International Journal of Computer and Information Technology
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Visualization of Prediction of The Spread of Covid-19 in Indonesia using Cellular Automata
Get PDFThe first case of COVID 19 was detected in Indonesia in early March 2020. One way to assist the government in making decisions to deal with COVID-19 is to create a map of the distribution of COVID-19 patients based on which can only be accessed by people who have an interest through the website. The data used in this study is the period, location, total cases. After getting the data, the data is then processed to get weekly rules. After getting the weekly rules, the data is entered into the calculation of the Moore scheme to get the prediction results for the next week. Then the prediction results are poured in the form of a map. The prediction process using CA neighbors is carried out using Moore\u27s formula, a formula that applies the adjacent neighbors of 8 neighbors. The accuracy level of Cellular Automata with Moore\u27s neighbors reaches 431.1466353% using MAPE. The error value in the Cellular Automata method is quite high due to several factors that make the prediction results with the original data results different, but this method can be used to research cases of covid 1
Secured Personal Notes Application using PlayFair Cipher 8 x 8 Matrix
Get PDFSecured personal notes application is a mobile application that allows a person to secure his personal and confidential information by storing it in the application after encrypting the data. This application involves complex encryption algorithms which keeps user data secured. Traditional notes applications allow users to barely have a password for the application which does not provide security at the higher level. So, in this application users are allowed to encrypt their personal information in order to provide high level security by entering a key which the user alone knows
Improving Smart Healthcare based on the Self-management Concept
Get PDFThe smart healthcare concept is new and interdisciplinary knowledge in the modern world, and it has not been a long time since its emergence and is also important from a management point of view. The electronic contexts can have several benefits as well as real-time responsiveness for patients in hospital. Due to the growth of smart healthcare in developed cities as well as megalopolises, management of this field has also faced several challenges. With the purpose of introducing smart healthcare characteristics as well as the self-management concept, this research has also been able to investigate privacy in real-time responsiveness and users’ loyalty to improve smart healthcare management. This study is conducted to improve smart healthcare based on the self-management concept and identify factors with priority. Findings have shown smart technologies, monitoring devices, and privacy had quite significant factors in the findings of this research
Overcoming the Challenge of Non-Optimal AP Selection in Wi-Fi Roaming
Get PDFThis paper addresses the critical issue of non-optimal Access Point (AP) selection in wireless networks, which significantly impacts network efficiency and user satisfaction. In dynamic wireless environments, particularly those integrating Internet of Things (IoT) applications, clients often face challenges in maintaining optimal connectivity due to suboptimal AP selection and inefficient roaming. This results in degraded network performance, characterized by reduced data transfer speeds, increased latency, and higher likelihood of connection drops. The paper delves into the intricacies of client-AP connectivity, exploring the reasons behind non-optimal AP selection and the lack of efficient roaming. It employs simulation tools and analytical methodologies to offer insights into identifying, analyzing, and resolving these issues. The goal is to enhance the client-AP connectivity experience in wireless networks, ensuring that they are robust, capable, and intelligently adaptive to the dynamic movements and requirements of users. Key strategies discussed include advanced algorithms for AP selection that go beyond mere signal strength, implementation of fast roaming technologies like IEEE 802.11r, 802.11k, and 802.11v, and smart AP management techniques such as load balancing and dynamic channel assignment. The paper also highlights the significant improvements brought by Wi-Fi 6 (802.11ax) in enhancing the Wi-Fi roaming experience through features such as Orthogonal Frequency Division Multiple Access (OFDMA), Target Wake Time (TWT), and BSS Coloring. The paper underscores the need for a comprehensive approach to address the challenge of non-optimal AP selection and efficient roaming in wireless networks. By leveraging advanced selection algorithms, implementing smart AP management strategies, and adopting fast roaming technologies, it is possible to significantly enhance the performance and user experience of wireless networks in our increasingly connected world
An Improved Gait Recognition Method Using Modified Gait Energy Image
Get PDFGait recognition is a valuable technology for remote and concealed identity authentication, widely applied in intelligent video monitoring. Existing gait recognition algorithms fall into two categories: appearance-based methods and model-based methods. While gait features differ from static biometric features like faces or fingerprints, they exhibit significant and robust characteristics over a gait cycle. Gait Energy Image (GEI) is a commonly used feature in gait recognition, synthesizing gait images into a single representative image. In this study, we propose an improved gait recognition method that addresses the impact of viewpoint variations, clothing, and carried objects. The method uses modified GEI (MGEI) and view detection and combins two-dimensional principal component analysis and linear discriminant analysis for feature extraction. Experimental results demonstrate the effectiveness of the proposed method in reducing the influence of view variations and achieving robust gait recognition
Spam Detection in Emails Using Machine Learning Techniques: A Review
Get PDFDespite the vast amounts of data available within email communication systems, spam remains a persistent issue, posing challenges for both users and organizations. Analyzing this data holds the potential to develop more effective methods for detecting and mitigating spam emails. However, extracting actionable insights from this data and leveraging them to construct robust spam detection systems presents a significant challenge. Traditional approaches to combating spam, such as rule-based filtering and heuristic methods, have become increasingly inadequate due to the evolving tactics of spammers. Machine learning techniques offer a promising solution by enabling the training of predictive models using historical email data. However, the effectiveness of these models is influenced by factors such as class imbalance and the identification of relevant features essential for spam detection. This paper provides a comprehensive review of various machine learning techniques employed in spam detection within email communication systems. By examining the strengths and weaknesses of different approaches, we aim to identify strategies for improving the efficiency and accuracy of spam detection. Additionally, we propose a spam detection framework centered around ensemble learning models trained on balanced datasets using techniques like SMOTE, and featuring only the most relevant features. This approach is intended to enhance detection performance while reducing false positives, thereby offering a more effective solution to the challenge of spam detection in email systems
File Carving: Analyzing Data Retrieval in Digital Forensics
Get PDFIn the current scenario, mostly the data are stored in digital media. Managing the storage and security of huge volume of data is emerging as a significant challenge for data science researchers and engineers. As data is considered as more costly and powerful than anything else, so during damage or loss of data thousands of dollars are being invested for data recovery. File caving is a technique used for data recovery from the file without the any contextual information when the storage media is formatted or file system got damaged. In this study, we have tried to describe the various types of file caving techniques and the tools used for file caving, along with their limitations and the categories of files which are supported along with the scenario for such recovery
Enhancing Cyber Security: The Role of Networking, Coordination, and Trusted Information Sharing in Organizational Resilience
Get PDFOrganizations must take proactive measures to strengthen their cybersecurity posture as cyber-attacks continue to develop and become more sophisticated. Networking, coordination, and the sharing of trustworthy information among entities and organizations have become essential tactics for achieving this goal. This article gives a general overview of how networking, coordination, and trusted information sharing can improve an organization\u27s cybersecurity posture. It covers the most recent advancements and trends in this field and analyses the advantages, difficulties, and best practices for putting these ideas into effect. The article\u27s conclusion emphasizes the necessity of a cooperative, all-encompassing strategy for cybersecurity that incorporates networking, coordination, and reliable information exchange
Legal Frameworks for Digital Space Protection in Kenya
Get PDFStrong cyber laws are necessary to protect digital spaces in Kenya, where the digital landscape is changing quickly. This need has grown. This article explores Kenya\u27s legal framework for cyberspace, focusing on important topics such as privacy, cybercrime, data protection, and intellectual property rights. It investigates the nation\u27s current state of cyber laws through a thorough assessment, determining whether it is sufficient to handle the problems brought about by emerging technologies and cyber threats.
Furthermore, the article acknowledges the interdependence of national legislation with international trends and examines the critical role that international norms and standards have played in influencing Kenya\u27s approach to cyber law. The paper highlights the importance of collaborative efforts between government agencies, private enterprises, and civil society in strengthening cyber resilience and promoting a secure digital environment.
This article adds to the ongoing discussion on cyber law in Kenya by critically examining the current framework and suggesting possible improvements. Its goal is to promote the creation of a thorough and functional legal system that guarantees the nation\u27s digital spaces are protected
Optimized Q-Learning-Based Handover Decision Algorithm for Femtocells Using Load Balancing in LTE-A Networks
Get PDFThe rapid growth of mobile devices and demand for mobile data has made it challenging to maintain capacity, high coverage, and data speed. With the emergence of small cell networks, the Long-Term Evolution (LTE) system helped to address these issues, Femtocell technology is being deployed to provide improved indoor coverage. However, a major challenge is the frequent handover and unequal distribution of cell loads, which lead to a reduction in call and data rates. Small cells have changing and unplanned load distribution over time, resulting in certain cells suffering high user density and strong resource competition, while others are having low user density and wasteful resource due to low consumption. This imbalance in cell load distribution greatly influences overall network performance and prevents Femtocells from realizing their full potential. Despite several efforts by researchers to enhance network communication, handover is still a challenging issue, many related works have been done in the field but still it needs improvement. This research proposes an Optimized Q-learning-based Handover Decision Algorithm for Femtocells using Load Balancing in LTE-A Networks to improve overall network performance. The algorithm learns to prioritize and select cells with low load during target cell selection and not only provides good Quality of Service (QoS) but also has a low load, resulting in better traffic distribution across the cells. Several simulations were performed using LTE-Sim. Results proved the outperformance of the proposed algorithm over the existing algorithm in terms of QoS with a packet loss ratio for CBR packet transmission of 512 bytes with a rate of 8 packets/second intervals, 88.53%, and VoIP packet transmission of 32 bytes per 20 ms/time interval, 89.24% respectively