International Journal of Wireless and Microwave Technologies @ijwmt
Journal articles - International Journal of Wireless and Microwave Technologies
All articles: 674
Investigation of application layer DDoS attacks using clustering techniques
Scientific article
The exponential usage of internet attracts cyber criminals to commit crimes and attacks in the network. The forensic investigator investigates the crimes by determining the series of actions performed by an attacker. Digital forensic investigation can be performed by isolating the hard disk, RAM images, log files etc. It is hard to identify the trace of an attack by collecting the evidences from network since the attacker deletes all possible traces. Therefore, the possible way to identify the attack is from the access log traces located in the server. Clustering plays a vital role in identifying attack patterns from the network traffic. In this paper, the performance of clustering techniques such as k-means, GA k-means and Self Organizing Map (SOM) are compared to identify the source of an application layer DDoS attack. These methods are evaluated using web server log files of an apache server and the results demonstrate that the SOM based method achieves high detection rate than k-means and GA k-means with less false positives.
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Investigations with All Optical Binary Subtractor Network at 100Gbps
Scientific article
This article demonstrates for the proposed all optical binary subtractor network. Performance explored by exploiting nonlinear attribute the cross gain modulation with semiconductor optical amplifier which otherwise considered as cons if used as an amplifying tool. Numerical simulations have been executed, accordingly accustomed data inputs at 100Gbps data rate employed, generated aspired difference and the borrow outputs concurrently. The design’s performance for the non return to zero, return to zero and Manchester modulation formats have been analyzed, according to it is key performance parameter the extinction ratio. Investigations inferred optimum performance for the non return to zero modulation format outcome extinction ratio of 13.5dB,together with difference and borrow output have been successfully confirmed. Further designs execution with non return to zero modulation format for the key parameters range of data rates, laser peak power, the normalizer power, pump current, the current injection efficiency and the modulator bias voltage have been evaluated. Evaluation inferred that optimum performance is subject to the pertinent election of the vital design parameters. The proposed design is simpler by virtue of key attributes low power consumption and stability altogether with higher integration capability as well provides output generation simultaneously at higher data rate. It was lacking with preceding elucidations. Accordingly, this illustration could be an assistance towards novel contemporary complex digital optical computing combinational networks.
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IoMT Survey: Device, Architecture, Communication Protocols, Application and Security
Scientific article
The technology-based lifestyle has led to a rise in people suffering from obesity, which in turn has led to the emergence of many chronic diseases such as elevated blood sugar and blood pressure, this give researchers a good reasons to develop Internet of Things networks, as the entry of technical innovations has led to Artificial intelligence in the medical field has revolutionized the provision of medical services and facilitated the lives of patients, from monitoring blood sugar levels to using remote surgery techniques, as it has saved a lot of effort and money for both the doctor and the patient at the same time, but these advantages open a wide scope for many problems as well. This survey studied the medical Internet of Things network in terms of presenting the definition, structure, types of devices used, their applications, and some of the communication protocols used in it. The attacks that the medical Internet of Things network may be exposed to were also classified based on the concerns they cause, and the solutions proposed by the researchers were presented. On the other hand, the previous works of the researchers were classified according to the types of devices used, communication protocols, and network security. In each of the mentioned parts, what the researchers have done and their contributions in this field were discussed, analyzed, and a review of the proposed future works in the used literature was presented.
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Issues of Organizing the Architecture of Processes for Identifying Digital Entities and Services
Scientific article
The article discusses the solution to the issue of information systems architecture, which makes it possible to separate identification flows associated with the processes of managing the identification of digital entities and data flows associated with the processes of managing data describing the properties of digital entities. At the same time, a new architecture of connections between digital entities and services is proposed, which makes it possible to create a flexible system for processing the properties of identifiers that can be described in an irregular and unstructured form. In this case, the nomenclature of the parameters of the properties of a digital entity can be customized and expanded as a separate entity, which always maintaining a connection with the identifier. This allows, within the framework of the information system, on the one hand, to adapt any identification systems and ensure the solution of convergence requirements, to ensure compliance and solution of the requirements of recognition, immutability, stability in conditions of processing large volumes of data without implementing generally accepted principles of a global unique permanent identifier, and on the other hand, build flexible connections between digital entities and services.
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Joint Beam-Power Coordinative Scheduling of Neighboring Sectors in Cellular Systems
Scientific article
Beam cooperative scheduling of downlink transmission is an important technique to improve the spectrum efficiency in next generation mobile networks. This paper focuses on switched beams (the emission angles of the beams are fixed) and proposes a joint beam-power coordinative scheduling algorithm among neighbor sectors in the downlink of mobile systems. Each sector coordinates the applied order and transmitted power of the beams with adjacent interfering sector, so as to reduce inter-sector interference and maximize throughputs. This scheduling problem is modeled as a constrained optimization problem and solved by our proposed iterative approach. Computer simulation shows that the proposed approach significantly outperform the existing round robin beam servicing approach and the approach that applies only beam cooperative scheduling.
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Keywords Review of IT Security Literature in Recent 20 Years
Scientific article
The volume of published scientific literature available on Internet has been increasing exponentially. Some of them reflect the latest achievement of the specific research domain. In recent years, many projects have been funded aiming to online scientific literature mining, especially in biomedical research. Scientific literature covers most of the hot topics in the research field and has a very large domain-specific vocabulary. The exploitation of domain knowledge and specialized vocabulary can dramatically improve the result of literature text processing. The purpose of this paper is to identify the frequently used keywords in IT security literatures. The result then can be utilized to improve the performance of automatic IT security document retrieval, identification and classification. Our method is to query CiteseeX to retrieve source data of paper description information and build an artificially annotated corpus. Over the corpus, we perform words frequency statistics, word co-occurrence analysis, discrimination index computation, retrieval efficiency analysis and thus build a lexicon of IT security based on our experimental result. The lexicon can further be used in improving retrieval performance and assisting new words discovering and document classification.
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Scientific article
Traditional signature-based Web Application Firewalls (WAFs) have difficulty detecting increasingly complex assaults that target web applications, such as SQL injections, Cross-Site Scripting (XSS), and API misuse. In this study, we introduce LLM-WAF, a new intelligent firewall architecture that uses Large Language Models (LLMs) to analyze HTTP traffic contextually and semantically. Our framework integrates pre-trained language models with realtime traffic monitoring pipelines to identify malicious payloads through natural language processing capabilities rather than static rule matching. The system incorporates a continuous learning mechanism using reinforcement signals from detected attacks to adapt to emerging threat vectors automatically. In comparison to conventional WAF systems, experimental evaluation on benchmark datasets such as the CSIC 2010 HTTP Dataset and real-world traffic scenarios shows that LLM-WAF achieves 96.8% detection accuracy with an F1=0.95cand dramatically lowers false positives.
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Lattice-reduction-aided equalization for V2V communication channel
Scientific article
World is moving towards the implementation of massive MIMO based communication system and that forces the researchers to design low complexity receiver architecture. MIMO system performance in Vehicular ad hoc networks (VANETs) is a popular research topic. And to support Vehicle-to-vehicle (V2V) communication in high speed mobility condition, it required to have reliable and secure of com-munication. This paper deals with the performance evaluation of the low complex LLR-MMSE receiver in terms of the channel capacity and bit error rate improvement. In this paper we have considered V2V Spatial Channel Model (SCM) and Nakagami-m chaneel model for the performance evaluation. The performance has been evaluated based on the mathematical calculation and simulated results. And also performance comparison between the conventional linear MIMO receivers with the lattics reduction aided MIMO receivers have been presented.
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Learning-Augmented Deterministic Task Allocation and Routing for Heterogeneous Multi-UAV Systems
Scientific article
This paper presents a learning-augmented deterministic method for heterogeneous multi-UAV task allocation and routing in static, fully observed environments. UAV-specific asymmetric path-length matrices represent the output of an offline path planner, allowing online planning to focus on assignment and route construction. The deterministic core evaluates insertions, checks energy feasibility, prioritizes tasks with few feasible UAVs, repairs blocked states, and improves completed routes. A shallow multilayer perceptron ranks feasible candidates by predicting future regret, defined as the difference between the makespan after deterministic completion and the immediate post-insertion makespan. The objective minimizes makespan first and uses aggregate route length only when makespan values are equal within the prescribed numerical tolerance. The model was trained on 12 synthetic instances and evaluated on 20 separate instances, each containing 20 tasks and four heterogeneous UAVs under uniform, clustered, and mixed layouts. It was compared with two greedy insertion heuristics, the corresponding deterministic ablation (CT-D), and a linear-regret variant. The proposed method achieved a mean makespan of 106.24 versus 107.46 for CT-D, a descriptive reduction of approximately 1.1%. Compared with CT-D, aggregate route length increased by approximately 1.5%, while mean runtime increased from 0.059 to 0.233 s. Performance improved on clustered and mixed layouts but declined slightly on uniform layouts.
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Scientific article
Forgetting the stipulated schedule or time of lectures due to one reason or the other has always been a major concern for students resulting in the students missing classes and thereby lagging behind in what the lecturer has taught the other students. The main purpose of developing the Lecture time table reminder system is to minimize this problem to an acceptable level. Lecture Timetable Reminder System is a mobile application developed on the Android platform for the students of Computer Science, 500level, Federal University of Technology, Akure, with the service of reminding them about their lectures. The major tools used in developing this application are Java, Eclipse, Android Software Development Kit (SDK), PHP and MySQL. Java is the programming language that was used and Eclipse is the Integrated Development Environment (IDE) and Android SDK is a virtual device emulator. Then PHP was used to produce a response customized for each user's request to the application, MySQL is the database.
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Leveraging CNN-LSTM Networks for Real-Time Intrusion Detection and Classification in IoT
Scientific article
The IoT (Internet of Things) devices extend the attack surface for cybercriminals, requiring robust IDS (Intrusion Detection Systems). In order to tackle the issues, the AI (Artificial Intelligence), especially the ML (Machine Learning) and DL (Deep Learning) is incorporated into IoT IDS to analyze large datasets, identify complex patterns, and adapt to evolving threats. Hence, the study proposes a modified CNN-LSTM model for real-time intrusion detection and classification in IoT Device Network Logs. The proposed model utilizes the CNNs (Convolutional Neural Networks) for spatial feature extraction and LSTM (Long Short-Term Memory) networks for capturing temporal dependencies, augmenting the accuracy and detection efficiency. The proposed CNN-LSTM model enhances the real-time intrusion detection and contains the ability to detect developing attacks in dynamic IoT environments, which makes it highly flexible for large-scale deployments. The IoT Device Network Logs dataset is used for evaluating the proposed modified CNN-LSTM model. The modified CNN-LSTM model is assessed using the performance metrics such as accuracy, precision, recall, F1-score, time complexity and false alarm rate. As a result, the modified CNN-LSTM model achieves superior performance and earlier detection in contrast to the conventional models deliberating its potential for enhancing IoT security.
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Lightweight Distance Estimation from Single Images without Camera Intrinsics
Scientific article
In this paper, we address the problem of estimating the distance between a camera and a photographed object using minimal prior information. Specifically, the goal is to obtain distance estimates without access to intrinsic camera parameters such as focal length, sensor size, or lens distortion coefficients. We propose three simple heuristic methods, which can be viewed as lightweight variants of the classical camera pinhole model (CPH), but do not require calibration. Instead, they rely only on the approximate real height of a known object in the scene. The methods were validated on a representative dataset of images captured with several modern cameras and smartphones, using known object dimensions as ground truth. Their performance was compared against CPH using error metrics such as mean absolute error (MAE), mean absolute percentage error (MAPE), root mean squared error (RMSE), mean signed error (MSD), coefficient of determination R2), and supported by statistical testing (Shapiro–Wilk, ANOVA, Kruskal–Wallis). The analysis confirmed that, while less precise than fully calibrated approaches, the proposed heuristics achieve consistent and reliable distance estimates under minimal assumptions. These methods are particularly suited for lightweight applications and devices with fixed focal lengths, such as smartphones.
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Load Balancing Mechanism for Edge-Cloud-Based Priorities Containers
Scientific article
Considering edge devices have limited resources, it's critical to keep track of their current resource usage and device resource allocation algorithms that send containers to edge and cloud nodes according to their priority. To minimize the strain on edge devices and enable the running of mission-critical applications, edge containers may need to be transferred to a cloud platform. In this paper, we suggested a mechanism for prioritizing container balance between the edge and cloud while attempting to assign delay-sensitive containers to edge nodes. We assess the performance of Docker container management systems on resource-constrained computers and offer ways for reducing administration and migration overhead based on the workload type, to bring load balance to the systems. The proposed algorithm gives flexibility to get the best possible ways to achieve load balancing. The Tensorflow’s object discovery API was used, accessed with Flask, Python's micro-web framework. Docker container management technology was used in the implementation of this application.
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Load Balancing in Cloud Computing Using Hungarian Algorithm
Scientific article
Cloud computing is a highly popular computing paradigm providing on-demand resources with high reliability and availability. The user requests are fulfilled by providing a virtual machine with the requested configuration. However, with the ever-increasing load on the cloud resources, the need for optimal resource utilization of the cloud resources has become the need of the hour. Load balancing has been identified as one of the possible ways to improve resource utilization in the cloud and the current state-of-the-art algorithms indicate the numerous attempts made to find the approximate solution for this NP-hard problem. In this work, we have focused on evaluating the efficiency of the Hungarian algorithm for load distribution in the cloud and compared its performance with First-come-first-serve (FCFS). The simulations were carried out in CloudSim and show remarkable improvement in various performance parameters. Finish time of a given task schedule was reduced by 41% and average execution time was reduced by 13% in the Hungarian algorithm when compared with FCFS. The simulations were carried out under different workload conditions to validate our results.
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Location based Energy Efficient Scheme for Maximizing Routing Capability of AODV Protocol in MANET
Scientific article
Nodes in Mobile Ad hoc Network (MANET) are forming a dynamic topology by that the nodes are continuously change their location and also the nodes functioning is dependent on the limited battery capacity that is called energy. The dynamic behavior of network connection is not maintained for long time. All nodes in network are energy dependent and efficient energy utilization is one of the important criteria in MANET. In this paper we proposed a new location based energy efficient scheme with AODV protocol. In this scheme energy dependent nodes are improving the routing capability of AODV protocol on the basis of location based protocol LAR (Location Aided Routing protocol). In network nodes are not aware about their energy status and also recur flooding of routing packets are consumes more energy in network by that the most of the energy is wasted in connection establishment. LAR protocol reduces that possibility of destination finding by maintain the record of location of each node in network respect to other nodes. It implies that every node in network is maintaining the record of other nodes (participating in routing procedure) with their current location and speed. If the nodes in network are know about the energy status and also about the status of location of receiver that reduces the energy consumption. The main aim of proposed scheme is to enhance the energy utilization in network. The performance of normal AODV, AODV with LAR and AODV with LAR and Energy is illustrate here and observe that the LAR protocol reduces the energy consumption and prolog the network lifetime that completely depend on the energy of mobile nodes.
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Loss Less and Privacy Preserved Data Retrieval in Cloud Environment using TRSE
Scientific article
In the modern era of the computing world, the data producing and using it is becoming large and instant at various places. For availing the data at different locations for processing we need to store it in the global platform. Cloud environment provides a best and easy way for this. Cloud computing is becoming as the essential thing for high-quality data services. However there are some potential problems with respect to data security. Here encryption techniques can be used for providing security, but with restricted efficiency. In this paper we propose a new encryption mechanism for providing data security in cloud environment. We propose a two round searchable encryption which supports multi keyword retrieval. Here we adapted a vector space model for improving search accuracy; the elgamal encryption technique allows users to involve in the ranking, while the essential key part of encryption will be done at the source itself. The proposed improves the data security and reduces data leakage.
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Luminous Intensity Control System Based on ZigBee Wireless Sensor Networks
Scientific article
This paper introduces an energy conservation luminous intensity control system based on ZigBee sensor networks for smart home. The study is conducted to reduce unnecessary energy consumption by changing the luminous intensity of white LED according to the light coming into the room. A detecting circuit connected to the pin of CC2430 is set on the working face to collect the real-time luminous intensity signal. Then the ZigBee module adjusts the PWM signal to drive the white LEDs aiming at keeping a fixed and appropriate luminous intensity (e.g. 500Lux). Meanwhile, it transmits the data to the ZigBee coordinator through ZigBee wireless network. The monitoring PC get the data through the serial communication interface and display the states of the lights. Administrators can turn on or off the lights by clicking on the screen. This system can realize monitoring and controlling all the lights wirelessly so that users can save a lot energy and staff members. The system has been proved to be effective and convenient.
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MANET testbed using raspberry PIs
Scientific article
Mobile ad-hoc networks (MANETs) are without any infrastructure and consists only of equal peers. This paper presents an empirical tests for MANET routing protocols. The testbed based on Linux platform installed in mobile computers. Some parameters are analyzed such as movement speed and the number of hops which impact on routing performance. The testbed consists of several Raspberry Pis (RPis) without the need for any central master device. For making the RPis mobile and independent of any fixed power sockets, each of them is powered by a battery. On the other hand, for the evaluation of the testbed, two routing protocols are chosen. The first protocol is called BABEL, which considered as a distance vector routing algorithm. The other one, the Optimized Link State Routing Protocol (OLSR) which considered as proactive routing protocol. The use case was a multi-hop download of files with different size. The aim is to evaluate how multiple hops influence the bandwidth and delay. The results show that OLSR performs better regarding the throughput. But Babel has less delay and faster regarding convergence.
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Scientific article
The rapid evolution of next-generation wireless communication systems has increased the demand for intelligent microwave components and energy-efficient wireless architectures capable of supporting ultra-high data rates, low latency, massive device connectivity, and adaptive resource management. Conventional optimization approaches often experience slow convergence, high computational complexity, and limited adaptability when optimizing multiple communication parameters simultaneously. To address these challenges, this paper proposes a Machine Learning-Assisted Adaptive Pelican Optimization (ML-APO) framework for the joint optimization of microwave components and wireless communication architectures. The proposed framework integrates an Adaptive Pelican Optimization Algorithm with a machine learning-assisted surrogate prediction model that rapidly estimates communication performance metrics, thereby significantly reducing computational overhead during the optimization process. The optimization simultaneously considers transmission power, antenna parameters, microwave component characteristics, spectrum allocation, routing efficiency, and communication reliability through a multi-objective fitness function. The adaptive search strategy of the Pelican Optimization Algorithm effectively balances global exploration and local exploitation, enabling faster convergence toward optimal network configurations while avoiding premature convergence. Extensive simulation results demonstrate that the proposed ML-APO framework achieves 96.41% energy efficiency, 43.8% improvement in network lifetime, 13.56 Gbps throughput, 99.43% packet delivery ratio, 0.49 ms end-to-end latency, and 0.54% packet loss, while reducing optimization time by 35.8% and improving convergence speed by 39.6% compared with existing optimization methods. These results demonstrate that the proposed framework provides an efficient, scalable, and intelligent solution for designing high-performance microwave components and next-generation wireless communication architectures suitable for future 6G and beyond wireless networks.
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Scientific article
In the wireless sensor network, various sensor nodes are present that are used for the communication, sensing and computing. An external mobile sink is present which move around the grid that is used for the communication with the nodes directly which are present in the network. As we know that for formation of network we need to find the route between all the nodes coming in the network, for this purpose routing is done. Routing is defined as moving of information from source to destination. For efficient network the routing protocol that is used should consume less energy, and less distance. In the MVGDRA routing algorithm is proposed that use the mobile sink approach. The selection of cluster head is done on the basis of the weight values. By doing this cluster head will be selected on the basis of the energy means which node has highest energy appointed as cluster head that increases the stability of the network. And the event driven based strategy is used for the data transfer, the energy will be only released when it is required. The energy will not be released after each round. By this the energy consumption of the system decrease and the life time the network is increased. So this method is considered to be more efficient and better than the traditional methods of routing as the network performance is enhanced and its life time is increased. Simulation results show the comparison between the VGDRA and the MVGDRA.
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