@article{sangeetha prabhu_2024, 
  title={A NOVEL DEEP LEARNING BASED CYBER ATTACK  DETECTION SYSTEM WITH BAIT BASED APPROACH FOR  MITIGATION}, 
  DOI={10.5281/zenodo.10867501}, 
  abstractNote={Almost every industry, government along with financial institution has transformed their transactions into cyberinfrastructure owing to augmenting trust and utilization of the Internet. Thus, the cyber system is made vulnerable to cyber-attacks. A malicious effort by an individual or else organization for breaching another system's information system is termed a cyber-attack organization. The (1) business organization, (2) military, (3) government, with (4) other financial institutions like banking are focused by the cyber-attacks either to hack secured information or for a ransom. The threat or crime related to a malicious event owing to a malware attack in cyber-space, which distraction and loss in business and money, is termed Cyber-risk. It frequently takes place in the form of security threats like spamming, hacking, and phishing. By stealing the information along with gaining admission to the remote objective, malware, which is malicious software, is developed to damage computer resources .exe, scripts, dlls, files, macros, et cetera are a few forms of malware that could function at the system's background. For 80% of cyber-attacks globally, present-day malware is responsible. By aiming at commercial enterprises, elevated valued persons, and government that is linked to the Internet, much malware is propagated via the internet. For stealing data from infected targets, most cybercriminals take advantage of internet-centric services. Internet-centric attacks on government and corporate have increased by 47% as per the Bureau of Information Resource Management and Federal Information Security (FIS). On the federal network, FIS has records of 4500 malicious samples, 4.5 million spam emails, together with over a billion spams.}, 
  publisher={Zenodo}, 
  author={Sangeetha Prabhu}, 
  year={2024}, 
  month={Mar}
  }