Results 151 to 160 of about 4,251 (194)
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Detecting Malicious Queries from Search Engine Traffic
2012 8th International Conference on Wireless Communications, Networking and Mobile Computing, 2012Search Engines not only provides internet users with useful information, but also helps hackers find vulnerable websites to exploit. This paper presents an algorithm that detects malicious queries from search engine traffic. To evaluate our algorithm, we take 3000 queries from Google Hacking Database as seed, and detect malicious queries from Google ...
Daoxin Pan +3 more
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A Method of Malicious Bot Traffic Detection
2019The traditional malicious bot traffic detection technology is usually based on rule matching or statistical analysis, which is not flexible enough and has low detection accuracy. This article systematically analyzes the formation and characteristics of malicious bot traffic.
Mengying Wu +3 more
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OCPP security - Neural network for detecting malicious traffic
Proceedings of the International Conference on Research in Adaptive and Convergent Systems, 2017Because the electric mobility has its focus on eco-friendly means of transport, a distributed platform designed for a smart city environment that can manage the electrical charging stations is vital. One of the major problems of distributed systems and cloud is security.
Adrian Gabriel Morosan, Florin Pop
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AI-Based Malicious Network Traffic Detection in VANETs
IEEE Network, 2018Inherent unreliability of wireless communications may have crucial consequences when safety-critical C-ITS applications enabled by VANETs are concerned. Although natural sources of packet losses in VANETs such as network traffic congestion are handled by decentralized congestion control (DCC), losses caused by malicious interference need to be ...
Nikita Lyamin +3 more
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Detecting Malicious Traffic through Two-phase Machine Learning
Proceedings of the Asia-Pacific Advanced Network, 2015Malicious Internet traffic is increasing with rapidly growing dependence on network technology. Intrusion detection systems (IDSs) are important countermeasure tools for detecting malicious traffic. To deal with the increase in unknown malicious traffic, it is necessary to improve IDS accuracy, which is based on anomaly detection. This study proposes a
Kazuma Shinomiya, Shigeki Goto
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Learning Invariant Representation for Malicious Network Traffic Detection
2016Statistical learning theory relies on an assumption that the joint distributions of observations and labels are the same in training and testing data. However, this assumption is violated in many real world problems, such as training a detector of malicious network traffic that can change over time as a result of attacker's detection evasion efforts ...
Bartos Karel +2 more
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Artificial Intelligence Based Malicious Traffic Detection
2022Lakshmi N. K. Meda, Hamid Jahankhani
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One-Shot Detection of Malicious TLS Traffic
2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD), 2022Gaofeng He +4 more
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Cooperative Detection of Camouflaged Malicious TLS Traffic
2023 Eleventh International Conference on Advanced Cloud and Big Data (CBD), 2023Jingang Wang +5 more
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Malicious traffic detection based on GWO-SVM model
2022 IEEE 4th International Conference on Civil Aviation Safety and Information Technology (ICCASIT), 2022Lechao Liu, Yan Zhuang, Xufei Gao
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