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Saikat Das, Mohammad Ashrafuzzaman, Frederick T. Sheldon and Sajjan Shiva
The distributed denial of service (DDoS) attack is one of the most pernicious threats in cyberspace. Catastrophic failures over the past two decades have resulted in catastrophic and costly disruption of services across all sectors and critical infrastru...
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Kanza Gulzar, Muhammad Ayoob Memon, Syed Muhammad Mohsin, Sheraz Aslam, Syed Muhammad Abrar Akber and Muhammad Asghar Nadeem
In the public health sector and the field of medicine, the popularity of data mining and its usage in knowledge discovery and databases (KDD) are rising. The growing popularity of data mining has discovered innovative healthcare links to support decision...
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Tianhao Hou, Hongyan Xing, Xinyi Liang, Xin Su and Zenghui Wang
Marine sensors are highly vulnerable to illegal access network attacks. Moreover, the nation?s meteorological and hydrological information is at ever-increasing risk, which calls for a prompt and in depth analysis of the network behavior and traffic to d...
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Xue Jun Li, Maode Ma and Yihan Sun
Modern smart grids are built based on top of advanced computing and networking technologies, where condition monitoring relies on secure cyberphysical connectivity. Over the network infrastructure, transported data containing confidential information, mu...
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Merve Ozkan-Okay, Refik Samet, Ömer Aslan, Selahattin Kosunalp, Teodor Iliev and Ivaylo Stoyanov
The fast development of communication technologies and computer systems brings several challenges from a security point of view. The increasing number of IoT devices as well as other computing devices make network communications more challenging. The num...
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Cristian González García and Eva Álvarez-Fernández
Big Data has changed how enterprises and people manage knowledge and make decisions. However, when talking about Big Data, so many times there are different definitions about what it is and what it is used for, as there are many interpretations and disag...
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Maya Hilda Lestari Louk and Bayu Adhi Tama
As a system capable of monitoring and evaluating illegitimate network access, an intrusion detection system (IDS) profoundly impacts information security research. Since machine learning techniques constitute the backbone of IDS, it has been challenging ...
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Vikas Tomer and Sachin Sharma
Malicious attacks are becoming more prevalent due to the growing use of Internet of Things (IoT) devices in homes, offices, transportation, healthcare, and other locations. By incorporating fog computing into IoT, attacks can be detected in a short amoun...
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D.A. Safronov,Y.D. Kazer,K.S. Zaytsev
Pág. 39 - 45
The purpose of this work is to reduce the cost of troubleshooting digital equipment by improving anomaly recognition methods based on the use of autoencoders. To do this, the authors propose to use two types of autoencoders: a deep feed-forward autoencod...
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Yanping Shen, Kangfeng Zheng, Yanqing Yang, Shuai Liu and Meng Huang
Various machine-learning methods have been applied to anomaly intrusion detection. However, the Intrusion Detection System still faces challenges in improving Detection Rate and reducing False Positive Rate. In this paper, a Class-Level Soft-Voting Ensem...
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