An Overview: Stochastic Gradient Descent Classifier, Linear Discriminant Analysis, Deep Learning and Naive Bayes Classifier Approaches to Network Intrusion Detection

The security of Network Systems is ravaged by attacks on Systems in a bid to gain unauthorized access into the network system. The aim of Network Intrusion Detection Systems is to detect anomaly patterns either while the attack is unfolding or after evidence that an intrusion occurred. The demand and crave for Internet usage have surged over the years and will continue to rise, which also puts gadgets that are connected to Networks at risk of attacks by Cyber Terrorist and hackers. This problem is not limited to individuals or Corporations alone but also E-Governments and Enterprises, despite billions of dollars allocated to Cyber Security, computer systems and networks do not give a 100 percent guarantee against Cyber-attacks. It is against this backdrop that we must establish Network Intrusion Detection Systems to reveal and counter Cyber-attacks on Networks and Computer Systems.