  Cyber-attacks have been one of the deadliest attacks in today's world. One of
them is DDoS (Distributed Denial of Services). It is a cyber-attack in which
the attacker attacks and makes a network or a machine unavailable to its
intended users temporarily or indefinitely, interrupting services of the host
that are connected to a network. To define it in simple terms, It's an attack
accomplished by flooding the target machine with unnecessary requests in an
attempt to overload and make the systems crash and make the users unable to use
that network or a machine. In this research paper, we present the detection of
DDoS attacks using neural networks, that would flag malicious and legitimate
data flow, preventing network performance degradation. We compared and assessed
our suggested system against current models in the field. We are glad to note
that our work was 99.7\% accurate.
