  Cybercrimes are becoming a bigger menace to both people and corporations. It
poses a serious challenge to the modern digital world. According to a press
release from 2019 Cisco and Cybersecurity Ventures, Cisco stopped seven
trillion threats in 2018, or 20 billion threats every day, on behalf of its
clients. According to Cybersecurity Ventures, the global cost of cybercrime
will reach \$6 trillion annually by 2021, which is significantly more than the
annual damage caused by all natural disasters and more profitable than the
global trade in all major illegal narcotics put together. Malware software,
including viruses, worms, spyware, keyloggers, Trojan horses, and botnets, is
therefore frequently used in cybercrime. The most common malware employed by
attackers to carry out cybercrimes is the botnet, which is available in a
variety of forms and for a variety of purposes when attacking computer assets.
However, the issue continues to exist and worsen, seriously harming both
enterprises and people who conduct their business online. The detection of P2P
(Peer to Peer) botnet, which has emerged as one of the primary hazards in
network cyberspace for acting as the infrastructure for several cyber-crimes,
has proven more difficult than regular botnets using a few existing approaches.
As a result, this study will explore various P2P botnet detection algorithms by
outlining their essential characteristics, advantages and disadvantages,
obstacles, and future research.
