International Journal of Wireless and Microwave Technologies @ijwmt
Journal articles - International Journal of Wireless and Microwave Technologies
All articles: 648
The Comparison of Machine Learning Algorithms on Online Classification of Network Flows
Scientific article
Online classification of network flows is a process that captures packets generated by network applications and identifies types of network applications (or flows) in real time. There are three key issues about online classification: observation window size, feature selection, and classification algorithms. In this paper, by collecting five types of typical network flow data as the experiment sample data, the authors found observation window size 7 is the best for the sample data and most classifiers. The authors proposed a full feature set based on the standard feature set which reflects statistical features of network flows. Using five commonly used feature selection methods, the authors identified the most effective features could be reduced from 56 original features to 11 effective features. Lastly, according to special need for online classification, the authors studied 11 different classifiers on their classification accuracy, model construction time, and classification speed. The results show that C4.5 and JRip are the two best algorithms for online classification.
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Scientific article
The accelerating pace of digital transformation has expanded dependency on online services, exposing a widening misalignment between technology adoption and cybersecurity competence. This study investigates generational disparities in digital security literacy, perceived risk, and protective behaviors, with a particular focus on senior citizens as high-risk end users within computer network and information security ecosystems. 112 participants from various age and professional cohorts were surveyed using a four-point Likert scale with minimal central tendency response bias followed by both descriptive and mean-comparison analyses. Results demonstrate that cybersecurity literacy is medium but uneven (mean = 2.02), with respondents from the oldest age group (age sixty and above) reporting the lowest composite security score and weakest preventive practices, including a Two-Factor Authentication penetration of only 35%. There is a clear confidence-competence gap (+0.47) among senior citizens, meaning they tend to overestimate their ability to deal with digital services but underestimate the challenge of acquiring technical knowledge. Building on these findings, the paper introduces the Digital Guardian for Seniors framework a conceptual, human-centric intervention model integrating adaptive, visually oriented pedagogy, an intergenerational cyber-buddy system, and suggested metrics for longitudinal evaluation. The study contributes to computer network and information security research by providing demographic-based empirical evidence and outlining a theoretical foundation for future empirical testing and targeted interventions for an aging digital population.
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The Economic Evaluation of Lighting Energy-saving Modification Program
Scientific article
Many lighting energy-saving modification programs have the embarrassment of uneconomical. This paper takes into account economic evaluation to solve the problem. According to illuminative equipments price, life span and power consumption, the optimal program will be found under the limited investment. Firstly, the benefit ratio will be used to evaluate on the equipments modification necessity, and get the modification sequence. If the biggest benefit ratio is in different equipment simultaneously, the better one will be selected in terms of relative investment recovery period. The relative remaining time is innovatively introduced into economic evaluation for determining the equipments modification locations. Then the system operation flowchart is to prove that the scheme is workable.
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The Empirical Study on the Relationship between Knowledge Integration and IT Project Performance
Scientific article
This article examines the relationship between timely project completion and the management’s integrative capability. Measures of the integrative capability are used to predict on-time project completion, where completion is a function of the duration of IT-related project delays. In a longitudinal study of 74 enterprise application integration projects in the medical sector, integrative capability was measured from the point of view of the CIO and a facility IT manager. Accounting for several project controls, our Cox regression results indicate both integrative dimensions significantly mitigate the duration of IT-related project delays, thus promoting timely project completion. The analysis also reveals the importance of taking management structure into consideration when studying IT phenomena in networked organizations.
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The Existence of Homoclinic Solutions for Second Order Hamiltonian System
Scientific article
The research of homoclinic orbits for Hamiltonian system is a classical problem, it has valuable applications in celestial mechanics, plasma physis, and biological engineering. For example, homoclinic orbits rupture can yield chaos lead to more complex dynamics behaviour. This paper studies the existence of homoclinic solutions for a class of second order Hamiltonian system, we will prove this system exists at least one nontrivial homoclinic solution.
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The Impact of Artificial Intelligence on Cybersecurity and Data Protection
Scientific article
The escalating complexity of cybersecurity threats necessitates advanced technological solutions to protect digital infrastructures. This study explores the application of Autoencoder neural networks, a deep learning model, for anomaly detection in network traffic, aiming to enhance real-time identification of cyberattacks. Using the CICIDS2017 dataset, which encompasses diverse attack types such as Distributed Denial of Service (DDoS) and infiltration, the Autoencoder was trained to detect deviations from normal traffic patterns based on reconstruction errors. The model was optimized through preprocessing, feature selection, and hyperparameter tuning, achieving strong performance metrics including precision, recall, F1-score, accuracy, and ROC-AUC. Despite its effectiveness in distinguishing normal and malicious traffic, challenges arose in detecting stealthy attacks like slow brute-force attempts. These results underscore the Autoencoder's potential in cybersecurity frameworks and highlight opportunities for improvement through adaptive thresholds and hybrid models. This study contributes to advancing AI-driven anomaly detection, promoting proactive defense against evolving cyber threats.
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Scientific article
Cyber security is of topical concern in the computing industry and in organizations that require ICT infrastructure for business-related activities. Theft or disrupting the flow of data and information can cause devastating damage to an institution’s reputation and this may lead to huge financial losses. More mayhem can be perpetrated by malicious codes such as worms to organizations that use wireless sensor networks for collecting and transmitting data and information. To tackle this issue of cyber security, researchers have used epidemiological models (such as SEIR and SEIR-V) to gain insight into malicious code propagation. However, topological concerns and its impact in worm propagation haven’t been thoroughly studied. Here, we modify older models by applying a different expression for sensor deployment area; we intend to highlight the spatial parameters that may allow for the extinction of worms in wireless sensor networks amidst countermeasures deployed by network managers.
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The Method for Best Basis Selection in the case of Non-Dyadic Wavelets
Scientific article
Wavelet analysis has established itself as a robust and highly effective framework for the processing and characterization of non-stationary signals. While classical dyadic wavelet transforms are widely utilized due to their computational efficiency, non-dyadic (rational) wavelet transforms often provide a superior representation of signal singularities and complex oscillatory patterns. The proliferation of diverse wavelet functions necessitates a systematic approach to basis selection, which remains a critical task for maximizing feature extraction capabilities. This paper investigates fundamental approaches for evaluating the efficiency of wavelet bases, focusing on criteria derived from the energy distribution of decomposition coefficients, the similarity between the wavelet coefficients and the original signal, and mutual information metrics. The applicability and mathematical robustness of these evaluation methods are specifically examined in the context of non-dyadic wavelet transforms. To validate the investigated methodologies, an additive two-harmonic test signal is employed, subjected to four distinct types of interference (additive white Gaussian, impulse, pink, and multiplicative noise) under varying signal-to-noise ratios. Finally, a comprehensive Composite Quality Index (CQI) is proposed. By aggregating the considered energetic and information-entropic characteristics, this index provides a reliable criterion for selecting the optimal non-dyadic wavelet basis for specific signal processing tasks.
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The Research and Application of Webpage Temper-proofing System
Scientific article
With the sharp increase of hacking attacks over the last couple of years, web application security has become a key concern. The attack to websites, especially the explosion of webpage interpolating incidents has become one of the most serious problems of it. In this paper, the system adopts Web server core embedded technology to imbed tamper detection module and application protection module into the Web server, define corresponding strategies for temper-proofing, and realize the real-time monitoring and protection of web pages and the dynamic content in databases.
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The Research of On-line Monitoring System of Power Cable Joint Temperature
Scientific article
Power cable joint is the weak link of power system’s safe operation, it is important significance to real-time master the operating temperature of power cable joint for the safety of the power system. This paper adopts wireless technology to design the temperature monitoring system of power cable joint. Monitoring terminal collection temperature data located in each power cable joint collects the measured data in the cable branch box through the near distance micro-consumption electronic wireless technology to data concentrators located at the bottom of the cable branch box, then transmits to the monitoring center through CAN bus network. The system realizes the low cost and on-line reliable monitoring of power cable point temperature of the urban cable branch box.
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The Selective Forwarding Attack in Sensor Networks: Detections and Countermeasures
Scientific article
Sensor networks are becoming closer towards wide-spread deployment so security issues become a vital concern. Selective forwarding attack is one of the harmful attacks against sensor networks and can affect the whole sensor network communication. The variety of defense approaches against selective forwarding attack is overwhelming. In this paper we have described all the existing defensive schemes according to our best knowledge against this attack along with their drawbacks, thus providing researchers a better understanding of the attack and current solution space. This paper also classifies proposed schemes according to their nature and defense. Nature of scheme classifies into Distributed and Centralized. Defense of scheme classifies into detection and prevention.
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The Study of Access Control for Service-Oriented Computing in Internet of Things
Scientific article
In Internet of Things, computing and processing of information is the core supporting. In this paper, we introduce “Service-Oriented Computing” to solve the computing and processing of information in IoT. However, a key challenge in service-oriented environment is the design of effective access control schemas.We put forward a model of Workflow -oriented Attributed Based Access Control (WABAC), and an access control framework based on WABAC model. WABAC model grants and adapts permissions to subjects according to subject atttribute, resource attribute, environment attribute and current task, meeting access control request of SOC. Using the approach presented can effectively enhance the access control security for SOC applications, and prevent the abuse of subject permissions.
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The Study on Formal Verification of OS Kernel
Scientific article
There is increasing pressure on providing a high degree of assurance of operation system’s security and functionality. Formal verification is the only known way to guarantee that a system is free of programming errors. We study on formal verification of operation system kernel in system implementation level and take theorem proving and model checking as the main technical methods to resolve the key techniques of verifying operation system kernel in C implementation level. We present a case study to the verification of real-world C systems code derived from an implementation of μC/OS – II in the end.
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Scientific article
The mobility and pervasiveness have created many opportunities of using mobile phones in performing activities of SMEs. This is due to the low ICT readiness especially in SMEs operating in less developed countries compared to large firms. Some of the challenges facing Tanzanian SMEs include but are not limited to poor ICT infrastructures, lack of ICT skills, lack of management support, poor financial capabilities and lack of reliable electrical power supply. While there is a number of studies which explains the factors influencing adoption and usage of mobile phones in SMEs, it is still unclear whether the mandatoriness has an impact on such acceptance. Understanding the voluntary aspects provides informed decision-making for SME managers and potential stakeholders on identifying the issues which need their attention. This study involved a survey of 459 respondents from Tanzanian SMEs using SEM and AMOS. The results show that the mandated use of mobile phones in the SMEs has a moderating effect on the overall acceptance of mobile phones in performing daily activities. Recommendations and suggestions for future works are also highlighted in this article.
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Scientific article
The Internet of Things (IoT) driven Industrial Revolution 4.0 (IR4.0) and this is impacting every sector of the global economy. With IoT devices, everything is computerized. Today's digital forensics is no longer limited to computers, mobiles, or networks. The current digital forensics landscape demands a significantly different approach. The traditional digital forensics frameworks no longer meet the current requirements. Therefore, in this paper, we propose a novel framework called “Multi-level Artifact of Interest Digital Forensics Framework for IoT” (MAoIDFF-IoT). The keynote "Multi-level" aims to cover all levels of the IoT architecture. Our novel IoT digital forensics framework focuses on the Artifact of Interest (AoI). Additionally, it proposes the action/detection matrix. It encompasses the advantages of the previous frameworks while introducing new features specifically designed to make the framework suitable for current and future IoT investigation scenarios. The MAoIDFF-IoT framework is designed to face the challenges of IoT forensic analysis and address the diverse architecture of IoT environments. Our proposed framework was evaluated through real scenario experiments. The evaluation of the experimental results reveals the superiority of our framework over existing frameworks in terms of usability, inclusivity, focus on the (AoI), and acceleration of the investigation process.
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TreeLoc: An Ensemble Learning-based Approach for Range Based Indoor Localization
Scientific article
Learning-based localization plays a significant role in wireless indoor localization problems over deterministic or probabilistic-based methods. Recent works on machine learning-based indoor localization show the high accuracy of predicting over traditional localization methods existing. This paper presents a Received Signal Strength (RSS) based improved localization method called TreeLoc(Tree-Based Localization). This novel method is based on ensemble learning trees. Popular Decision Tree Regressor (DTR), Random Forest Regression (RFR), and Extra Tree Regressor have been investigated to develop the novel TreeLoc method. Out of the tested algorithm, the TreeLoc algorithm showed better performances in position estimation for indoor environments with RMSE 8.79 for the x coordinate and 8.83 for the y coordinate.
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Trust Modelling and Management for IoT Healthcare
Scientific article
The IoT wave is on rise and it is considered as the biggest world changing computing ecosystem after the invention of Internet where the meaning of lifestyle is expected to be changed. IoT is now diffusing pervasively in most areas of life like smart home, smart cities, smart irrigation, smart healthcare etc. The concerned industry is trying to reap maximum benefits from this regime without putting extra efforts or investing much to make the related infrastructure secure and trustworthy. IoT end device, a.k.a smart object, is one component of this ecosystem, responsible to interact with the physical environment and gather the data, along with communication technologies, processing capabilities like fog or cloud computing and applications to interact with the device (s). It is possibility that such devices can be faulty, compromised or misbehaving because of internal or external factors like hardware malfunctioning or cyber-attacks. In this situation the data gathered and transferred by such devices can be disaster and challenging in decision making specifically in an area where the human life is involved like IoT healthcare. We have proposed a mathematical model to estimate the trust of such devices. Trust on IoT devices and gathered data from such trusted devices will boost the confidence of end users on this new computing regime; especially in healthcare environment. The estimated trust status (trusted, uncertain, and untrustworthy) will be saved in a database or CSV file with a timestamp to be used as reputation by healthcare applications. Patients are assigned their SOI based on their specific diagnoses and procedures performed during their medical encounter. Similarly, for a patient with heart diseases or having hypertension can be considered in extreme category with a value of γ = 1 if there is some deviation of readings.
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Trust Models in Cloud Computing: A Review
Scientific article
It is common to hear that big or small organizations are moving to cloud computing for its scalability and cost savings. But, how do you decide which cloud provider to trust? Trust is a vital factor, especially for service oriented systems in the area of Information Technology and Security. Several issues have been raised by enterprises and individuals concerning the reliability of the cloud resources. In cloud computing, trust helps the consumer to choose the service of a cloud service provider for storing and processing their sensitive information. In this paper, a methodical literature analysis of trust management and existing trust models is presented to evaluate trust based on various QoS parameters. Key research issues and future research directions in existing literature are also suggested.
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Two Noise Addition Methods For Privacy-Preserving Data Mining
Scientific article
In the last decade, more and more researches have focused on privacy-preserving data mining(PPDM). The previous work can be divided into two categories: data modification and data encryption. Data encryption is not used as widely as data modification because of its high cost on computing and communications. Data perturbation, including additive noise, multiplicative noise, matrix multiplication, data swapping, data shuffling, k-anonymization, Blocking, is an important technology in data modification method. PPDM has two targets: privacy and accuracy, and they are often at odds with each other. This paper begins with a proposal of two new noise addition methods for perturbing the original data, followed by a discussion of how they meet the two targets. Experiments show that the methods given in this paper have higher accuracy than existing ones under the same condition of privacy strength.
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Two-Layer Encryption based on Paillier and ElGamal Cryptosystem for Privacy Violation
Scientific article
Our life nowadays relies much on technologies and online services net banking, e-voting and so on. So, there is a necessity to secure the data that is transmitted through the internet. However, while performing decryption, it sometimes led to privacy violation so there is need to operate on users encrypted data without knowing the original plaintext. This paper represents the implementation of two-layer cryptosystem using paillier and elgamal algorithm both following asymmetric encryption. It is mainly focusing the challenges of privacy protection and secure utilization of information, where homomorphy encryption is gaining attention. Additive homomorphism is used in paillier cryptosystem which is used in fields like secure biometrics and electronic voting. Elgamal ensures that paillier encrypted data is secured that ensures two-layer encryption.
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