Data Mining Methods for Anomaly Detection of HTTP Request Exploitations

Author(s):  
Xiao-Feng Wang ◽  
Jing-Li Zhou ◽  
Sheng-Sheng Yu ◽  
Long-Zheng Cai
2015 ◽  
Vol 11 (1) ◽  
pp. 89-97 ◽  
Author(s):  
Mohsen Kakavand ◽  
Norwati Mustapha ◽  
Aida Mustapha ◽  
Mohd Taufik Abdullah ◽  
Hamed Riahi

2005 ◽  
Vol 7 (2) ◽  
pp. 132-136 ◽  
Author(s):  
Dragos Margineantu ◽  
Stephen Bay ◽  
Philip Chan ◽  
Terran Lane

2021 ◽  
Vol 11 (17) ◽  
pp. 7987
Author(s):  
Aida Kamišalić ◽  
Renata Kramberger ◽  
Iztok Fister

Blockchain and Data Mining are not simply buzzwords, but rather concepts that are playing an important role in the modern Information Technology (IT) revolution. Blockchain has recently been popularized by the rise of cryptocurrencies, while data mining has already been present in IT for many decades. Data stored in a blockchain can also be considered to be big data, whereas data mining methods can be applied to extract knowledge hidden in the blockchain. In a nutshell, this paper presents the interplay of these two research areas. In this paper, we surveyed approaches for the data mining of blockchain data, yet show several real-world applications. Special attention was paid to anomaly detection and fraud detection, which were identified as the most prolific applications of applying data mining methods on blockchain data. The paper concludes with challenges for future investigations of this research area.


Author(s):  
I.M. Burykin ◽  
◽  
G.N. Aleeva ◽  
R.Kh. Khafizianova ◽  
◽  
...  
Keyword(s):  

2021 ◽  
pp. 111144
Author(s):  
Yuzhou Wang ◽  
Zhengfei Li ◽  
Huanxin Chen ◽  
Jianxin Zhang ◽  
Qian Liu ◽  
...  

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 228598-228604
Author(s):  
Yongqiang Zhao ◽  
Shirui Pan ◽  
Jia Wu ◽  
Huaiyu Wan ◽  
Huizhi Liang ◽  
...  

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