International Journal of Computer Networks and Communications Security

Volume 7, Issue 3, March 2019

 

 

Modified Grey Wolf Optimization Algorithm by using Classical Optimization Methods
 

Modified Grey Wolf Optimization Algorithm by using Classical Optimization Methods

Pages: 49-60 (12) | [Full Text] PDF (635 KB)
RB Thanoon, BA Mitras
Department of mathematics, college of computer sciences & mathematics, Mosul

Abstract -
The Grey Wolf optimization algorithm represents one of a post- intuition algorithms, which was proposed first time in 2014 by Mirijalili, an algorithm based on swarms intelligence and community intelligence which inspired from the behavior of Grey wolves. It has excellent properties that exceed the characteristics of the other swarms intelligence because it is simple, flexible, easy to use and capable to developing and had a special ability to achieve the right balance between exploration and exploitation during research. Two Hybrid algorithms of the Grey wolves algorithm were proposed in this paper with two classical algorithms: (Conjugate Gradient Algorithm ) and the second is ( Parallel Tangent Algorithm). Each of the two algorithms above improves the elementary community randomly generated as the primary community of the Grey Wolves optimization algorithm using the characteristics of the two classical algorithms above. The test was applied to (10) high-efficiency optimization functions with different dimensions and different iteration . The results of the hybrid algorithms were excellent, encouraging and superior to the original algorithms. The new algorithms showed very high efficiency. The hybrid algorithms achieved optimal solutions by achieving the most minimum value ( f mini) for most of these functions that have been tested statistically by calculating the minimum average values for more than one implementation.
 
Index Terms - Grey wolf optimization, post- intuition algorithms, Conjugate Gradient methods, Parallel Tangent method, unconstrained Optimization

Citation - RB Thanoon, BA Mitras. "Modified Grey Wolf Optimization Algorithm by using Classical Optimization Methods." International Journal of Computer Networks and Communications Security 7, no. 3 (2019): 49-60.

Representation of the Block Data Encryption Algorithm in an Analytical form for Differential Cryptanalysis
 

Representation of the Block Data Encryption Algorithm in an Analytical form for Differential Cryptanalysis

Pages: 61-64 (4) | [Full Text] PDF (702 KB)
JG Umarovich, MA Rakhimovich
Docent, Candidate of physics-mathematics, Department of Information Security, Faculty of Mathematics, National University of Uzbekistan named after Mirzo Ulugbek, City Tashkent, Uzbekistan
Rector, Doctor of technical sciences, professor, National University of Uzbekistan named after Mirzo Ulugbek , City Tashkent, Uzbekistan

Abstract -
The article presents the study of cryptographic transformations of the Kuznyechik algorithm in relation to differential analysis and the translation of their representations into a more convenient form for cryptanalysis. A simplification of the type of transformations of the algorithm to algebraic the form, in which cryptanalysis software will be more effective. Since the description of the algorithm in the analytical form allows for 16 cycles of execution of the shift register with linear feedback, each of which will be carried out 16 operations of multiplication and 15 operations of addition, reduced to 16 multiplying and 15 the operations of addition. The result is an algebraic form of linear transformation (from shift register with linear feedback to matrix multiplication in a finite field). Two theorems, which are the basis of the simplified analysis, are proved. Due to them, it is not necessary to store 16 matrices of 256×256 sizes each, but only to perform the multiplication operation, as well as to store the minimum number of differential analysis matrices.
 
Index Terms - Block Cipher, Transform, Differential Cryptanalysis

Citation - JG Umarovich, MA Rakhimovich. "Representation of the Block Data Encryption Algorithm in an Analytical form for Differential Cryptanalysis." International Journal of Computer Networks and Communications Security 7, no. 3 (2019): 61-64.

A Taxonomy of Potential Factors Determining the Performance of IT-Organizations Using Cloud Computing
 

A Taxonomy of Potential Factors Determining the Performance of IT-Organizations Using Cloud Computing

Pages: 65-71 (7) | [Full Text] PDF (308 KB)
S Abdullahi, LI Bagiwa
Department of Mathematics and Computer Sciences, Faculty of Natural and Applied Sciences Al-Qalam University, Katsina, P.M.B. 2137 Dutsinma Road, Katsina State. Nigeria

Abstract -
Cloud computing is an internet based computing environment that provides services and other computing resources for users to subscribe who only pay for the resources and services used. Cloud computing is ideal technology now a days for small and medium business organizations. The technology gives opportunity to small and medium business organizations to have access to infrastructures that they cannot afford to buy as well as compete in large business markets. . It provides attractive benefits to many public and private organizations like Pay As You Use (PAYU), fast deployment, Flexibility etc. This paper identify twenty (20) potential factors determining the performance of IT-Organization using cloud computing services and categorized these factors according to organizational or functional unit.
 
Index Terms - Cloud Computing, Cloud Performance, Organizational performance, Cloud Performance factors

Citation - S Abdullahi, LI Bagiwa. "A Taxonomy of Potential Factors Determining the Performance of IT-Organizations Using Cloud Computing." International Journal of Computer Networks and Communications Security 7, no. 3 (2019): 65-71.