موضوع امنیت داده‌ها واطلاعات در اینترنت و شبکه‌های اجتماعی در سال‌های اخیر جدی‌تر و فراگیرتر شده است. رمزنگاری برای حل مشکلات امنیتی استفاده می‌شود. با این حال، صرف رمزگذاری پیام نمی‌توانداهداف موردنظر را برآورده کند. زیرا کنترل دسترسی بر پیام‌های رمزگذاری شده دربرخی ازبرنامه‌ها مورد نیاز است. برای دستیابی به این الزامات، از رمزگذاری مبتنی بر ویژگی(ABE) استفاده می‌شود. این نوع رمزگذاری هم امنیت و هم ساختار دسترسی را برای کاربران شبکه به طور همزمان فراهم می‌کند. رمزگذاری مبتنی بر شناسه فازی را می‌توان حالت خاص ازABEدر نظر گرفت که ساختار دسترسی آستانه را برای کاربران فراهم می‌کند. این مقدار آستانه توسط مرجع برای کاربران در مرحله تولید کلید تعیین می‌شود که همیشه ثابت است. این بدین معنی است که کاربری که برای دریافت کلید به مرجع مراجعه می‌کند، کلیدی را دریافت کرده که وابسته به این مقدار آستانه است. بنابراین، فرستنده (رمزگذار) که پیامی را برای این کاربر ارسال می‌کند، نقشی در تعیین مقدار آستانه ایفا نخواهد کرد. این مشکل شده در طرح‌های رمزگذاری مبتنی بر ویژگی با سیاست‌گذاری روی کلید(KP-ABE)نیز وجود دارد. در این مقاله،روشی ارائه می‌دهیم که بتوان یک طرحFIBEرابه نوعی تغییر دادکه برای تعیین مقدارآستانه علاوه برمرجع،فرستنده نیزایفای نقش کرده وبار محاسباتی ومخابراتی طرح راافزایش ندهد. Manuscript profile

Nowadays, the great benefits of cloud computing have dramatically increased the number of e-banking users. Hence, the competition in the banking industry has boosted and managers need to evaluate their branches on a regular basis. To this end, this study aims to evaluate cloud-based banking systems based on the Quality of Service (QoS) attributes using the Dynamic Network Data Envelopment Analysis (DNDEA) model. The main advantage of this research is that the efficiency of cloud-based bank branches can be estimated more realistically according to their internal structure over a specific time span. To conduct the experiment, 40 bank branches in Iran are analyzed by considering between-period and divisional interactions during 2018-2019. A cloud-based bank branch is conceptualized as a set of three inter-connected divisions including capabilities, intermediate process, and profitabilities. Some outputs of sub-DMUs 2 and 3 are treated as desirable and undesirable carry-overs between consecutive periods. In addition, the cost items and QoS attributes are considered as the inputs and outputs of divisions, respectively. The results indicate that 28 bank branches were efficient and all of the inefficiencies fall in divisions 1 and 3. Moreover, the number of efficient branches has been reduced from 2018 to 2019. Manuscript profile

One of the most famous algorithms in the field of focused exploration of data mining correlation rules is the Apriori algorithm and its many developed versions. But what can be raised as a major challenge in this field is the proper application of this algorithm in the distributed environments of today's world. In this research, a parallelization-based approach is proposed to improve the performance of the Apriori algorithm in the process of exploring recurring patterns on network topologies. The proposed approach includes two major features: (1) combining the node centrality criterion and the Apriori algorithm to identify frequent patterns, (2) using the mapping/reduction method in order to create parallel processing and achieve optimal values in the shortest time. Also, this approach pursues three main goals: reducing the temporal and spatial complexity of the Apriori algorithm, improving the process of extracting dependency rules and identifying recurring patterns, comparing the performance of the proposed approach on different network topologies in order to determine the advantages and disadvantages of each topology. To prove the superiority of the proposed method, a comparison has been made between our approach and the basic Apriori algorithm. The evaluation results of the methods prove that the proposed approach provides an acceptable performance in terms of execution time criteria compared to other methods. Manuscript profile

Core vector regression (CVR) is an extension of the core vector machine algorithm for regression estimation by generalizing the minimum bounding ball (MEB) problem. As an estimator, both the kernel function and its parameters can significantly affect the prediction precision of CVR. In this paper, a method to improve CVR performance using pre-processing based on data feature extraction and Grid algorithm is proposed to obtain appropriate parameters values of the main formulation and its kernel function. The CVR estimated mean absolute error rate here is the evaluation criterion of the proposed method that should be minimized. In addition, some benchmark datasets out of different databases were used to evaluate the proposed parameter optimization approach. The obtained numerical results show that the proposed method can reduce the CVR error with an acceptable time and space complexity. Therefore, it is able to deal with very large data and real world regression problems. Manuscript profile

In this paper, some properties of $\alpha$-skew Armendariz and central Armendariz rings have been studied by variety of others. We generalize the notions to central $\alpha$-skew Armendariz rings and investigate their properties. Also, we show that if $\alpha(e)=e$ for each idempotent $e^{2}=e \in R$ and $R$ is $\alpha$-skew Armendariz, then $R$ is abelian. Moreover, if $R$ is central $\alpha$-skew Armendariz, then $R$ is right p.p-ring if and only if $R[x;\alpha]$ is right p.p-ring. Then it is proved that if $\alpha^{t}=I_{R}$ for some positive integer $t$, $ R $ is central $ \alpha $-skew Armendariz if and only if the polynomial ring $ R[x] $ is central $ \alpha $-skew Armendariz if and only if the Laurent polynomial ring $R[x,x^{-1}]$ is central $\alpha$-skew Armendariz.‎ Manuscript profile