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In the contemporary world, there is a frequent concern regarding the preservation and protection of password data. Numerous services and internet resources require specific accesses to enter their systems. When dealing with a multitude of resources and passwords, the question arises as to where and in what form to store them. Typically, software solutions, namely password managers, are employed for this purpose. The objective of this study is to enhance the efficiency of storing restricted-access information by developing an application with encryption capabilities. To achieve this goal, a review and analysis of modern password managers were conducted, revealing that existing solutions fail to meet the requirements of many enterprises, including 'OdesSeo,' a comprehensive internet marketing enterprise located in the city of Odesa. For the secure storage of restricted-access information, SHA3 encryption algorithms were chosen for employee account passwords, while AES-256 was selected for project passwords of service clients. The latter ciphers were translated into Base64 positional numeral system format. A mobile password manager application was developed and successfully implemented in the production environment of 'OdesSeo.' The increase in the efficiency of storing restricted-access information at 'OdesSeo' is measured in monetary terms, with the lower threshold being 50,000 UAH or 1,200 USD, representing the minimum necessary expenses, according to risk managers' estimates, to mitigate the consequences of information leaks or unauthorized access to the enterprise system and client projects. [ABSTRACT FROM AUTHOR]

Detection of digital image forgeries in open sources has garnered significant attention. This is attributed to the proliferation of mobile photo and video technology, the accessibility and multifunctionality of graphic editors, as well as the rise in cybercrime. Cybersecurity and/or information security aim, among other things, to ensure the integrity of digital images. Violations of the integrity of digital images can be carried out through various methods such as cloning, photo manipulation, scaling (enlarging or reducing objects), etc. Scaling detection has been the subject of several works, but often the proposed solutions prove to be ineffective for scaling down or scaling with a coefficient less than one. The goal of this work is to detect scaling of digital images by developing a method based on the analysis of high-frequency components of discrete cosine transformation. Experimental findings indicate that when a portion of the image is reduced, the high-frequency coefficients of the discrete cosine transformation increase. A threshold value was successfully established, allowing the separation of scaled portions of the digital image from the original ones. Based on the conducted research, a scaling detection method was developed, with an error rate of 7% and 14% for types 1 and 2 errors, respectively. The developed method proves effective for scaling objects by at least threefold and high-contrast scaled objects. However, when reducing a portion of the image by half, the error rate for type 1 errors increases to 30%. Further research by the authors aims to reduce the limitations of the developed method. [ABSTRACT FROM AUTHOR]

The main focus of the study is the need for a modern and efficient system of document exchange between teachers and students. Changes in the educational environment, structure and format of the educational process as a result of the spread of technology and, in particular, the COVID-19 pandemic require the latest solutions. The effectiveness of the educational process and its manageability largely depend on the speed, reliability and convenience of information exchange between participants in the educational process. Educational institutions exchange huge amounts of information on a daily basis, from moving homework to final exams. Without modern digital technologies, this process can be not only slow, but also accompanied by losses, errors and delays, so the need for a document exchange system is relevant today. In addition, information security is a major anchor for the implementation of such systems, as document exchange involves the processing and transmission of sensitive information that must be protected from unauthorized access and misuse. In response to these challenges, efforts have been focused on developing a document exchange system that uses modern encryption algorithms for secure data transmission. This research and development has acquired not only academic but also practical significance, as it fills the gap between the requirements for modern e-learning and the real capabilities of educational institutions in the exchange and protection of information. The result of the conducted research was the development of a system that uses modern digital technologies, such as two-factor authentication, the AES encryption protocol, and the PBKDF2 hashing algorithm. The developed document exchange system is a practical contribution to the field of educational technologies, which opens new horizons for automation, efficiency and security in the field of document exchange in education. [ABSTRACT FROM AUTHOR]

The study of information and psychological security raises a number of issues related to ensuring human security and preserving human health in connection with various types of information threats: targeted information influence on the population through the media, the Internet, which can lead to negative socio-political consequences; incomplete realisation of citizens' rights to receive and exchange reliable information; provoking social, ethnic, religious tensions through the activities of certain media; manipulation of Predicting the results of information and psychological influence is an important and urgent problem not only on the scale of an individual, but also for the national security of the state. The purpose of this paper is to increase the efficiency of forecasting information and psychological influence by modifying the model of information and psychological influence based on the analysis of influence factors. The paper reviews existing models for predicting the results of influence, from which a model was selected for modification to improve the forecasting results. The result of the work is a methodology that takes into account the channels of information and psychological influence, the emotional component of memes and the methods of counteraction that can be used by the opposing side, which allowed to create a theoretical basis for further practical research. The results obtained can be used to predict the information and psychological impact on society and/or to choose methods of counteracting this impact to reduce its consequences. [ABSTRACT FROM AUTHOR]

It is obvious that there can be no security without information security. Staying in one or another in formation space changes consciousness, forces people to commit crimes of varying degrees of severity, or to justify supporting criminals. An important tool in the violation of information security is propaganda, which does not disdain any methods to achieve the goal, including using fake photo, video, and audio files to realize informational and psychological influence on society. The methods of dealing with such cases are comprehensive and complex in nature. Among them, the methods of establishing the truth of digital content or proving that this or that in formation is fake play an important role. When forging digital files, in particular, digital images, post-processing methods such as blurring, multiplicative noise, etc. are often used. Identifying these types of post-processing is currently not a solved task, although it has certain successes. The purpose of this work is to improve the detection efficiency of digital image processing by developing a blur detection method and a multiplicative noise detection method. A computational experiment was conducted, as a result of which it was established that the discrete cosine transformation is a convenient and effective tool for detecting Gaussian blur and multiplicative noise. Blur ring reduces the value of high-frequency DCP coefficients, while multiplicative noise increases them. At the same time, the raw image has high-frequency coefficients within a certain norm. In the work, it was possible to single out threshold values that allow recording deviations from the norm in one direction or another, on the basis of which a method for detecting blur ring and a method for detecting multiplicative noise, based on the analysis of high-frequency coefficients of DCP, was developed. [ABSTRACT FROM AUTHOR]

Deep learning is an effective and useful technique that is widely used in a variety of fields, including computer vision, machine vision, and natural language processing. Deepfake uses deep learning technology to manipulate images and videos of a person that people cannot distinguish from real ones. Deepfake is usually created in two ways. The first way is through a generative competition network, or GAN, which uses two separate neural networks that work together to learn how to study the characteristics of real images so that they can create compelling photo fakes. The second way is with an artificial intelligence (AI) algorithm called an encoder, which works by running pictures of two people's faces through an encoder to find similarities between those pictures and running a decoder that takes a face image and swaps them. The achievements in the field of Deepfake are equally impressive and disturbing. In someone else's hands, this technology can be used to spread misinformation and undermine public confidence almost as a sci-fi type of identity theft, when you can get anyone to say anything. In this regard, it can be stated that the task of Deepfake detection is very important and requires the application of new research in this area, the development of new algorithms for Deepfake detection and improvement of existing methods. Therefore, the purpose of this work is to create a system for detecting violations of the integrity of media files made by Deepfake technology. The work selected the neural network and its training on a specially created basis, which made it possible to detect Deepfake in both digital images and digital videos. [ABSTRACT FROM AUTHOR]

At a time when the use of digital content in all spheres of life is constantly growing, the ability to verify the authenticity of digital files, in particular digital images, is extremely important in protecting information from integrity violations. In the information war, photo fakes are always used to achieve certain, often criminal, goals. Both society as a whole and individuals must take care of information security and protect their information space from unverified information. Modern methods of detecting violations of the integrity of graphic information to some extent address some issues of information security, however, they are not universal and often require development, improvement, additional research and so on. Thus, existing methods for detecting such a common method of image falsification as scaling are effective only in cases where the falsified part is enlarged, however, when reducing part of the image, they are not effective. Moreover, in open printing the problem of detecting reduced scalable parts of the image is not covered. Therefore, the aim of this work is to increase the efficiency of scaling detection as digital image falsification by developing an algorithm for detecting scaling with a negative coefficient. In this paper, the method of error level analysis is adapted to detect reduced parts of the digital image. The efficiency of the adapted method in terms of errors of the 1st and 2nd kind was: errors of the 1st kind - 2%, 2nd kind - 7%. In addition, it has been found that this method is also effective in detecting simultaneously scalable (reduced) and moved parts of a digital image. This method detects artifacts (errors) in the digital image, which occur when reducing its part - the falsified area has a higher high-frequency component than the rest of the image, which is amplified under the influence of compression after saving the falsification in a lossy format. [ABSTRACT FROM AUTHOR]

Today, more and more actively forces us to take care of our information security. Events in the world and in Ukraine, information, hybrid wars, cybercrimes are what have become our everyday reality, and what prompts us to look for new and improve existing methods and means of information protection. One of the issues of information protection is the protection of graphic content from violations of its integrity. Violation of the integrity of digital images can be done with a wide variety of graphic editor tools. In particular, such a tool of the Adobe Photoshop graphic editor "patch" is a convenient way to falsify a photo, which is currently not paid attention to in the open press. Therefore, the need to identify this tool became the basis for the experiments described in this article. The purpose of this work is to improve the effectiveness of detecting fake photos made using the Adobe Photoshop tool "Patch" by developing an algorithm. In the work, a computational experiment was carried out using 100 digital images, which were processed with the "patch" tool. Based on the computational tool, an algorithm was developed that proved to be effective in cases where the image after falsification is saved in lossy and lossless formats. In most cases, it was possible to detect the presence of a violation of integrity in the case when it really took place, and to establish the fact of the absence of processing with the "patch" tool, when it really was not. [ABSTRACT FROM AUTHOR]

It is said that the best password manager is our brain. This statement makes sense, but sometimes our brain does not cope, we have to use external resources. The number of passwords per user is growing every year: new social networks, new bank accounts, new registrations in various services, accounts on various services (television, music, Internet service providers, etc.). According to the rules of information security, using the same password for different client services is not rational, because if attackers can, for example, choose a password for your email, they will try to apply it to your other applications such as Internet banking and more. Modern man understands that each service needs its own unique password. The password must be strong, contain a certain number of characters, where among the numbers and letters the reliability of the password is increased by special characters and case changes. It's hard to remember. But remembering one password is beyond the power of most of us. Choosing a convenient and reliable password manager is not an easy task. You really have to trust the service. In the end, it is he who will store your confidential information. In this paper, two dozen password managers were tested and eleven were selected, which are the best in terms of functionality, security and convenience. However, each of the well-known managers does not take into account the individual characteristics of users and needs additions according to their needs. Therefore, the creation of software for storing passwords in encrypted form is relevant. Encrypted passwords can be accessed through the one password you need to remember. Such relationship software was created in this paper, taking into account the needs of corporate and private use. [ABSTRACT FROM AUTHOR]