Mohd Nazri Ismail, Mohd Nazri
National Defence University of Malaysia

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Predictive Wireless Received Signal Strength Using Friis Transmission Technique Rawi, Roziyani; Mohd Isa, Mohd Rizal; Ismail, Mohd Nazri; Abu Bakar Sajak, Aznida; Yahaya, Yuhanim Hani
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.2178

Abstract

A good WLAN performance is crucial in determining the quality of experience (QoE) among the campus community. Proper WLAN planning and design should be done beforehand to ensure good WLAN performance. Various studies have discussed different methods of conducting WLAN planning to predict WLAN's best performance, including using artificial intelligence and mathematical approaches. One of the processes involved in performing WLAN planning is measuring performance parameters. Signal strength is one of the vital parameters to be measured in determining the excellent performance of WLAN in a particular area. When deploying a WLAN design in two different environments, the signal strength outcomes can differ due to various factors, including obstacles and path loss propagation issues within the deployment area. Higher Learning Institutions (HLIs) present a unique challenge as their building designs vary to accommodate student needs. As a result, the selection of materials used will also be different, affecting the WLAN performance. A detailed study should investigate the effect of path loss propagation and the type of obstacle that affects WLAN performance in HLI. Thus, this study focuses on predicting received signal strength using Friis Transmission and studying the effect of path loss propagation on WLAN performance. The simulated model significantly affects signal strength when the signal passes through different types of building material (non-LOS) and line-of-sight (NLOS), where concrete walls substantially affect the received signal strength between transmitters. The proposed model can assist network planners in designing robust WLAN infrastructure by improving signal strength, particularly in the HLI WLAN environment. 
Detecting Distributed Denial-of-Service (DDoS) Attacks Through the Log Consolidation Processing (LCP) Framework Khairuddin, Mohammad Adib; Mohd Isa, Mohd Rizal; Mohd Shukran, Mohd Afizi; Ismail, Mohd Nazri; Maskat, Kamaruzaman
JOIV : International Journal on Informatics Visualization Vol 8, No 3 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.3.2184

Abstract

One major problem commonly faced by organizations is a network attack especially if the network is vulnerable due to poor security policies. Network security is vital in protecting not only the infrastructure but most importantly, the data that moves around the network and is stored within the organization. Ensuring a secure network requires a complex combination of hardware including both network and security devices, specialized applications such as web filtering and log management, and a group of well-trained network administrators and highly skilled analysts.  This paper aims to present an alternative to the current log management solution. A hindrance to the current log management solution is the difficulty in amalgamating and correlating a vast number of logs with different formats and variables. This paper uses a novel framework called Log Consolidation Processing (LCP) based on the System Information Event Management (SIEM) technology, to monitor the behavior and the fitness of a network. LCP provides a flexible and complete solution to collect, correlate, and analyze logs from multiple devices as well as applications. An experiment testing the effectiveness of LCP in detecting DDoS attacks in a campus network environment was conducted, demonstrating a highly successful rate of detection. Besides threat detection and avoidance through log monitoring and analysis, other benefits of implementing the LCP framework are also included. This paper concludes by mentioning suggested enhancements for the LCP framework.
Enhancing The Server-Side Internet Proxy Detection Technique in Network Infrastructure Based on Apriori Algorithm of Machine Learning Technique Maskat, Kamaruzaman; Mohd Isa, Mohd Rizal; Khairuddin, Mohammad Adib; Kamarudin, Nur Diyana; Ismail, Mohd Nazri
JOIV : International Journal on Informatics Visualization Vol 9, No 2 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.2.3410

Abstract

The widespread use of proxy servers has introduced challenges in managing and securing internet connections, particularly in detecting non-transparent proxies that obscure the originating IP address. Proxy servers, while beneficial for bandwidth management and anonymity, can be exploited for malicious purposes, such as bypassing geo-restrictions or concealing cyberattacks. This study aims to address the gap in identifying proxy usage by providing an organized review of existing detection techniques and proposing a hybrid server-side detection framework. The objectives of the research include identifying and comparing proxy detection methods, developing a hybrid approach using machine learning, and evaluating its effectiveness in enhancing network security. The methodology involves collecting primary data through controlled environments simulating direct and proxy-based connections. A machine learning model, based on the Apriori algorithm, is employed to analyze network traffic patterns and identify characteristics indicative of proxy usage. Attributes such as IP addresses, port numbers, and round-trip times are used to train the model. The proposed framework is tested for its robustness, accuracy, and speed against existing detection methods. The results demonstrate the feasibility of the hybrid approach in improving the detection of non-transparent proxies, particularly those not easily identifiable using conventional techniques. The findings have significant implications for securing server-side infrastructure, aiding in cyber threat mitigation, and enforcing organizational policies. Future research can expand on this framework by testing it against broader proxy types and integrating real-world data to enhance its reliability and scope. This study contributes to advancing cybersecurity practices by addressing a critical challenge in proxy detection.
Adoption of Industry 4.0 with Cloud Computing as a Mediator: Evaluation using TOE Framework for SMEs Abu Bakar, Muhammad Ramzul; Mat Razali, Noor Afiza; Ishak, Khairul Khalil; Ismail, Mohd Nazri; Tengku Sembok, Tengku Mohd
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.2205

Abstract

Industry 4.0 represents a significant shift in production processes, necessitating the integration of humans, products, information, and robots into digitalized workflows. While this transformation offers numerous benefits, its adoption, particularly among small and medium enterprises (SMEs), is hindered by various challenges such as financial constraints, maintenance costs, and a lack of digital culture and awareness. This study examines the adoption of Industry 4.0, specifically through cloud computing technologies, within the manufacturing and service sectors of SMEs in Malaysia. Cloud computing is economical, straightforward, and easily implemented for SMEs. We propose a conceptual model based on an extended Technology-Organisation-Environment (TOE) model, integrating refined constructs and considering digital organizational culture as a moderator, with cloud computing acting as a mediator to enhance firm performance. The study investigates the relationship between these constructs and addresses overlooked factors influencing adoption. Utilizing a structured questionnaire with 54 items derived from previous research, we employ partial least squares structural equation modeling (PLS-SEM) to analyze data collected from a pilot study. Our findings confirm the reliability and validity of the proposed conceptual model, meeting established criteria for composite reliability, average variance extracted (AVE), Cronbach's alpha, and discriminant validity (HTMT Criterion). Furthermore, this study presents empirical findings on technological, organizational, and environmental influences on adopting cloud computing. The insights gained from this research offer valuable guidance to enhance the performance of SMEs in the Industry 4.0 landscape.