DDoS Attack Detection on Bitcoin Ecosystem using Deep-Learning

Since Bitcoin, the first cryptocurrency that applied blockchain technology was developed by Satoshi Nakamoto, the cryptocurrency market has grown rapidly. Along with this growth, many vulnerabilities and attacks are threatening the Bitcoin ecosystem, which is not only at the bitcoin network-level but also at the service level that applied it, according to the survey. We intend to analyze and detect DDoS attacks on the premise that bitcoin's network-level data and service-level DDoS attacks with bitcoin are associated. We evaluate the results of the experiment according to the proposed metrics, resulting in an association between network-level data and service-level DDoS attacks of bitcoin. In conclusion, we suggest the possibility that the proposed method could be applied to other blockchain systems.

[1]  Aron Laszka,et al.  When Bitcoin Mining Pools Run Dry - A Game-Theoretic Analysis of the Long-Term Impact of Attacks Between Mining Pools , 2015, Financial Cryptography Workshops.

[2]  Satoshi Nakamoto Bitcoin : A Peer-to-Peer Electronic Cash System , 2009 .

[3]  Bitcoin Risk Analysis , 2014 .

[4]  Wei Shao,et al.  Identifying Bitcoin Users Using Deep Neural Network , 2018, ICA3PP.

[5]  Simon Caton,et al.  Predicting the Price of Bitcoin Using Machine Learning , 2018, 2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP).

[6]  Kai Zimmermann,et al.  Bitcoin - Asset or Currency? Revealing Users' Hidden Intentions , 2014, ECIS.

[7]  Damon McCoy,et al.  Stressing Out: Bitcoin "Stress Testing" , 2016, Financial Cryptography Workshops.

[8]  Venkata Marella Bitcoin: A Social Movement Under Attack , 2017 .

[9]  Steven Lee,et al.  Anomaly Detection in the Bitcoin System - A Network Perspective , 2016, ArXiv.

[10]  Steven Lee,et al.  Anomaly Detection in Bitcoin Network Using Unsupervised Learning Methods , 2016, ArXiv.

[11]  Neil Gandal,et al.  Price Manipulation in the Bitcoin Ecosystem , 2017 .

[12]  Konstantinos Markantonakis,et al.  An Evaluation of the Security of the Bitcoin Peer-To-Peer Network , 2018, 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData).

[13]  Vukosi N. Marivate,et al.  Unsupervised learning for robust Bitcoin fraud detection , 2016, 2016 Information Security for South Africa (ISSA).

[14]  Luca de Alfaro,et al.  Learning From Graph Neighborhoods Using LSTMs , 2016, AAAI Workshops.

[15]  Tyler Moore,et al.  Empirical Analysis of Denial-of-Service Attacks in the Bitcoin Ecosystem , 2014, Financial Cryptography Workshops.

[16]  Myung-Sup Kim,et al.  A survey on blockchain cybersecurity vulnerabilities and possible countermeasures , 2019, Int. J. Netw. Manag..

[17]  D. Yermack Is Bitcoin a Real Currency? An Economic Appraisal , 2013 .

[18]  Tyler Moore,et al.  The impact of DDoS and other security shocks on Bitcoin currency exchanges: evidence from Mt. Gox , 2017, J. Cybersecur..

[19]  Deepak Zambre Analysis of Bitcoin Network Dataset for Fraud , 2013 .