Portable document formats (PDFs) are widely used for document exchange due to their widespread usage and versatility. However, PDFs are highly vulnerable to malware attacks, which pose significant security risks. Exis...
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The health status of the young and middle-aged population has a significant impact on the stable functioning of society. To address the issue of poor prediction accuracy in the current study, the BP neural network (BP...
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The growing demand for cloud computing has made it imperative to optimize the utilization of cloud resources. Resource optimization can be improved through Virtual Machine (VM) Placement. In order to effectively optim...
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Detecting and promptly identifying cracks on road surfaces is of paramount importance for preserving infrastructure integrity and ensuring the safety of road users, including both drivers and pedestrians. Presently, t...
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Understanding and predicting air quality is pivotal for public health and environmental management, especially in urban areas like Delhi. This study utilizes a comprehensive dataset from the Central Pollution Control ...
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This paper investigates an unmanned aerial vehicle(UAV)-assisted multi-object offloading scheme for blockchain-enabled Vehicle-to-Everything(V2X)*** to the presence of an eavesdropper(Eve),the system’s com-munication...
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This paper investigates an unmanned aerial vehicle(UAV)-assisted multi-object offloading scheme for blockchain-enabled Vehicle-to-Everything(V2X)*** to the presence of an eavesdropper(Eve),the system’s com-munication links may be *** paper proposes deploying an intelligent reflecting surface(IRS)on the UAV to enhance the communication performance of mobile vehicles,improve system flexibility,and alleviate eavesdropping on communication *** links for uploading task data from vehicles to a base station(BS)are protected by IRS-assisted physical layer security(PLS).Upon receiving task data,the computing resources provided by the edge computing servers(MEC)are allocated to vehicles for task *** blockchain-based computation offloading schemes typically focus on improving network performance,such as minimizing energy consumption or latency,while neglecting the Gas fees for computation offloading and the costs required for MEC computation,leading to an imbalance between service fees and resource *** paper uses a utility-oriented computation offloading scheme to balance costs and *** paper proposes alternating phase optimization and power optimization to optimize the energy consumption,latency,and communication secrecy rate,thereby maximizing the weighted total utility of the *** results demonstrate a notable enhancement in the weighted total system utility and resource utilization,thereby corroborating the viability of our approach for practical applications.
Thermal images are crucial for object detection in surveillance, security, industrial automation, and vehicular navigation due to their ability to capture heat signatures. However, complexities like low contrast, fluc...
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The dominance of Android in the global mobile market and the open development characteristics of this platform have resulted in a significant increase in *** malicious applications have become a serious concern to the...
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The dominance of Android in the global mobile market and the open development characteristics of this platform have resulted in a significant increase in *** malicious applications have become a serious concern to the security of Android *** address this problem,researchers have proposed several machine-learning models to detect and classify Android malware based on analyzing features extracted from Android ***,most existing studies have focused on the classification task and overlooked the feature selection process,which is crucial to reduce the training time and maintain or improve the classification *** current paper proposes a new Android malware detection and classification approach that identifies the most important features to improve classification performance and reduce training *** proposed approach consists of two main ***,a feature selection method based on the Attention mechanism is used to select the most important ***,an optimized Light Gradient Boosting Machine(LightGBM)classifier is applied to classify the Android samples and identify the *** feature selection method proposed in this paper is to integrate an Attention layer into a multilayer perceptron neural *** role of the Attention layer is to compute the weighted values of each feature based on its importance for the classification *** evaluation of the approach has shown that combining the Attention-based technique with an optimized classification algorithm for Android malware detection has improved the accuracy from 98.64%to 98.71%while reducing the training time from 80 to 28 s.
Message queuing telemetry transport (MQTT) has emerged as the widely adopted application layer protocol for IoT environments because of its lightweight header, minimal power, and bandwidth requirements. Despite its po...
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Message queuing telemetry transport (MQTT) has emerged as the widely adopted application layer protocol for IoT environments because of its lightweight header, minimal power, and bandwidth requirements. Despite its popularity, the earlier version of the protocol, MQTT v3.1.1, encounters performance issues in large-scale implementations and required an update to handle the growing requirements of modern IoT applications. In response to these concerns, MQTT v5.0 was released with several significant features designed to enhance the reliability, user experience, and performance of IoT systems. While the MQTT protocol features were intended to facilitate robust and efficient communications, adversaries could exploit these features to mount various types of attacks in IoT deployments. More specifically, the Denial-of-Service (DoS) attacks toward the MQTT protocol have recently gained a lot of attention from the research community. However, the existing works primarily focus only on exploring the possibilities of misusing the MQTT v3.1.1 protocol features to generate DoS attacks in IoT realms. In this work, we attempt to extensively investigate the advanced protocol features of MQTT v5.0 that can be exploited to launch DDoS attacks impacting the IoT paradigm. We present the first critical evaluation of Distributed DoS (DDoS) attacks on the MQTT v5.0 protocol by analyzing three significant features: 1) CONNECT properties;2) user properties;and 3) flow control. Moreover, we systematically propose attack scenarios based on the adversary’s capabilities, thus illustrating the practicality of proposed attacks in real-world scenarios. Furthermore, we built a real-world testbed for IoT healthcare application to evaluate the severity of the identified attacks. The experimental results demonstrate the effectiveness of these attacks in impacting the availability of guaranteed IoT services to legitimate users, even in times of need. Additionally, we disclose the insightful findings o
This paper centers on leveraging Convolution-Augmented Transformer Models originally designed for Automatic Speech Recognition (ASR) in the realm of Sign Language—specifically, American Sign Language Fingerspelling R...
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