• Akshata Zanje
• Amit Kshirsagar
• Akshay Wankhade
• Himanshu Thakare

Computers and networks have been under threat from viruses, worms and attacks from hackers since they were first used. In 2018, the number of devices connected to the Internet exceeded the number of human beings and this increasing trend will see about 80 billion devices by 2024. Securing these devices and the data passing between them is a challenging task because the number of IBAs is also increasing sharply year by year. To address this issue, a large number of defences against network attacks have been proposed in the literature. Despite all the efforts made by researchers in the community over the last two decades, the network security problem is not completely solved. In general, defence against network attacks consists of preparation, detection and reaction phases. The core element of a good defence system is an IOT Botnet Attack (IBA) Detection System (IBA-DS), which provides proper attack detection before any reaction. An IBA-DS aims to detect IBAs before they seriously damage the network. The term IBA refers to any un-authorized attempt to access the elements of a network with the aim of making the system unreliable.

IoT,botnets, machine learning, IDS, feature selection, LSTM, RNN

"Efficient Approach For Detection Of Iot-Botnet Cyber Attack Using Machine Learning ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.284-287, May-2023, Available :http://www.jetir.org/papers/JETIRFX06050.pdf

"Efficient Approach For Detection Of Iot-Botnet Cyber Attack Using Machine Learning ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. pp284-287, May-2023, Available at : http://www.jetir.org/papers/JETIRFX06050.pdf