Explain how the automated malware analysis can be made ineffective and unscalable by the use of two unintelligible techniques, Host Identify-Based Encryption and Instruction Set Localization

 

 

 

 

 

 

 

Impeding Automated Malware Analysis

 

Author Note

 

 

Impeding Automated Malware Analysis

Malware analysis can be depicted as understanding the behavior of various malicious programs (Gandotra et al., 2019). With time, information gathered from the analysis has been used to detect similar malware and repair damaged systems. Additionally, cyber attackers have continued developing systems that prevent malware from being analyzed (Kara, 2019). This has not been of advantage for both parties. In this assignment, the focus will be on how the automated malware analysis can be made ineffective and unscalable by the use of two unintelligible techniques, Host Identify-Based Encryption and Instruction Set Localization, which is believed to make a malware sample dependent on the unique properties of the host it infects.

One thing that motivates me for the project is the fact that the techniques should not be limited to the existing analysis environment but rather be able to resist any potential analysis techniques that may occur in the future. Studies have been done through the stated techniques on the advantages and disadvantages and the various ways they can be implemented effectively to curb malware analysis.

Additionally, various designs can be made on the techniques that may assist in overcoming some challenges, involving host IDs that are the combination of both the host and network identifiers. My contribution is that I will ensure that the techniques are implemented, and the information is followed efficiently. One resource that can be used in this case includes the prototype design that will help explain and test ideas on the two techniques that will be the center of the study (Lauff et al., 2019). Through the resource, designing the host encryption and instruction set localization might easily assist in preventing automated malware analysis.

 

 

References

Gandotra, E., Bansal, D., & Sofat, S. (2019). Malware intelligence: Beyond malware analysis. International Journal of Advanced Intelligence Paradigms, 13(1-2), 80-100.

Kara, I. (2019). A basic malware analysis method. Computer Fraud & Security, 2019(6), 11-19.

Lauff, C., Menold, J., & Wood, K. L. (2019, July). Prototyping canvas: Design tool for planning purposeful prototypes. In Proceedings of the design society: International Conference on Engineering Design (Vol. 1, No. 1, pp. 1563-1572). Cambridge University Press.