Journal of Cyber Security in Computer System

Design and Implementation of Social Media Sentiment and Engagement Pattern using VADER and TextBlob

2026-07-23T09:18:12+00:00

The rapid growth of social media and related platforms generates vast amounts of user-created content. This extensive information contains significant material that is shared on social media for specific purposes, and in response, the public expresses their opinions through likes, dislikes, shares, comments, and various reactions to these posts. This study aims to investigate the sentiment and engagement aspects associated with this information, as well as the genuine opinions of the public regarding these posts. It is a challenging task due to the unstructured nature of the content, the high dimensionality of public inputs, and the complexity of the information. Traditional analytical methods and two-dimensional visualization techniques often struggle to effectively uncover hidden patterns and relationships within large-scale social media datasets. This study introduces a conceptual framework for analyzing sentiment and engagement trends on social media by employing three-dimensional visual analytics and machine learning approaches. First, social media data is gathered and processed to eliminate noise, duplicates, and non-essential information. Sentiment-related characteristics are obtained using VADER and TextBlob, while engagement features are calculated based on interaction metrics including likes, shares, comments, and reposts. To tackle the difficulties posed by high-dimensional data, Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP) are used to create compact three-dimensional representations that maintain essential structural information. Additionally, clustering algorithms such as K-Means and DBSCAN are employed to detect clusters of posts that share similar sentiment and engagement attributes. Techniques from network analysis are applied to explore interaction patterns, pinpoint influential users, and uncover online communities. The resulting three-dimensional visualizations enable an intuitive examination of user behavior, sentiment distribution, and engagement dynamics across social media platforms.

QuantumShield: A BB84-Driven Post-Quantum Cryptographic Framework for Secure Data Encryption with Hybrid Key Distribution

2026-06-20T05:40:16+00:00

Contemporary public-key schemes such as RSA and Elliptic Curve Cryptography face an existential threat from quantum algorithms that solve their underlying hard problems in polynomial time. Although standards bodies have begun selecting post-quantum replacements, few working prototypes exist that bring these ideas into an accessible, interactive format. This paper describes QuantumShield, a browser-based encryption tool that unifies three complementary defence layers within a single pipeline. First, the BB84 quantum key distribution protocol is faithfully simulated through IBM’s Qiskit framework using a chunked-circuit approach, producing a 256-bit key after basis sifting, error-rate sampling, and SHA-256 privacy amplification. Second, the derived key drives AES-256-GCM authenticated encryption for payload protection. Third, a simplified Learning With Errors lattice signature provides post-quantum integrity verification over the ciphertext. Experiments across qubit counts from 64 to 1024 show a basis-match rate holding at the theoretical 50 %, zero quantum bit error rate in the noise-free simulator, and linear time growth averaging 90 ms per 20-qubit chunk. All 45 validation tests passed. QuantumShield runs entirely on commodity hardware and requires no cloud credentials, offering a cost-free reference platform for quantum-safe cryptography research and instruction.

Architecture and Development of a Comprehensive Software-based IoT Security Auditing Framework: A Single System Simulation Model

2026-05-11T11:37:45+00:00

IoT devices have become extensively utilized in the dynamic internet landscape. While there has been a rapid expansion in the deployment of IoT technology, proper security measures have failed to keep pace. This study intends to identify the security vulnerabilities in the IoT technology using a software-based auditing approach. This study seeks to analyze the effectiveness of real-time security scanning and password entropy auditing through the use of a single system simulation (SSS) model. In this research, a simulated environment will be established to test the security vulnerabilities of the IoT technology using a software tool based on Python and FastAPI for identifying vulnerable network services like FTP, SSH and HTTP. The results reveal that non-intrusive scanning proves highly effective in the detection of insecure network services and ports. Moreover, it can be observed that password entropy auditing, which includes password strength analysis, proves to be a useful method for detecting weak passwords that may be subject to dictionary attacks. It can also be noted that the extensive adoption of secure protocols and hard passwords must be ensured at all costs regarding IoT technology. This study not only highlights the importance of ethical hacking for education and network security but also sheds light on the IoT vulnerabilities.

Movie Ticket Booking System for Multiplex Theatre: A Conceptual Framework for Design, Architecture, and User Experience

2026-07-21T05:25:23+00:00

With the blistering development of digital commerce and mobile technology, the nature of consumer interaction with the entertainment service has directly changed, and the presence of online movie ticket booking systems is an inseparable part of the contemporary multiplex theatre ecosystem. The conceptual paper has provided an overall framework for the design, architecture, and evaluation of a movie ticket booking system customized to meet the operational complexities of multiplex theatres. The paper methodically explores the functional and non-functional requirements of such a system, offers a layered software architecture which includes front-end user interfaces, back-end business logic and persistent data storage, and explores important subsystems such as seat reservation management, payment gateway integration, user authentication, and notification services. The principles of user experience design, the concurrency control mechanism to enable simultaneous seat selection, and the safety of data are given special attention. The paper also discusses scalability initiatives, microservice breakdown and how cloud infrastructure can support peak load in high-demand film releases. Issues like prevention of ticket touting, dynamic pricing and accessibility of the various user groups are critically examined. Through the combination of the knowledge in software engineering, information systems, and human-computer interaction research, this paper presents a conceptualized holistic advice that could be valuable to practitioners in creating a strong, user-friendly, and commercially viable multiplex ticket booking system.

Rendering Techniques through Images in Computer Graphics

2026-06-01T06:09:08+00:00

The field of computer graphics is currently undergoing a transformative shift from traditional explicit geometric modeling toward data-driven neural implicit representations. This review paper provides an extensive and structured survey of contemporary image-based rendering (IBR) techniques, with a primary focus on the evolution and diversification of neural radiance fields (NeRF). Historically, IBR relied on complex geometric proxies, multi-view stereo, and depth-map interpolation, which frequently struggled with non-Lambertian surfaces, transparency, and thin structures. The emergence of coordinate-based neural networks has redefined this paradigm by encoding 3D scenes as continuous volumetric functions of spatial position and viewing direction. This study presents a meticulous analysis of thirty influential research contributions that have shaped the modern landscape of neural rendering. These works are categorized based on their technical innovations, including multi-scale anti-aliasing, hash-grid acceleration, tensor factorization for memory efficiency, and the modeling of non-rigid deformations in dynamic environments. By synthesizing findings from these thirty pivotal papers, this review highlights significant milestones in achieving photorealistic novel view synthesis, reducing computational latency for real-time applications, and automating the reconstruction of large-scale outdoor scenes. The study concludes by situating these advancements within the broader context of AR/VR, digital twins, and autonomous systems, offering a comprehensive look at how neural rendering has established a new gold standard for immersive visual computing.