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A Rankable Boolean Searchable Encryption Scheme Supporting Dynamic Updates in a Cloud Environment
IEEE Access, 2023 At present, three problems exist in searchable encryption in cloud storage services: firstly, most traditional searchable encryption schemes only support single-keyword search while fail to perform Boolean searches; even if a few schemes support Boolean ...
Sixu Guo +4 more
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An Effective Cost-Sensitive XGBoost Method for Malicious URLs Detection in Imbalanced Dataset
IEEE Access, 2021 Imbalanced class has been a common problem encountered in the modeling process, and has attracted more and more attention from scholars. Biased classifiers, which limit the classifiers’ performance for minority classes, will be produced if the ...
Shen He +4 more
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IEEE Access, 2023 Existing secure two-party Euclidean distance computation schemes are mostly performed based on a semi-honest model, which faces bottlenecks in computation efficiency and security. In view of this, this study proposed a secure two-party euclidean distance
Li Su, Huizheng Geng, Sixu Guo, Shen He
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Multi-semantic feature fusion attention network for binary code similarity detection
Scientific Reports, 2023 Binary code similarity detection (BCSD) plays a big role in the process of binary application security test. It can be applied in several fields, such as software plagiarism detection, malware analysis, vulnerability detection.
Bangling Li +8 more
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Enhancing Mobile Learning Security [PDF]
International Journal on Integrating Technology in Education, 2016 Mobile devices have been playing vital roles in modern dayeducation delivery as students can access or download learning materials on their smartphones and tablets, they can also install educational apps and study anytime, anywhere. The need to provide adequate security forportable devices being used for learning cannot be underestimated. In this paper,
Shonola, Shaibu A., Joy, Mike
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FLPP: A Federated-Learning-Based Scheme for Privacy Protection in Mobile Edge Computing
Entropy, 2023 Data sharing and analyzing among different devices in mobile edge computing is valuable for social innovation and development. The limitation to the achievement of this goal is the data privacy risk.
Zhimo Cheng +5 more
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Entropy, 2023 The increasing demand for end-to-end low-latency and high-reliability transmissions between edge computing nodes and user elements in 5G Advance edge networks has brought new challenges to the transmission of data. In response, this paper proposes LERMS,
Zhongfu Guo +7 more
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Explainable Machine Learning for Default Privacy Setting Prediction
IEEE Access, 2021 When requesting a web-based service, users often fail in setting the website’s privacy settings according to their self privacy preferences. Being overwhelmed by the choice of preferences, a lack of knowledge of related technologies or unawareness
Sascha Lobner +3 more
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Interlayer Chemical Modulation of Phase Transitions in Two-Dimensional Metal Chalcogenides
Molecules, 2023 Two-dimensional metal chalcogenides (2D-MCs) with complex interactions are usually rich in phase transition behavior, such as superconductivity, charge density wave (CDW), and magnetic transitions, which hold great promise for the exploration of exciting
Zhi Zhang +5 more
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Privacy-Preserving Task-Matching and Multiple-Submissions Detection in Crowdsourcing
Sensors, 2021 Crowdsourcing enables requesters to publish tasks to a platform and workers are rewarded for performing tasks of interest. It provides an efficient and low-cost way to aggregate data and solve problems that are difficult for computers but simple for ...
Jie Xu, Zhaowen Lin, Jun Wu
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