to download project abstract of ai and ml

At DataPro, we provide final year projects with source code in python for computer science students in Hyderabad , Visakhapatnam.


We provide ai and ml projects in this abstract.

Bot detection using machine learning (ML), with network flow-level features, has
been extensively studied in the literature. However, existing
approaches typically incur a high computational overhead and do not completely
capture the network communication patterns, which can expose additional aspects
of malicious hosts. Recently, bot detection systems that leverage communication
graph analysis using ML have gained attention to overcome these limitations.

A graph-based approach is rather intuitive, as graphs are true representation of
network communications. In this paper, we propose BotChase, a two-phased
graph-based bot detection system that leverages both unsupervised and
supervised ML. The first phase prunes presumable benign hosts, while the second
phase achieves bot detection with high precision. Our prototype implementation of
BotChase detects multiple types of bots and exhibits robustness to zero-day
attacks. It also accommodates different network topologies and is suitable for
large-scale data. Compared to the state-of-the-art, BotChase outperforms an end-
to-end system that employs flow-based features and performs particularly well in
an online setting.

Malicious Attacks Detection Using Machine  Learning - ai and ml
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