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Jian Wang and Ying Li
Ensuring the security of IoT devices and chips at runtime has become an urgent task as they have been widely used in human life. Embedded memories are vital components of SoC (System on Chip) in these devices. If they are attacked or incur faults at runt...
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Lexin Zhang, Kuiheng Chen, Liping Zheng, Xuwei Liao, Feiyu Lu, Yilun Li, Yuzhuo Cui, Yaze Wu, Yihong Song and Shuo Yan
This study introduces a novel high-accuracy fruit fly detection model based on the Transformer structure, specifically aimed at addressing the unique challenges in fruit fly detection such as identification of small targets and accurate localization agai...
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Salman Ibne Eunus, Shahriar Hossain, A. E. M. Ridwan, Ashik Adnan, Md. Saiful Islam, Dewan Ziaul Karim, Golam Rabiul Alam and Jia Uddin
Accidents due to defective railway lines and derailments are common disasters that are observed frequently in Southeast Asian countries. It is imperative to run proper diagnosis over the detection of such faults to prevent such accidents. However, manual...
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Mingxin Zou, Yanqing Zhou, Xinhua Jiang, Julin Gao, Xiaofang Yu and Xuelei Ma
Field manual labor behavior recognition is an important task that applies deep learning algorithms to industrial equipment for capturing and analyzing people?s behavior during field labor. In this study, we propose a field manual labor behavior recogniti...
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Hao An, Ruotong Ma, Yuhan Yan, Tailai Chen, Yuchen Zhao, Pan Li, Jifeng Li, Xinyue Wang, Dongchen Fan and Chunli Lv
This paper aims to address the increasingly severe security threats in financial systems by proposing a novel financial attack detection model, Finsformer. This model integrates the advanced Transformer architecture with the innovative cluster-attention ...
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Lu Li, Junwang He, Dongxiao Xu, Wen Chen, Jinpei Yu and Huawang Li
Since deep space exploration tasks, such as space gravitational wave detection, put forward increasingly higher requirements for the satellite platform, the scale and complexity of the satellite management unit (SMU) software are also increasing, and the...
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Xiaoyu Tang, Sijia Xu and Hui Ye
In network edge computing scenarios, close monitoring of network data and anomaly detection is critical for Internet services. Although a variety of anomaly detectors have been proposed by many scholars, few of these take into account the anomalies of th...
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Giacomo Gori, Lorenzo Rinieri, Amir Al Sadi, Andrea Melis, Franco Callegati and Marco Prandini
The correct and efficient measurement of security properties is key to the deployment of effective cyberspace protection strategies. In this work, we propose GRAPH4, which is a system that combines different security metrics to design an attack detection...
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Jiaqi Zhao, Ming Xu, Yunzhi Chen and Guoliang Xu
Nowdays, DNNs (Deep Neural Networks) are widely used in the field of DDoS attack detection. However, designing a good DNN architecture relies on the designer?s experience and requires considerable work. In this paper, a GA (genetic algorithm) is used to ...
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Boyu Xie, Qi Su, Beilun Tang, Yan Li, Zhengwu Yang, Jiaoyang Wang, Chenxi Wang, Jingxian Lin and Lin Li
With the advancement in modern agricultural technologies, ensuring crop health and enhancing yield have become paramount. This study aims to address potential shortcomings in the existing chili disease detection methods, particularly the absence of optim...
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Tareq Khan
Wildfires kill and injure people, destroy residences, pollute the air, and cause economic loss. In this paper, a low-power Internet of Things (IoT)-based sensor network is developed, which automatically detects fires in forests and sends the location to ...
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Elena Fedorchenko, Evgenia Novikova and Anton Shulepov
In order to provide an accurate and timely response to different types of the attacks, intrusion and anomaly detection systems collect and analyze a lot of data that may include personal and other sensitive data. These systems could be considered a sourc...
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Chunxian Wang, Xiaoxing Wang, Yiwen Wang, Shengchao Hu, Hongyang Chen, Xuehai Gu, Junchi Yan and Tao He
Neural architecture search (NAS) is a popular branch of automatic machine learning (AutoML), which aims to search for efficient network structures. Many prior works have explored a wide range of search algorithms for classification tasks, and have achiev...
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Florin Dumitrescu, Bogdan Ceachi, Ciprian-Octavian Truica, Mihai Trascau and Adina Magda Florea
Space Surveillance and Tracking is a task that requires the development of systems that can accurately discriminate between natural and man-made objects that orbit around Earth. To manage the discrimination between these objects, it is required to analyz...
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Shahriar Shakir Sumit, Dayang Rohaya Awang Rambli, Seyedali Mirjalili, Muhammad Mudassir Ejaz and M. Saef Ullah Miah
Human detection is a special application of object recognition and is considered one of the greatest challenges in computer vision. It is the starting point of a number of applications, including public safety and security surveillance around the world. ...
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Dong-Han Mo, Yi-Ching Wu and Chern-Sheng Lin
Through artificial intelligence optical autonomous drones (UAV) can detect cracks. It avoids terrain collapse, maintains intact geographic features, and warns people to protect their lives. It can solve the neglect of human eye detection and the collapse...
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Yufan Zeng and Jiashan Tang
Graph neural networks (GNNs) have been very successful at solving fraud detection tasks. The GNN-based detection algorithms learn node embeddings by aggregating neighboring information. Recently, CAmouflage-REsistant GNN (CARE-GNN) is proposed, and this ...
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Sepehr Honarparvar, Sara Saeedi, Steve Liang and Jeremy Squires
Emerging deep learning (DL) approaches with edge computing have enabled the automation of rich information extraction, such as complex events from camera feeds. Due to the low speed and accuracy of object detection, some objects are missed and not detect...
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Klaus Kammerer, Manuel Göster, Manfred Reichert and Rüdiger Pryss
A deep understanding about a field of research is valuable for academic researchers. In addition to technical knowledge, this includes knowledge about subareas, open research questions, and social communities (networks) of individuals and organizations w...
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Arthur Fournier, Franjieh El Khoury and Samuel Pierre
The rapid adoption of Android devices comes with the growing prevalence of mobile malware, which leads to serious threats to mobile phone security and attacks private information on mobile devices. In this paper, we designed and implemented a model for m...
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