As technology rapidly advances, the Internet has become an essential part of modern life. However, public awareness of cybersecurity has not kept pace with the growing threat landscape. Cyber incidents have become more frequent, caused by factors such as malware , software vulnerabilities, and social engineering. With the evolution of malicious attack methods, there is a growing need for innovative and effective cybersecurity defense strategies. This study proposed a Domain Generation Algorithm (DGA) domains detection framework leveraging a deep learning architecture combined with FastText. Using FastText for word embedding extraction, this research developed the Hybrid DGA DefenseNet (HDDN), which integrates Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks. This hybrid model extracts features from datasets and performs both detection and classification. On the Netlab360 and UMUDGA datasets, the model achieved detection accuracy of 97.70 % and 97.42 %, outperforming the Random Forest approach by 15.77 % and 16.29 %, and the C5.0 with GAN approach by 6.40 % and 7.22 %. Additionally, the model achieved classification accuracy of 93.86 % on the Netlab360 dataset and 90.09 % on the UMUDGA dataset, demonstrating the effectiveness of HDDN compared to existing methods.

Cybersecurity is a critical concern in our increasingly digital world, with phishing attacks posing one of the most insidious threats to individual and organizational security. Although machine learning has revolutionized phishing detection, there is still a considerable gap in the ability to detect such threats in real time with high accuracy and efficiency. Current methods often fail to dynamically adapt to the rapidly evolving tactics of cyber adversaries, leading to gaps in detection and prevention capabilities. We introduce an optimized Multi-Layer Ensemble Model that leverages a combination of advanced machine learning classifiers, including K-nearest neighbors, Decision Trees, Random Forest, Extra Tree, and XGBoost, to enhance the accuracy and efficiency of phishing website detection. Experimental results demonstrate that our model achieves a significant improvement in detection accuracy, rising from 95.99% to 97.25%, while maintaining a minimal response time of 4.8 seconds. This model effectively reduces both false positives and negatives, adapting dynamically to new phishing tactics. This advancement not only addresses critical vulnerabilities in cybersecurity defenses but also sets a new benchmark for real-time phishing detection systems, offering a scalable solution that can evolve with the threat landscape.

To predict rainfall, our proposed model architecture combines the Convolutional Neural Network (CNN), which uses the ResNet-152 pre-training model, with the Recurrent Neural Network (RNN), which uses the Long Short-term Memory Network (LSTM) layer, for model training. By encoding the cloud images through CNN, we extract the image feature vectors in the training process and train the vectors and meteorological data as the input of RNN. After training, the accuracy of the prediction model can reach up to 82%. The result has proven not only the outperformance of our proposed rainfall prediction method in terms of cost and prediction time, but also its accuracy and feasibility compared with general prediction methods.

The remote control is widely used for its convenience and its support of resource sharing. However, it can be exploited by hackers. This work aims to prevent remote network threats using behavioral features and machine learning mechanisms. A threat intelligence monitoring engine called DEtect remote Shell Threat system (DEST) was designed and divided into three levels, depending on the hazard. The performance analysis results demonstrate that the proposed DEST system has an accuracy of 99.20% and an F1-score of 99.80%. It is superior to existing detection methods, offering 4% and 1% improvement in accuracy and F1-score.

The website security is an important issue that must be pursued to protect Internet users. Traditionally, blacklists of malicious websites are maintained, but they do not help in the detection of new malicious websites. This work proposes a machine learning architecture for intelligent detecting malicious URLs. Forty-one features of malicious URLs are extracted from the data processes of domain, Alexa and obfuscation. ANOVA (Analysis of Variance) test and XGBoost (eXtreme Gradient Boosting) algorithm are used to identify the 17 most important features. Finally, dataset is used to learn the XGBoost classifier, which has a detection accuracy of more than 99%.

This work presents a novel indoor positioning system that exploits a hybrid algorithm for future productivity 4.0. In the proposed system, LEDs are signal transmitters that are deployed on a ceiling. The target receiver is a smart sensor that receives the frequency, color temperature and luminance of the LEDs. First, the system determines the frequency of the LEDs to select a subspace to narrow down from a positioning area and to compute the position of the target. This work proposes a hybrid fingerprint that is based on RSSI values. RSSI signals are easily disturbed by refraction or diffraction. This research is based on line-of-sight light emission, which increases the accuracy of indoor positioning.

Following recent advances in sensing and wireless technologies, Internet-of-Things (IoT) applications are being exploited in various fields. The scale of IoT systems and the number of devices that they include has become huge, and the construction of IoT applications is, therefore, becoming increasingly challenging. This work proposes a script framework as a convenient development interface for service-oriented architecture (SOA) scheduling of web-based information of IoT applications, called ScriptIoT, which is composed of the IoT fundamental in case of all type of devices integration and a scriptable agent. Based on the IoT fundamental class, various IoT devices may be developed and the scriptable agent enables IoT applications to be configured using scripts. The proposed ScriptIoT framework, which offers both polling an event-driven mechanism for delegating IoT applications to the agent and reporting event of the specified device, contributes to large-scale applications. Experiments herein reveal that in the proposed ScriptIoT framework, the access time and CPU loading are slightly greater than those achieved using traditional C programming by 3% and 13%, respectively, but the proposed framework exhibits improved flexibility and scalability.

Address scrambling and data inversion techniques are proposed for yield enhancement of NROM-based ROMs in this paper. Besides using the conventional fault replacement techniques,fault maskingeffects are also exploited to further improve the fabrication yield and reduce the amount of extra spare rows/columns. That is, we consider the logical effects of physical defects when the customer's code is to be programmed. A novel test and repair flow is also proposed. Based on the proposed techniques, possibilities of fault masking can be maximized. Arow/column scrambling control wordand acontrol columnare used for the control of the scrambling techniques and the data inversion technique, respectively. The problem for determining the control word can be modeled with a bipartite graph. The proposed test and repair techniques can be easily incorporated into the ROM BIST architectures. This makes the proposed techniques more practical to be integrated into current design flow. According to experimental results, the fabrication yield can be improved significantly. Moreover, the incurred hardware overhead and timing penalty are almost negligible.

When the mobile station (MS) is far away from the base station (BS) or terrain and buildings interfere with transmission, the data rate decreases with the increased distance from the BS, and the coverage range of the BS will be shortened to only a few kilometers. The IEEE Working Group has proposed the 802.16j relay technology. This technology can be used to forward data for a BS while overcoming the signal strength attenuation. Since the cost of constructing the relay station is low, the MS will have to scan more than one signal when entering the Mobile Multi-Hop Relay (MMR) network. In this paper, we introduce a novel path selection mechanism that exploits the remaining slot and signal strength indicator (SSI). Since the signal strength will affect the Modulation and Coding Scheme (MCS) combination, we propose to use SSI integrated with the MCS, taking the hop count into account. We demonstrate that our proposed scheme is capable of producing an optimal path selection.

In this paper, efficient built-in self-repair (BISR) techniques for multiple repairable memory cores with different sizes and divided redundancy mechanisms are proposed. Embedded memory cores are first partitioned into memory groups. For each memory group, a redundant memory module is added and divided into row blocks and column blocks. Moreover, the memory cores within a memory group are partitioned into divided arrays (consisting of row/column blocks) of the same size. The redundant memory can be shared among all memory cores within the same memory group. Therefore, unlike the traditional redundancy architectures, a row (column) block is used as the basic replacement element. Based on the proposed redundancy architecture, a heuristic heterogeneous extended spare pivoting redundancy analysis algorithm suitable for built-in implementation is also proposed. Experimental results show that the repair rate and manufacturing yield can be improved significantly due to the efficient usage of redundancy. Moreover, the area overhead of the BISR circuitry for an example memory group consisting of four memory instances of size 9.25 Mbits is only 1.12%.

Wireless Sensor Network (WSN) is still a hottest research topic which can be applied to a lot of new research field such as robotic and smart grid. Its not only used for detecting the new environment but also monitoring any situation which has dynamic variation. However, the sensor node is relied on the battery energy that limited the lifetime of entire network. In this paper, we proposed a novel scheme called Dynamic Duty cycle and Dynamic Schedule Assignment (DDDSA) which not only can reduce number of RTS/CTS (Request to Send / Clear to Send) packets but also dynamically update the Duty Cycle value. Furthermore, the proposed scheme does not calculate the traffic information repeatedly in overlapping areas. This scheme will reduce more idle nodes to achieve energy efficiency.

Current medium access control (MAC) protocols for wireless sensor networks (WSNs) do not support prioritized channel access and often suffer from varying degrees of starvation and fairness problems. That is, with a little bad luck, a sensor node might have to wait arbitrarily long to send its frame, and thus results in the invisibility of some sensed area. In this paper we introduce a simple, but yet well performing starvation free backoff scheme based on sensor MAC (S-MAC) protocol for WSNs. The proposed scheme allows a sensor node to adjust its backoff window size according to its re-transmission times. An analytical analysis is carried out to study the saturation throughput of proposed scheme under backlogged conditions. In addition to the theoretical analysis, simulations were also conducted to analyze the proposed scheme and the results show that our scheme can effectively alleviate the starvation and fairness problem and achieve better performance in high density WSNs.

In realizing cyber-physical systems, research on developing network supported with predictable Quality of Service (QoS) is extremely important. This study exploits heterogeneous networking as communication medium of cyber physical application using a distributed multi-agent scheme (DMAS). The DMAS is based on the concept of cooperation and the awareness algorithm. The proposed scheme is developed for supporting QoS management which consists of a collection of problem-solving agents with three modules: the knowledge source, the in-cloud blackboard system, and the control engine built into the scheme. A set of problem-solving agents autonomously process local tasks and cooperatively interoperate via an in-cloud blackboard system to guarantee QoS. An awareness algorithm, called the Q-learning algorithm, calculates the exceptive rewards of a handoff to all access networks. These rewards are then used by these problem solving agents to determine what to do. Through operations and cooperation among the active agents, a policy is selected and a user-accepted schedule that meets the specified QoS is generated. In addition, to realize actual results, an integrated test-bed emulation network based on NetFPGA-OpenFlow platform is purposed in this paper.

Cognitive Radio (CR) is an innovative wireless sensing technology which can improve efficiency of spectrum usage. Based on CR, Cognitive network (CN) further focus on end-to-end communications for the global optimization and policy enforcement. However, there is a lack of global control channel or middleware for cognitive optimization in CN environment. In this paper, we proposed a Cognitive IP Multimedia Subsystem framework called Cog IMS, which consists of benefits from CN and IP multimedia subsystem (IMS). In this framework, the cognitive optimization is modeled as a service over IMS architecture. By adopting the proposed service-oriented framework, the global optimization is simple to achieve under standardized architecture and the computation requirement is reduced from user to core network. Finally, we simulate wireless users who using services to compare Cog IMS with CN and IMS. The simulation results show that the proposed Cog IMS can achieve the optimization of wireless resource allocation with different network situations.

This study achieves Quality-of-Service (QoS) management in heterogeneous networking using a distributed multi-agent scheme (DMAS) based on the concept of cooperation and the awareness algorithm. The proposed scheme is developed for supporting QoS management in a user-accepted and cost-effective fashion, which consists of a collection of problem-solving agents with three modules: the knowledge source, the in-cloud blackboard system, and the control engine built into the scheme. A set of problem-solving agents autonomously process local tasks and cooperatively interoperate via an in-cloud blackboard system to guarantee QoS. An awareness algorithm, called the Q-learning algorithm, calculates the exceptive rewards of a handoff to all access networks. These rewards are then used by these problem-solving agents to determine what to do. Through operations and cooperation among the active agents, a policy is selected and a user-accepted schedule that meets the specified QoS is generated. Compared with traditional QoS management mechanisms, the proposed DMAS scheme has a 36% lower packet loss ratio in video streaming applications and a 34% lower average delay in VoIP applications with only a minor sacrifice in system computational complexity.

A novel IP Multimedia Subsystem (IMS) framework with cloud computing architecture is proposed for use in high-quality multimedia applications. The IMS supports heterogeneous networking with Quality-of-Service (QoS) policy. MapReduce analysis is also used to enhance cloud computing capability. This architecture enables users to access high-quality multimedia applications via Android-based appliances. In this study, the IMS QoS policies of three wireless access technologies, 3G, WiFi and WiMAX, are integrated in a cloud computing environment to provide different services such as VoIP services and video streaming services. Experimental results indicate that the proposed mechanism improves system performance by allocating resources according to service priority. The proposed architecture also significantly improves system capacity to accommodate numerous users.

Due to Internet Protocol (IP) is the most important protocol in Next Generation Networks. 3GPP utilizes Session Initial Protocol (SIP) based on IP as the base protocol for negotiating sessions in IP Multimedia Subsystem (IMS). Different from traditional circuit-switched network, the media traffic and signaling are delivered through IP transport layer in IMS. The media traffic may affect the signaling efficiency in core network because the traffic collisions and delivery packets in best effort. This paper proposes a novel path-migration mechanism for enhancing the traffic efficiency in IMS. The simulation results show that by adopting proposed path-migration mechanism, the interference and traffic collision can be reduced and the signaling efficiency in core network can be improved.

In this paper we introduce an analytical model to analysis the saturation throughput of SSB algorithm, and then we use this analytical model to find out an optimal value of threshold for SSB algorithm that maximizes the network capacity based on the current channel status. Simulations are conducted to evaluate the performance of SSB protocol. The results confirm that the performance of SSB can be greatly improved by proper choice of the threshold according to the current channel status.

In this paper, an investigation toward mobile P2P architecture brings a new insight to realize future mobile cloud computing systems. Although mobile devices capacity in storing data and running computational process is very limited, the main problem for implementing mobile cloud computing environment is still motivated by the classic issue of information properties query process. Heterogeneous wireless networks (HWNs) architecture then exploited to solve this fundamental problem. The HWNs information properties dispersion model based on coverage area of mobile node aid to simplify the querying process. By HWN and mobile P2P integration a reliable mobile cloud computing service can perform services and resources exchange among peer nodes. In addition this integrated architecture gives the extension of mobile P2P into Network as a Service (NaaS) approach to resource sharing among mobile users.

Geographic Forwarding is part of geographic routing that each node only needs to know the location of its neighbor and the destination. This method can reduce the cost that table-driven routing needs to maintain the whole path even if the path are not in use, and save time when searching the path compared with the reactive routing. When we using geographic forwarding, it usually encountered the local maximum that cannot forward the packet directly to the destination; this fundamental problem is also called "Dead End". We use the algorithm called "A star" that usually used in role playing game or strategic game to detour the terrain that cannot pass through directly. Nodes must vote their agent in a specific area to be a decision-maker to find a reference route for source node. When the route is decided, then we will use geographic forwarding according to this reference path to the destination to avoid the dead end.

This study proposes a novel embedded worldwide interoperability for microwave access (WiMAX)-based vehicular router, with a network mobility architecture, that promotes the Telematics services for ubiquitous/pervasive computing environment anytime and anywhere. Each Telematics user processes the handoff procedure with the mobile Internet protocol mechanism. Hence, the proposed WiMAX-based vehicular router can process multiple Telematics users for handoff procedures simultaneously. This study explores and analyses network performances in terms of packet loss, round-trip time (RTT) and handoff latency. The embedded WiMAX-based vehicular router has a packet loss about 36% lower, and average RTT is approximately 34% lower than the traditional wireless fidelity-based vehicular router. The handoff latency analysis indicates that the embedded WiMAX vehicular router has better performance using the mobile network with the embedded router and more than two Telematics users.

Abstract Radio frequency identification (RFID) is a technology for identifying objects by radio signal. The reader collision problem is caused by the interrogation zones overlap of multiple readers, and leading to incorrect and unreliable data. This study proposes an array‐based reader anti‐collision scheme (ARCS) for solving the reader‐to‐tag interference problem. This mechanism uses array and grouping techniques to schedule the active readers to reduce the read cycle (RC) time. The ‘RC’ and ‘collision ratio (CR)’ measures serve as performance indexes in the proposed scheme. From ‘RC’ comparison, the ARCS mechanism has the maximum improvement of 55 per cent as compared with the existing mechanisms. Furthermore, take ‘CR’ index, ARCS has the maximum improvement of 42 per cent as compared to the others. Copyright © 2008 John Wiley & Sons, Ltd.

Abstract This work proposes a novel middleware architecture for tele‐homecare systems. The proposed architecture is composed of three layers: a device management layer, a data management layer and an application layer. Vital signs sensing is achieved by wired and wireless sensor node integrated with a medical device, or by sensors connected with serial link. Although defined as the software above the medical sensor network, the two‐layer middleware is below the application program that provides a common programming abstraction for tele‐homecare systems. An application,called the Tele‐Homecare Household Monitor System, based on the proposed middleware is implemented and evaluated. The transmission energy costs (the number of messages transmitted in the system) and the average delays caused by aggregation function are compared in two configurations and four different implementations of aggregation function. To increase power efficiency and prolong the system life‐time, the aggregation functions should be implemented on the sensor node of the wireless sensor network if this is feasible. To minimize the message delay, the aggregation functions should be implemented on cluster head. Good message aggregation and filtering significantly reduce the number of messages transmitted and stored in the system, and could translate the sensed readings into useful and meaningful information. Copyright © 2009 John Wiley & Sons, Ltd.

The authors address the problem of providing fair multimedia quality-of-service (QoS) in IEEE 802.11 distributed co-ordination function-based wireless local area networks in the infrastructure mode where mobile hosts experience heterogeneous channel conditions due to mobility and fading effects. It was observed that unequal link qualities can pose significant unfairness of channel sharing, which may thereby lead to the degradation of multimedia QoS performed in adverse conditions. A cross-layer adaptation scheme that provides fair QoS by online adjusting the multidimensional medium access control layer backoff parameters in accordance with the application-layer QoS requirements as well as the physical-layer channel conditions was proposed. The solution is based on an optimisation approach, which utilises neural networks to learn the cross-layer function. Simulation results demonstrate that the proposed adaptation scheme can tackle heterogeneous channel conditions and random joining (or leaving) of hosts to achieve fair QoS in terms of throughput and packet delay.

Although Wireless Local Area Network (WLAN) services are inexpensive and have a high bandwidth, UMTS services provide a larger covered area and high mobility. Based on intelligent deduction, this study presents a novel service scheduling scheme for WLAN/UMTS dual-mode networks. The developed system, Distributed Multi-Agent System (DMAS), consists of a set of problem-solving agents that autonomously process their own tasks and interoperate with each other by a shared database to reach a suitable schedule for dual-mode network services. A two-level control mechanism composed of local-control and meta-control is proposed to achieve a high degree of goodness in service scheduling. Simulation results indicate that the quality of service (QoS) of the proposed discipline in terms of average delay and jitter is better than that of the pure UMTS network by 25% and 10%, respectively. The scheduling discipline can improve the service quality in multiple-mode networks.

Bluetooth is the standard for short range, low power, low cost wireless communication radio technology. Recently, the low price and the small size of the mobile device make a great success in personal mobile communication. Because of the short radio range of Bluetooth technology, when those mobile devices move in the Bluetooth public access network, they will require frequent handoffs. In this study, we propose a new scheme to improve handoff performance for Bluetooth services. This new scheme consists of three procedures: preliminary procedure, handoff procedure, and update procedure. We analyze the Inquiry Scan Interval, Inquiry Scan/spl I.bar/Window, Page/spl I.bar/Scan Interval, and Page Scan Window to reduce the connection delay From the simulation results, it was found that we can get the connection time is 2.3889 seconds and the handoff time is about 15.4 ms. Therefore, the connection time of Bluetooth services is reduced. Finally, we can decrease the handoff delay effectively. Simulation results also show that our new scheme significantly reduces handoff delay.

The use of IP (Internet protocol) technology in the information and communications industry constitutes a major global trend. A highly efficient service architecture, enabling technologies and advanced applications are essential to rapid multimedia services in an all-IPv6 network environment. This work presents an all-IPv6 service platform based on open service architecture (OSA) to support a set of standard interfaces and applications. The all-IPv6 network environment was integrated using a network-processor-based IPv4/IPv6 translator and a mobile router (MR) supported IPv6 network mobility. The feasibility of the open service platform for all-IPv6 network environments and of the designed application programming interfaces was examined using three applications: e-commerce, video-on-demand, and on-line gaming. The performance analysis indicates that the system throughput increased from 10.5 to 60.5 Mb/s as the number of users increased from 1 to 80; the mean response time increased from approximately 1 to 10.5 ms, and the delay time increased from 0.1 to 1 ms.

Because the radio spectrum is limited, managing the limited amount of resources is an important issue, especially for high-speed data applications. This paper presents a distributed multiagent scheme (DMAS) that was developed for supporting resource allocation in a customer-accepted and cost-effective fashion. The scheme consists of a collection of problem-solving agents with three modules built into the scheme: the knowledge source, the blackboard system, and the control engine. Through operations and cooperation among the active agents, an allocation policy is selected and a customer-accepted schedule that meets the specified quality of service (QoS) is generated. A comparison of the performance between the DMAS scheme and other references previously proposed was derived using a 55 microcell model. It was found that the proposed scheme gave the highest quality of service satisfaction (around 90% at light loading and 60% at heavy loading).

To provide cellular data services with differentiated QoS, a shared resource scheme based on the optimization theory and LaGrange /spl lambda/-calculus was developed. This scheme can generate a fair schedule for a diverse mix of traffic with diverse QoS requirements in a limited radio spectrum. We define acceptance indication (AI) as the QoS measurement of the shared resource scheme. The experimental results show that the average acceptance rate of the schedule derived from our approach provides 2.5% higher than those of other existing heuristics.

DS/CDMA has been proposed as a multiple access scheme suitable for future mobile communication systems. CDMA with a conventional matched filter detector is affected by the near-far problem where there are high-powered users. To support the high quality of service in a fading environment, many mechanisms using multi-user detection schemes are proposed. Based on these existing mechanisms and a distributed artificial intelligence technique, we propose a distributed multi-agent scheme to assist CDMA system managers with interference cancellation. The scheme consists of a collection of problem-solving agents, and there are three key modules including knowledge source, blackboard system, and control engine which were built in the scheme. Performance comparisons between our scheme and other heuristics were derived from random traffic patterns. Extensive simulations show that the proposed scheme significantly reduced the bit-error-rate (BER) in CDMA networks and dramatically improves the connection blocking performance.

To support mobility management in a mobile communication environment, a universal browser based ndhu-View management system was designed. Besides the traditional management functions, the ndhu-View system extends to the capabilities of location tracking. Java facilities and SNMP-compatible MIB were defined and utilized to build the ndhu-View interfaces and operations. A /spl pi/-calculus analytical model was developed for bringing out the mobility feature. From the prototype system, the ndhu-View system can achieve a high degree of efficiency in stationary-mobile communication management with extended capabilities and traditional management functions.

Increasing demand for wireless mobile communications coupled with the limited spectrum resources has motivated investigation into alternative efficient and flexible location management solutions. The paper presents a distributed multi-agent mechanism that was developed for supported the location management scheduling in a cost-effective fashion. The mechanism consists of a collection of problem-solving agents, and there are three key modules including knowledge source, blackboard system, and control engine are built in this mechanism. Performance comparisons between our mechanism and other schemes are derived from a real traffic modeling framework. Results show that the proposed mechanism significantly reduces the time for call setup and increases the paging efficiency in wireless mobile communications.