Identifying Malicious Botnet Traffic through Active Monitoring Approach

Abstract

Botnet represents one of the most genuine dangers to network access. The Botnet malware ordinarily searches for vulnerable device over the web. It endeavors to infect as many associated devices as possible, utilizing their assets for mechanized undertakings that may cause noteworthy financial and social damage while being covered up to the user and device. Botnet is a malicious and harmful activity; the detection of such activity is the most crucial task. To detect such activity, there are several detection techniques available like DNS based, Anomaly-based, Signature-based and Network-based. As per research, no one detection technique is 100% accurate, as each detection technique has its advantages and limitation. So, to make our device and data secure from such activity, data and device honor need to take care. So, user can get idea and alert regarding such activity if it is happening through our device and on our data. In this paper, we have explored the network traffic monitoring approach, which can be used for accurate and efficient identification of botnet network activity and experimented how, through active monitoring of devices; device honor could get a hint for malicious activities on their device.