Nasn A Novel Approach for Securing Network from Malware Injection
Bany Muhammad, Nooh
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With immense globalization and the fast growth of technologies, the world is now running with the real time technologies which means the communication made over the internet and the data is fetched simultaneously from the website. There are different websites which include the vulnerability of hosting the suspicious activities like hosting of the Malware or Worm which cause serious effect on the running system. Malware is such a threat which is injected silently and creates a massive affect on the system by creating different types of syndrome on the system like the system slow down, unexpected shut down and even the data breach. Data breach is actually the main target of the hackers through which the hacker steals data from the database and flies off. This is because of unsecured network protection and unreliable software hosting on system. So, to make the system secure over the network the protection should be upgraded with new approach so that the unauthorized access to the network can be restricted. As the hackers leave no stamp for their identification, so after the data breach takes place, the IP of the hacker cannot be recognized. This is the reason for which the hackers are hard to be recognized. There are different approaches to prevent the suspicious access but most of them are basically cracked by the data hijackers. In this paper, the discussion and the approach are made through which the unauthorized access can be obstructed and thereby the probability of hijacking of the host system can be minimized by using the Artificial Neural Network.