• Aaditya Banchhiwal
• Jatin Bhardwaj
• M L Sharma
• V K Saini
• K C Tripathi

The effect of the threats posed by Distributed Denial of Service (DDoS) attacks on substantially large networks, such as a Blockchain network, demands effective detection and response methods due to the sheer enormity of the problems it causes. These methods are to be deployed not only at the network edge but also at its core. This paper gives an overview of a new solution that would prevent such attacks. It states that web applications can be prevented from DDoS attack by using a layered architecture based on blockchain and deep learning. This can prevent DDoS attack by capturing all the incoming traffic requests made to the server. The requests are redirected to a blockchain based architecture having computational capabilities of smart contracts. In this decentralized database, the dataset of various traffic requests are stored in the form of cryptographically secured chunks. The smart contract is used to filter out requests based on the type of request and some previously set parameters. The parameters are fed to the deep learning layer that is able to detect the anomalous request and differentiate between a genuine and a malicious user. The attack patterns show anomalies in the characteristics of the different selected packet attributes. Accuracy of detection and performance of the system is analyzed using live traffic traces from a variety of network environments ranging from points in the core of the network to those in an edge network.

DDoS Attack, Cybersecurity, Blockchain, Smart Contracts, Machine Learning

"DDoS Prevention on Distributed application using Blockchain Smart Contracts and Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 4, page no.16-22, April-2020, Available :http://www.jetir.org/papers/JETIR2004203.pdf

"DDoS Prevention on Distributed application using Blockchain Smart Contracts and Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 4, page no. pp16-22, April-2020, Available at : http://www.jetir.org/papers/JETIR2004203.pdf