API as a way to interact with social networks

In the realities of the pandemic, chat bots have become indispensable helpers. They do not need a lot of resources and constant human control. A method of interacting with social networks through a specialized software interface Web API, which is the basis of the REST architecture, is considered. The basic structure of requests for receiving and sending data to servers is presented. On the example of the implementation of a chatbot for vk.com, capable of automating a dialogue with users, the main design stages are presented, including the requirements for the implementation and operation mode based on the client-server architecture, implementation and testing. The project server is implemented on a Raspberry Pi4 single-board computer. Demonstrated code for performing basic queries and implemented a Long Polling approach to continuously track and distribute user messages. Methods were formed to obtain the necessary resources from the server, to declare a new resource on the server, to update information on the server, and to delete certain objects from the database. The result was a patented software product "Intelligent assistant of VSUIT for social networks".

A possible review by the European ministry of education in 2050—by a reluctant manager of Europe’s path towards educational dependency

Murat Adam is head of policy and curriculum for the European ministry of education. Political pressure is rising. Media channels across the European federation are labeling the continent as the most recent member of the education periphery. In Mr Adam’s world, curricular authority transpires from the big 3, the North American Union (NAU), China, and Russia. Credibility and endorsement are educational currencies—institutional capital as Bourdieu once defined it, reigns. Mr Adam’s battle is already lost, member states of the European federation have lost their educational means of production, but he cannot afford to admit that. European teachers’ credentials increasingly force graduates into care taking jobs at digital day cares. These are a response to US teachers’ and practitioners’ revolts of the late 20s, linked to perceived multisensory impoverishment of digitally schooled children. Just like in South Asia, Africa, and South America, digital day cares merely provide the digital and social framework and setup K-12 students to listen to internationally accredited professionals teach from China, Russia, and the NAU. Day and night shifts are common. He knows that the European federation lost the contest, by the time it decided not to invest into its own internet infrastructure. The educational first world’s curricular authority would not have been possible without the three nations’ proprietary server architecture, which commodified bandwidth and connectivity. The internet of the past is nothing more than a front for the three de-facto mutually exclusive digital ecosystems, provided by China, the NAU, and Russia.

BrainShield: A Hybrid Machine Learning-Based Malware Detection Model for Android Devices

Android has become the leading operating system for mobile devices, and the most targeted one by malware. Therefore, many analysis methods have been proposed for detecting Android malware. However, few of them use proper datasets for evaluation. In this paper, we propose BrainShield, a hybrid malware detection model trained on the Omnidroid dataset to reduce attacks on Android devices. The latter is the most diversified dataset in terms of the number of different features, and contains the largest number of samples, 22,000 samples, for model evaluation in the Android malware detection field. BrainShield’s implementation is based on a client/server architecture and consists of three fully connected neural networks: (1) the first is used for static analysis and reaches an accuracy of 92.9% trained on 840 static features; (2) the second is a dynamic neural network that reaches an accuracy of 81.1% trained on 3722 dynamic features; and (3) the third neural network proposed is hybrid, reaching an accuracy of 91.1% trained on 7081 static and dynamic features. Simulation results show that BrainShield is able to improve the accuracy and the precision of well-known malware detection methods.

A Framework for Migration of SOA based Applications to Microservices Architecture

This Distributed systems have evolved rapidly as the demand for independent design, and deployment ofsoftware applications has increased. It has emerged from the monolithic style of client-server architecture toservice-oriented architecture, and then to the trending microservices. Monolithic applications are difficult toupdate, maintain, and deploy as it makes the application code very complex to understand. To overcome the designand deployment challenges in monolithic applications, service oriented architecture has emerged as a style ofdecomposing the entire application into loosely coupled, scalable, and interoperable services. Though SOA hasbecome popular in the integration of multiple applications using the enterprise service bus, there are fewchallenges related to delivery, deployment, governance, and interoperability of services. Additionally, the servicesin SOA applications are tending towards monolithic in size with the increase in changing user requirements. Toovercome the design and maintenance challenges in SOA, microservices has emerged as a new architectural styleof designing applications with loose coupling, independent deployment, and scalability as key features.

Healthchain: A Privacy Protection System for Medical Data Based on Blockchain

Recently, with the great development of e-health, more and more countries have made certain achievements in the field of electronic medical treatment. The digitization of medical equipment and the structuralization of electronic medical records are the general trends. While bringing convenience to people, the explosive growth of medical data will further promote the value of mining medical data. Obviously, finding out how to safely store such a large amount of data is a problem that urgently needs to be solved. Additionally, the particularity of medical data makes it necessarily subject to great privacy protection needs. This reinforces the importance of designing a safe solution to ensure data privacy. Many existing schemes are based on single-server architecture, which have some natural defects (such as single-point faults). Although blockchain can help solve such problems, there are still some deficiencies in privacy protection. To solve these problems, this paper designs a medical data privacy protection system, which integrates blockchain, group signature, and asymmetric encryption to realize reliable medical data sharing between medical institutions and protect the data privacy of patients. This paper proves theoretically that it meets our security and privacy requirements, and proves its practicability through system implementation.

CONSTRUCTION OF A MODULAR STRUCTURE OF AN AUTOMATED SYSTEM FOR INTEGRATING SUPPORT FOR THE PROTECTION OF STRATEGICALLY IMPORTANT RESOURCES OF A TRANSPORT ENTERPRISE

The purpose of the scientific work is to build a scheme for the interaction of modules of an automated system for integrated protection of strategically important resources of an enterprise, in particular, a transportation industry enterprise. To ensure a high efficiency of the presented system, efficient allocation between the modules is necessary for the protection functions. Within the framework of this task, the article presents sets of functions for each security module. The outstanding feature of the work is the proposed scheme of optimal interaction of the modules of the automated system of integrated protection of strategically important resources of the enterprise. The article considers the mechanism of isolation of "affected" resources (and modules) of the main automated control systems of a transportation enterprise, consisting of the sequential execution of the functions of forming "affected zones and quarantine", the function of redirecting datastream. The paper presents a structural diagram of the interaction of modules of an automated system for integrated protection of strategically important enterprise resources, sets of functions for each module are formed, a scheme for ensuring isolation of "affected" resources is presented, the main difficulties of implementing an automated system are described, in particular, the features of its implementation at the transportation industry enterprise connected with the client-server architecture of the main AS, a number of additional organizational and technical measures for protecting strategically important enterprise resources are proposed.

Distributed Architecture for an Integrated Development Environment, Large Trace Analysis, and Visualization

Integrated development environments (IDEs) provide many useful tools such as a code editor, a compiler, and a debugger for creating software. These tools are highly sophisticated, and their development requires a significant effort. Traditionally, an IDE supports different programming languages via plugins that are not usually reusable in other IDEs. Given the high complexity and constant evolution of popular programming languages, such as C++ and even Java, the effort to update those plugins has become unbearable. Thus, recent work aims to modularize IDEs and reuse the existing parser implementation directly in compilers. However, when IDE debugging tools are insufficient at detecting performance defects in large and multithreaded systems, developers must use tracing and trace visualization tools in their software development process. Those tools are often standalone applications and do not interoperate with the new modular IDEs, thus losing the power and the benefits of many features provided by the IDE. The structure and use cases of tracing tools, with the potentially massive execution traces, significantly differ from the other tools in IDEs. Thus, it is a considerable challenge, one which has not been addressed previously, to integrate them into the new modular IDEs. In this paper, we propose an efficient modular client–server architecture for trace analysis and visualization that solves those problems. The proposed architecture is well suited for performance analysis on Internet of Things (IoT) devices, where resource limitations often prohibit data collection, processing, and visualization all on the same device. The experimental evaluation demonstrated that our proposed flexible and reusable solution is scalable and has a small acceptable performance overhead compared to the standalone approach.

Data Reduction of Digital Twin Simulation Experiments Using Different Optimisation Methods

The paper presents possible approaches for reducing the volume of data generated by simulation optimisation performed with a digital twin created in accordance with the Industry 4.0 concept. The methodology is validated using an application developed for controlling the execution of parallel simulation experiments (using client–server architecture) with the digital twin. The paper describes various pseudo-gradient, stochastic, and metaheuristic methods used for finding the global optimum without performing a complete pruning of the search space. The remote simulation optimisers reduce the volume of generated data by hashing the data. The data are sent to a remote database of simulation experiments for the digital twin for use by other simulation optimisers.