selection for Big Data Security Analytics |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Sisiaridis, D., Markowitch, O. |
| Conference Name | 2018 1st International Conference on Data Intelligence and Security (ICDIS) |
| Keywords | apache spark, application program interfaces, artificial intelligence, artificial intelligence security, Big Data, big data security analytics, Complexity theory, composability, computational complexity, cyber security, cybersecurity attacks, cybersecurity threats, data complexity, data mining, data mining techniques, feature extraction, feature selection, heterogeneous data, Human Behavior, input logs preprocessing, learning (artificial intelligence), machine learning, machine learning algorithms, Metrics, network sensors, pubcrawl, pyspark, python, python API, Resiliency, security, security of data, Task Analysis |
| Abstract | Feature extraction and feature selection are the first tasks in pre-processing of input logs in order to detect cybersecurity threats and attacks by utilizing data mining techniques in the field of Artificial Intelligence. When it comes to the analysis of heterogeneous data derived from different sources, these tasks are found to be time-consuming and difficult to be managed efficiently. In this paper, we present an approach for handling feature extraction and feature selection utilizing machine learning algorithms for security analytics of heterogeneous data derived from different network sensors. The approach is implemented in Apache Spark, using its python API, named pyspark. |
| URL | https://ieeexplore.ieee.org/document/8367638 |
| DOI | 10.1109/ICDIS.2018.00014 |
| Citation Key | sisiaridis_reducing_2018 |
- pubcrawl
- heterogeneous data
- Human behavior
- input logs preprocessing
- learning (artificial intelligence)
- machine learning
- machine learning algorithms
- Metrics
- network sensors
- Feature Selection
- pyspark
- Python
- python API
- Resiliency
- security
- security of data
- Task Analysis
- apache spark
- feature extraction
- data mining techniques
- Data mining
- data complexity
- cybersecurity threats
- cybersecurity attacks
- cyber security
- computational complexity
- composability
- Complexity theory
- big data security analytics
- Big Data
- artificial intelligence security
- Artificial Intelligence
- application program interfaces