No. 19/2024

Online archive of Computer Science and Mathematical Modelling

No. 19/2024

1. Jakub Grątkiewicz, Rafał Kasprzyk - Memes as an inconspicuous tool in information warfare

   Pages: 5 - 13
   Abstract: Memes, in the form of images, phrases or short videos, are an important and inconspicuous source of information in the Internet age. Their simplicity and popularity make them a potential tool in information warfare, capable of producing certain effects in society. The article presents memes as information weapons, analyzing the process of their creation and distribution. Reference is made to Richard Dawkins' meme theory and the theory of reflexive control to explain how memes can influence the decisions and perceptions of audiences. The example of the “Disaster Girl” meme and its variations were presented, illustrating the ability of memes to replicate and evolve. A classification of memes in terms of the information they convey was made, pointing out their potential to shape public opinion and emphasizing the subjective nature of their reception.
   Keywords memes theory, disinformation, information warfare
   Full article: 5_13_jg_rk_memes_csmm_19_2024.pdf
2. Dominik Kania, Piotr Górny - Assessing the security status of systems using the OAuth 2.0 authorization protocol

   Pages: 15 - 23
   Abstract: The article presents an analysis of the security of systems using the OAuth 2.0 protocol. It is an authorization protocol widely used in websites, including the largest in the world. It is characterized by high complexity and complicated operation. However, when used correctly, it provides significant convenience for users in sharing data with web applications from other websites. This describes specialized tests that were conducted to identify weaknesses in the basic OAuth 2.0 implementation. Based on these tests, the threats and risks associated with inaccurate implementation were identified, along with a presentation of their potential effects.
   Keywords authorization, protocol, vulnerability
   Full article: 15_23_dk_pg_assessing_csmm_19_2024.pdf
3. Patryk Serafin - Modern web technologies – frameworks, advantages, disadvantages and optimal applications

   Pages: 25 - 34
   Abstract: Modern web applications leverage a variety of frontend and backend technologies to deliver scalable, secure, and high-performance digital experiences. This paper examines key web development frameworks, highlighting their advantages, disadvantages, and optimal use cases. Frontend frameworks such as React, Angular, and Vue.js are analyzed in terms of interactivity, modularity, and scalability, while backend solutions like Django, Node.js, Flask, and Spring Boot are evaluated for security, performance, and data management capabilities. Additionally, the paper explores technology selection criteria based on application complexity, real-time processing requirements, and scalability needs. Special attention is given to security and performance considerations, emphasizing best practices for mitigating vulnerabilities and optimizing resource efficiency. The study concludes with insights into emerging trends in web development, including microservices, serverless computing, and AI-driven applications. By providing a structured comparison of modern web technologies, this paper serves as a guide for developers and businesses seeking to make informed decisions in selecting the right stack for their specific requirements.
   Keywords Web applications, frontend frameworks, backend frameworks
   Full article: 25_34_pserafin_modernweb_csmm_19_2024.pdf
4. Rafał Wasiluk - Content-based image similarity measurement grounded on information retrieved by semantic segmentation algorithms

   Pages: 35 - 43
   Abstract: The purpose of this article is to present a novel approach for recording information contained in an image in a structured form and performing image similarity assessment with use of these data structures. The solution presented in this document relies on an analysis of results produced by pre-trained semantic segmentation algorithms. These outcomes can be transformed to a set of vectors representing some characteristics of each class of objects detected in the provided image. These data structures can contain meaningful information about algorithm detections, such as the object’s position on the image, the object’s size compared to the overall image size or the object’s dominant colors, etc. Vectors prepared as described previously can be further compared with other image embeddings using many mathematical tools like distance measures. Moreover, the approach described in this article allows the user to define a value of weight tied to each characteristic. This provides the ability to make a subset of features more important than others and have a greater impact on the final value of image similarity.
   Keywords image similarity, semantic segmentation, vector image representation
   Full article: 35_43_rwasiluk_contentbasedimage_csmm_19_2024.pdf