تصميم وتنفيذ تطبيق دردشة قائم على نظام اندرويد امن من نهاية الى نهاية == Design and Implementation of an End - to - End Secure Android based Chat Application
طرائق تجميع البيانات الكفوءة باستخدام الطاقة من اجل اطالة عمر شبكات الاستشعار اللاسلكية الدورية == ENERGY - EFFICIENT DATA AGGREGATION APPROACHES FOR PROLONGING LIFETIME OF PERIODIC WIRELESS SENSOR NETWORKS
الاداء الامثل لشبكات الاستشعار اللاسلكية باستخدام نماذج نشر مختلفة == An Optimal Performance of the Wireless Sensor Networks Using Various Deployment Models
اقتراح خوارزمية هجينة للتشفير الكتلي == Proposed Hybrid Block Cipher Algorithm
تقييم الية الثقة في شبكات المركبات == Evaluation of Trust Mechanism for VANETs
تحسين خوارزمية تشفير A5/1 بالاعتماد على تقنية الترشيح لتطبيق انترنيت الاشياء == Improvement of A5/1 encryption algorithm based on filtration technique for IoT Application
طريقة تحليلية لانظمة التشفير الصوتي البايومتري == Analytical Approach of Biometric Based Voice Encryption System
تحسين نظام مقترحات هجين باستخدام خورازمية الترتيب PageRank == Hybrid Recommender System Enhancement Using Personalized PageRank Algorithm
استخدام تقنية الحساب المرن لتقييم RSA وAES == Soft Computing Technique to Evaluate RSA and AES
Author name:
فرقد حامد عبد الرحیم
Supervisor name:
ستار بدر سدخان المالكي
Abstract:
Security evaluation algorithms can be considered as one of the most important challenges in computer networks. This is because of the growing data sharing among all clients (users). Therefore, the security level evaluation aspect of cryptography systems is recently appeared to be very important.In this work, evaluations of (RSA and AES) encryption methods are carried out by using Fuzzy Inference System (FIS) and Adaptive Neuro - Fuzzy Inference System (ANFIS). The editor of MATLAB (2013) is employed in this study and it contains a hybrid ANFIS facility between the Artificial Neural Network (ANN) and Fuzzy Logic techniques.First of all, designing and programming software codes for the first encryption method (RSA) have been simulated according to its original algorithm. Consequently, executing the RSA algorithm to collect the data values is implemented for the following parameters (message length, execution time, length of key and cipher message entropy). These parameters have been considered in the proposed approaches. So, the RSA data is used as the bases of the FIS inputs. Then, all the training and testing data values have been collected from the proposed FIS and prepared to be used in the next step (the ANFIS). The number of training samples has been selected to be 100 values by executing special software programs. These values have been utilized as follows : opening the ANFIS editor; loading the training data; determining the main ANFIS parameters and training the data with the least error tolerance. Subsequently, the number of testing samples has been chosen to be also 100 values by implementing special software programs. Hence, the evaluations are observed and the characteristics of the ANFIS which attained the best tested results have been benchmarked. Similar steps to evaluate the RSA by using large key numbers are implemented except of utilizing the parameter (key length) to study the influence of the key value on security evaluations. The proposed FISSecurity evaluation algorithms can be considered as one of the most important challenges in computer networks. This is because of the growing data sharing among all clients (users). Therefore, the security level evaluation aspect of cryptography systems is recently appeared to be very important.In this work, evaluations of (RSA and AES) encryption methods are carried out by using Fuzzy Inference System (FIS) and Adaptive Neuro - Fuzzy Inference System (ANFIS). The editor of MATLAB (2013) is employed in this study and it contains a hybrid ANFIS facility between the Artificial Neural Network (ANN) and Fuzzy Logic techniques.First of all, designing and programming software codes for the first encryption method (RSA) have been simulated according to its original algorithm. Consequently, executing the RSA algorithm to collect the data values is implemented for the following parameters (message length, execution time, length of key and cipher message entropy). These parameters have been considered in the proposed approaches. So, the RSA data is used as the bases of the FIS inputs. Then, all the training and testing data values have been collected from the proposed FIS and prepared to be used in the next step (the ANFIS). The number of training samples has been selected to be 100 values by executing special software programs. These values have been utilized as follows : opening the ANFIS editor; loading the training data; determining the main ANFIS parameters and training the data with the least error tolerance. Subsequently, the number of testing samples has been chosen to be also 100 values by implementing special software programs. Hence, the evaluations are observed and the characteristics of the ANFIS which attained the best tested results have been benchmarked. Similar steps to evaluate the RSA by using large key numbers are implemented except of utilizing the parameter (key length) to study the influence of the key value on security evaluations. The proposed FISSecurity evaluation algorithms can be considered as one of the most important challenges in computer networks. This is because of the growing data sharing among all clients (users). Therefore, the security level evaluation aspect of cryptography systems is recently appeared to be very important.In this work, evaluations of (RSA and AES) encryption methods are carried out by using Fuzzy Inference System (FIS) and Adaptive Neuro - Fuzzy Inference System (ANFIS). The editor of MATLAB (2013) is employed in this study and it contains a hybrid ANFIS facility between the Artificial Neural Network (ANN) and Fuzzy Logic techniques.First of all, designing and programming software codes for the first encryption method (RSA) have been simulated according to its original algorithm. Consequently, executing the RSA algorithm to collect the data values is implemented for the following parameters (message length, execution time, length of key and cipher message entropy). These parameters have been considered in the proposed approaches. So, the RSA data is used as the bases of the FIS inputs. Then, all the training and testing data values have been collected from the proposed FIS and prepared to be used in the next step (the ANFIS). The number of training samples has been selected to be 100 values by executing special software programs. These values have been utilized as follows : opening the ANFIS editor; loading the training data; determining the main ANFIS parameters and training the data with the least error tolerance. Subsequently, the number of testing samples has been chosen to be also 100 values by implementing special software programs. Hence, the evaluations are observed and the characteristics of the ANFIS which attained the best tested results have been benchmarked. Similar steps to evaluate the RSA by using large key numbers are implemented except of utilizing the parameter (key length) to study the influence of the key value on security evaluations. The proposed FISapproach confirmed that the RSA evaluation is successfully implemented to the ANFIS editor.All the previous steps are repeated for the AES encryption method except one difference. That is, the utilized parameters here are the (message length, execution time and cipher message entropy). Basically, two key values are determined for the AES, which equals to 128 bits. Likewise the RSA, the suggested procedures are applied to the AES and the proposed FIS approach confirmed that the AES evaluation is successfully implemented to the ANFIS editor.Finally, comparisons between this study and previous work, and between the RSA and AES are established. In addition, comparisons between the evaluated outcomes of the FIS and ANFIS have been investigated by using two statistical metrics.
عنقدة الصور اعتمادا على طريقة كسورية مطورة وتنقيب المخططات == Image Clustering Based on Developed Fractal Method and Graph Mining
نظام الكشف التعاوني عن هجومات الفيضان الموزعة للحرمان من الخدمة والتعقب المستوحى من مجتمع العناكب الاجتماعية == Collaborative Detection System of DDoS Flooding Attacks and Tracing Inspired by Social Spiders Society
اخفاء المعلومات في صفحات الويب الهجينة == HYBRID STEGANOGRAPHY OF WEBPAGE
