Data security is a significant requirement in our time. As a result of the rapid development of unsecured computer networks, the personal data should be protected from unauthorized persons and as a result of exposure AES algorithm is subjected to theoretical attacks such as linear attacks, differential attacks, and practical attacks such as brute force attack these types of attacks are mainly directed at the S-BOX and since the S-BOX table in the algorithm is static and no dynamic so this is a major weakness for the S-BOX table, the algorithm should be improved to be impervious to future dialects that attempt to analyse and break the algorithm  in order to remove these weakness points, Will be generated dynamic substitution box (S-B

The biometric-based keys generation represents the utilization of the extracted features from the human anatomical (physiological) traits like a fingerprint, retina, etc. or behavioral traits like a signature. The retina biometric has inherent robustness, therefore, it is capable of generating random keys with a higher security level compared to the other biometric traits. In this paper, an effective system to generate secure, robust and unique random keys based on retina features has been proposed for cryptographic applications. The retina features are extracted by using the algorithm of glowworm swarm optimization (GSO) that provides promising results through the experiments using the standard retina databases. Additionally, in order t

With the wide developments of computer applications and networks, the security of information has high attention in our common fields of life. The most important issues is how to control and prevent unauthorized access to secure information, therefore this paper presents a combination of two efficient encryption algorithms to satisfy the purpose of information security by adding a new level of encryption in Rijndael-AES algorithm. This paper presents a proposed Rijndael encryption and decryption process with NTRU algorithm, Rijndael algorithm is widely accepted due to its strong encryption, and complex processing as well as its resistance to brute force attack. The proposed modifications are implemented by encryption and decryption Rijndael

With the wide developments of computer science and applications of networks, the security of information must be increased and make it more complex. The most important issues is how to control and prevent unauthorized access to secure information, therefore this paper presents a combination of two efficient encryption algorithms to satisfy the purpose of information security by adding a new level of encryption in Rijndael-AES algorithm. This paper presents a proposed Rijndael encryption and decryption process with NTRU algorithm, Rijndael algorithm is important because of its strong encryption. The proposed updates are represented by encryption and decryption Rijndael S-Box using NTRU algorithm. These modifications enhance the degree of

The aim of robot path planning is to search for a safe path for the mobile robot. Even though there exist various path planning algorithms for mobile robots, yet only a few are optimized. The optimized algorithms include the Particle Swarm Optimization (PSO) that finds the optimal path with respect to avoiding the obstacles while ensuring safety. In PSO, the sub-optimal solution takes place frequently while finding a solution to the optimal path problem. This paper proposes an enhanced PSO algorithm that contains an improved particle velocity. Experimental results show that the proposed Enhanced PSO performs better than the standard PSO in terms of solution’s quality. Hence, a mobile robot implementing the proposed algorithm opera

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a local

Abstract

Much attention has been paid for the use of robot arm in various applications. Therefore, the optimal path finding has a significant role to upgrade and guide the arm movement. The essential function of path planning is to create a path that satisfies the aims of motion including, averting obstacles collision, reducing time interval, decreasing the path traveling cost and satisfying the kinematics constraints. In this paper, the free Cartesian space map of 2-DOF arm is constructed to attain the joints variable at each point without collision. The D*algorithm and Euclidean distance are applied to obtain the exact and estimated distances to the goal respectively. The modified Particle Swarm Optimization al