Detecting Malware & Network Intrusions Essay

Pages: 4 (1317 words)  ·  Bibliography Sources: 4  ·  File: .docx  ·  Level: Master's  ·  Topic: Computer Science  ·  Written: July 16, 2019

SAMPLE EXCERPT:

[. . .]

Some of the advantages of signature based techniques include:
  • Malware can be detected easily
  • Using less resources compared to other approaches
The disadvantage, however, is that unknown malwares cannot be detected.

Some advantages of heuristic system include unknown and known malware can be detected. The disadvantages include:
  • The levels of false positives are high
  • It needs more time and resources due to space
  • Data needs to be updated frequently to know the new malware codes available.
Specification based has advantages like:
  • Unknown and new malware can be detected
  • Low levels of false positives
Disadvantages include:
  • High levels of false positives
  • New malware cannot be detected efficiently
  • Development of specifications is time consuming

Network Intrusion Identification and Malware Detection Techniques

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Behavioral blocking; suspicious behavior approach does not identify known viruses but monitors the behavior of all programs. The techniques are borrowed from Heuristic and Generic direction. For example, if a program attempts to write or read data to an executable file, an antivirus can flag the behavior and alert the user on the next course of action. This is a good technique to block any new malware since it can only monitor the behavior of any file being changed in the system however this brings about a large number of false positives.

Essay on Detecting Malware & Network Intrusions Assignment

Recently, complicated behavior analysis has emerged looking at all possibilities from a kernel context before deciding on the malware to detect and delete. Unlike fingerprint sensor scanners or heuristic approach, behavior blocking software integrates with the operating system and monitors all the programs in real-time. Before malicious actions get to do harm to the machine, their behavior is monitored and blocked form executing any actions in the host computer. The behaviors might be like;
  • Attempts to format a disk drive
  • Modification of logical executable files
  • Attempts to view a file or delete
  • Modification of critical system settings
In case any of these behaviors is detected, the malware intrusion preventive measures are always deployed to scan the system and ensure every file is clean and free of any malware. In case the host computer is connected to the internet, Malwarebytes should be deployed to monitor any suspicious activity over the web and traffic flowing into and out of the network. Heuristic system can be deployed to the host computer to monitor each and every traffic packet, files and activities in that machine and then deployed into other host computers to monitor for malwares.

In conclusion, internet is growing each and every day with malware and threats to computer systems being the most prolific matter. Malware attack the system and corrupt files, disrupt the working of the computer and sometimes crashed it. The polymorphic nature of how it’s written shows destruction it causes to computer systems and networks too and it makes it difficult to adjust to this kind of threat since they also adapt to antimalware tactics. The fastest solution is using AI and machine learning techniques to teach machines how to think like human and act like intrusion detection systems. Being able to monitor traffic, corrupt files, modifications and any threats to a computer system is crucial for data safety especially for big firms.

References
  1. Discussions, S., & Discussions, G. (2019). Malware Detection Techniques Description. Retrieved from https://malwaretips.com/threads/malware-detection-techniques-description.14028/
  2. Nancy, Dr. Sanjay Silakari, & Uday Chourasia. (2016). A Survey Over the Various Malware Detection Techniques used in Cloud Computing. International Journal Of Engineering Research And, V5(02). doi: 10.17577/ijertv5is020388
  3. RIASAT, R., SAKEENA, M., WANG, C., SADIQ, A., & WANG, Y. (2017). A Survey on Android… [END OF PREVIEW] . . . READ MORE

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