In the field of text recognition models, existing adversarial attack algorithms mainly target white-box scenarios, which are usually limited to single-color backgrounds and short text length. However, withthe complex...
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Automatic modulation recognition (AMR) is a crucial task in intelligent receiver systems, with significant applications in both civilian and military scenarios. Deep learning-based modulation recognition algorithms ha...
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作者:
Ramkumar, G.
Saveetha University Department of Ece Chennai India
Phishing attacks pose a huge threat for online security and therefore need advanced detecting techniques in order to mitigate the damages it causes. this paper introduces a sophisticated model for the detection of phi...
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ISBN:
(纸本)9798350379945
Phishing attacks pose a huge threat for online security and therefore need advanced detecting techniques in order to mitigate the damages it causes. this paper introduces a sophisticated model for the detection of phishing websites, named the Blended ResNet-EfficientNet Model (BREM), which unifies the advantages of the ResNet and EfficientNet architectures. To address this challenge, BREM uses the rich hierarchical patternrecognition ability of ResNet-50 and the practical feature extraction capability of EfficientNet-B3 to achieve classification performance in phishing detection. On overall assessment BREM outperforms both traditional machinelearning models and standalone deep learning model with an accuracy of 96%, precision at 94%, recall of 95% and FI score of 94.5%. these same authors validate the high specificity (97 %), negative predictive value (95 %) and Matthews correlation coefficient of 0.92 further underlining the robustness and reliability of BREM. this approach does not only improve the accuracy of detection, but also provides much better security against phishing campaigns. In the near future research directions such as real-time deployment, more experiments on different feature sets, adversarial robustness, transfer learning from heterogeneous datasets, model learning models and patternrecognition. they are able to draw from an immense amount of data and address minor deviances, which allows AI's better discrimination of real versus false websites, therefore increasing user cyber protections and preventable breaches [3] [4]. At the heart of securing phishing websites identification is making use of powerful AI capabilities to scan and recognize phishing convincingly. this AI utilizes different methods - natural language processing (NLP), image recognition and behavioral analysis - to keep an eye on things happening to web content and its design. Behavior analysis tracks user-interactions and web behavior to detect for abnormal operations, which co
Offline reinforcement learning (RL) addresses the challenge of expensive and high-risk data exploration inherent in RL by pre-training policies on vast amounts of offline data, enabling direct deployment or ...
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machinelearning approaches for lung respiratory sound identification and categorization have increased in study. Transfer learning uses pre-trained models to extract relevant attributes from input data, one of the mo...
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In today's world, rapid global development has improved living standards but also led to a significant rise in waste generation, posing challenges for waste management systems. To address this issue, integrating s...
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In the dynamic world of technology, the fusion of biometrics and artificial intelligence has ushered in an unprecedented era marked by convenience, security, and cutting-edge innovation. Biometrics, the science of usi...
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ISBN:
(纸本)9798350327328
In the dynamic world of technology, the fusion of biometrics and artificial intelligence has ushered in an unprecedented era marked by convenience, security, and cutting-edge innovation. Biometrics, the science of using unique physical or behavioral attributes for identification and authentication, has seamlessly merged into daily routines. From unlocking smartphones with a fingerprint to clearing airport security with facial recognition, biometrics has transformed the way people interact with technology and the world. Simultaneously, Generative AI, powered by machinelearning models, has unlocked new frontiers in generating remarkably realistic synthetic data, including human faces, voices, and fingerprints. this convergence of biometrics and Generative AI lies at the heart of a complex and rapidly evolving landscape, giving rise to profound questions concerning individual privacy and security. this study examines the correlation between demographic factors like age, gender, educational background, technological competence, and the regularity of employing biometric authentication, and their awareness about biometric technologies. Additionally, this research explores concerns regarding the potential misuse of biometric data and the notion that organizations should seek explicit consent before collecting such data. Lastly, it assesses the awareness of potential privacy risks and the belief that individuals should receive education regarding the utilization of their biometric data in AI systems. Descriptive research design has been used in this study. the first section of the questionnaire using Microsoft Forms covers the demographic factors, technological proficiency and frequency of using biometric authentication (e.g., fingerprint, facial recognition). the next section focuses on awareness and usage of biometric technologies, biometric privacy, trust, education, awareness of biometrics, generative AI and deepfakes using the Likert Scale. 53 samples were obtained th
In recent years, withthe rapid development of brain science and information science, affective Brain Computer Interfaces (aBCI) have become a hot topic. EEG signals which record the electrical activity of neurons in ...
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Raveling on asphalt surfaces can lead to the occurrence of diseases such as loose potholes on the road surface. Monitoring and real-time warning of the development status of pavement raveling helps formulate road main...
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Crime is considered an intended execution of an act that is harmful to society and punishable under criminal law. Bangladesh as a developing country has experienced severe crime-related issues in recent years due to t...
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