Zobrazeno 1 - 10
of 160
pro vyhledávání: '"Kangfeng Zheng"'
Publikováno v:
Sensors, Vol 24, Iss 11, p 3481 (2024)
Malicious social bots pose a serious threat to social network security by spreading false information and guiding bad opinions in social networks. The singularity and scarcity of single organization data and the high cost of labeling social bots have
Externí odkaz:
https://doaj.org/article/806198b5b399419dbd9c98b1aa9aa694
Publikováno v:
Buildings, Vol 14, Iss 5, p 1217 (2024)
The interfacial bonding capacity between cement emulsified asphalt composite binder (CEACB) and reclaimed asphalt pavement (RAP) plays a critical role in improving the pavement performance of cold recycled asphalt emulsion mixtures (CRAEMs). This stu
Externí odkaz:
https://doaj.org/article/8fce340b6f744cffbca7c968d4bc3b11
Publikováno v:
IEEE Access, Vol 8, Pp 21077-21090 (2020)
Vehicular Ad-hoc Network (VANET) is a significant component of intelligent transportation system, which facilitates vehicles to share sensitive information and corporate with others. However, due to its unique characteristics, such as openness, dynam
Externí odkaz:
https://doaj.org/article/52be92ba998f4402b4acfc81dfa58658
Publikováno v:
IEEE Access, Vol 8, Pp 73127-73141 (2020)
In recent years, machine learning-based intrusion detection systems (IDSs) have proven to be effective; especially, deep neural networks improve the detection rates of intrusion detection models. However, as models become more and more complex, peopl
Externí odkaz:
https://doaj.org/article/074f50827cb44703ad1e61ca14e9b565
Publikováno v:
IEEE Access, Vol 8, Pp 36664-36680 (2020)
The detection and removal of malicious social bots in social networks has become an area of interest in industry and academia. The widely used bot detection method based on machine learning leads to an imbalance in the number of samples in different
Externí odkaz:
https://doaj.org/article/89c068d5358e4ec29473a9393e8363ac
Publikováno v:
IEEE Access, Vol 8, Pp 42169-42184 (2020)
To explore the advantages of adversarial learning and deep learning, we propose a novel network intrusion detection model called SAVAER-DNN, which can not only detect known and unknown attacks but also improve the detection rate of low-frequent attac
Externí odkaz:
https://doaj.org/article/4df61ebceb634c46a85420475dbf87a0
Publikováno v:
Tongxin xuebao, Vol 40, Pp 124-137 (2019)
Aiming at the problems existing in the application of machine learning algorithm,an optimization system of the machine learning model based on the heuristic algorithm was constructed.Firstly,the existing types of heuristic algorithms and the modeling
Externí odkaz:
https://doaj.org/article/8a65648daff541ea870116d1691afc00
Publikováno v:
Applied Sciences, Vol 12, Iss 21, p 11298 (2022)
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 E
Externí odkaz:
https://doaj.org/article/06dad479af4948db9fc12d9822881f26
Publikováno v:
Sensors, Vol 22, Iss 17, p 6627 (2022)
In order to improve user authentication accuracy based on keystroke dynamics and mouse dynamics in hybrid scenes and to consider the user operation changes in different scenes that aggravate user status changes and make it difficult to simulate user
Externí odkaz:
https://doaj.org/article/ef5b3e3e59ff41f8b325d5edb8a92a22
Publikováno v:
IEEE Access, Vol 7, Pp 26218-26228 (2019)
Keystroke biometrics is a well-investigated dynamic behavioral methodology that utilizes the unique behavioral patterns of users to verify their identity when tapping keys. However, the performance of keystroke biometrics is unreliable due to its hig
Externí odkaz:
https://doaj.org/article/acbf6e72c4924d63a111f21e76ecd0ed