Arman Process Journal (APJ)

Abstract With the increasing development of technology and the expansion of the use of the Internet, botnets are considered as one of the most important security threats in the digital space. Botnets are networks of infected devices controlled by attackers and used for various purposes such as sending spam, DDoS attacks, and stealing sensitive information. Considering the increasing trend of using botnets, it is very important to detect and prevent their activity. The spread of communication, resource sharing, curiosity, earning money, gathering information and gaining resource capacity are motivations for creating botnets. In addition to these, political, economic and military motives should also be added. Our method has the ability to detect known and unknown botnets that use this method. Our goal in this paper is to present an innovative method to detect botnets using failed response analysis and neural network. In this method, botnets are detected based on failed responses or NXDomain in each host. This feature increases the accuracy of detection in small and medium networks. This method has been tested in networks infected with Konfiker and Kraken botnets and the information obtained from it has been analyzed using neural networks. The evaluation results show the good performance of this method in botnet detection.

Abstract The rapid expansion of the Internet and the cost-effective growth of key technologies enable it to revolutionize information technology and create unprecedented opportunities for the development of large-scale distributed applications. At the same time, there is a growing concern about the security of web-based businesses, which are rapidly proliferating on the Internet. Implementing electronic business systems and entering the field of electronic commerce are technical and social solutions to facilitate communication and easy access to information. But the increase of business dependence on information systems has resulted in damages, threats and technical and non-technical measures to violate the principles of business information security, which is the main challenge and problem of organizations and the subject of this article. To achieve dynamic e-businesses, we must implement security in it under fundamental frameworks so that we can use it as a sustainable example of business. A correct understanding of security risks and risks, especially the risks that exist in the executive frameworks of electronic businesses, help a lot in the design and architecture of a safe and efficient infrastructure. In this article, we are going to examine the security aspects of electronic businesses.

Abstract The portable video-on-demand system is a video compression system for transmitting video in a wireless network, it is sent in smaller packets and uses Wi-Fi and Bluetooth standards to connect to mobile devices and tablets at any time and place. There is a method for transmitting video in a portable wireless network. Here, we use the VQ pyramid decoding method, a video compression method that we used to transmit video in wireless networks with limited bandwidth. This method is able to reduce the amount of data and preserve In this method, the video quality is divided into two small frames. This algorithm uses a set of quantized codes to select the closest code to each block of the frame, and then this code is used as a representative of the block in the frame. The method instead of transmitting all the block information, only the block representative code information is transmitted, which reduces the data volume. In fact, VQ pyramid decoding is an efficient method for video compression and transmission in wireless networks, which reduces the data volume and maintains the video quality. It provides the possibility of transmitting and watching high-quality video in a network with limited bandwidth. Overall, literature reviews in this field analyze and examine these techniques and their applications for optimizing video systems, and they aim to find the best methods for compressing videos with high quality at low bit rates.

Abstract In the digital age we are witnessing, artificial intelligence (AI) has emerged as a key factor in the evolution of e-commerce. This article examines how to use AI to improve the experience of using data-driven web apps and combine it with artificial intelligence packages, as well as a more dynamic user interface with smart and dynamic parts and create a competitive advantage for businesses. For this research, we used forms that are designed dynamically and collect data from the user, and finally analyze the data and display it in the form of charts and graphs. Our findings show that AI has been able to Increase accuracy of predictions. Using data and advanced algorithms, AI is able to predict customer behavior and market demand with high accuracy. Automation of processes and reduction of the need for manpower has reduced operating costs. Recommender systems and intelligent customer support have led to faster and more personalized service. It has emerged as a powerful e-commerce tool that can help businesses succeed in today's competitive marketplace. As technology continues to advance, we can expect AI to play an even greater role in this industry.

Abstract  With the expansion of the cyber world, issues are directly and indirectly entered into this area and are studied; The Internet of Things and Blockchain are two developing technologies that create opportunities for new topics including smart contracts. A smart contract is a computer protocol based on blockchain technology to create or improve a contract. In these contracts, valid transactions are defined as programmed code and applied automatically without the need for intermediaries. In this research, we will first introduce the Internet of Things, blockchain, and then smart contracts created from the combination of these two technologies and the advantage of making smart contracts. The method of this research is descriptive and data analysis. The Internet of Things, which is undergoing growth in the IT industry; It provides limitless opportunities for smart contracts; So, in the absence of IoT sensors, these contracts have limited potential. Of course, the technical challenges of smart contracts are a set of programs that are self-verifying, self-executing, and tamper-resistant. By integrating blockchain technology, the smart contract is able to perform a task in real time at a low cost and provide a higher degree of security. Examining a few scenarios in real life shows; The technical challenges of smart contracts are very few along with the advantages of using these contracts. By identifying and analyzing the performance measurement of smart contracts, significant results are obtained for the development of these contracts.

Abstract One of the most important aspects of customer relationship management is discovering the customer's purchasing behavior pattern. The organization can act by defining more precise marketing strategies to attract similar customers. In today's competitive world, accurate knowledge of customers and the ability to respond to their needs is critical to the success of organizations. With recent advances in data mining and big data analysis, organizations are now able to use more sophisticated methods to segment customers and better understand their behavior. The novelty, frequency and financial model (RFM) as one of the prominent models in this field, provides the possibility of dividing customers based on their value for the organization. In this thesis, a customer segmentation scheme is presented using fractal clustering and AVOAGA optimization method, which is a combination of two optimization methods, African vulture and genetic method. The simulation of the proposed design was done in the Python environment and using the standard data set containing RFM of customers. Based on the results obtained from the simulation, the proposed design is improved in both compactness and dispersion indices compared to the basic design.