Analysis of Computational Time on DREAD Model
Main Article Content
Abstract
In identifying the risks, there are several factors needed to consider, such as the extent to which these risks are exploited and how much damage will occur. Considerations for choosing the most appropriate risk reduction that is fast and safe to perform a good calculation. Calculation complexity is one thing that should be considered in selecting an algorithm to be applied to the decision support system. This paper uses DREAD model by discussing the complexity testing and implement DREAD model into a program. Complexity is used to find out the computation time and its ratio completed with the result that the computation time of the final data is affected by the data addition. Therefore, the addition of data greatly affects the computation time which is required the ratio of computing time, even though it has a bunch of similar data computation time and in fact these have different results that the ratio of computation time does not give any effect (stable). Computation ratio changes from the initial data group until the end of data group are not significantly compared with the value of computing time for each additional 100 tested data.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
IJCERT Policy:
The published work presented in this paper is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. This means that the content of this paper can be shared, copied, and redistributed in any medium or format, as long as the original author is properly attributed. Additionally, any derivative works based on this paper must also be licensed under the same terms. This licensing agreement allows for broad dissemination and use of the work while maintaining the author's rights and recognition.
By submitting this paper to IJCERT, the author(s) agree to these licensing terms and confirm that the work is original and does not infringe on any third-party copyright or intellectual property rights.
References
McEvoy, N., & Whitcombe, A. (2002). Structured Risk Analysis. In International conference on infrastructure security (Vol. 2437, pp. 88-103). Bristol. October 1-3.
Elky, S. (2006). An Introduction to Information System Risk Management. SANS Institute InfoSec Reading Room. Retrieved from http://www.sans.org.
Hamdani, & Wardoyo, R. (2016). The Complexity Calculation for Group Decision Making Using TOPSIS Algorithm. Advances of Science and Technology for Society AIP Conf. Proc. 1755, 070007-1–070007-7; doi: 10.1063/1.4958502. Published by AIP Publishing. ISBN: 978-0-7354-1413-6.
Ölmez, M., & Lindemann, U. (2014). Procedia Comput. Sci., 28, 130.
Wegener, I. (2005). Complexity Theory (Exploring the Limits of Efficient Algorithms). Dortmund: Springer-Verlag.
Sipser, M. (2006). Introduction to the Theory of Computation – Second Edition. Massachusetts: Thomson Course Technology.
Meier, J. D., Mackman, A., Vasireddy, S., Dunner, M., Escamilla, S., & Murukan, A. (2003). Improving web application security: Threats and Countermeasures. Microsoft Corporation.