Access to information about the activities of the Security Service of Ukraine in the context of countering disinformation by A. I. Marushchak, N. O. Kudriavtseva

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Blockchain applications in managing oral oncology patient data: Privacy, security, and beyond by Meenakshi Singh, Dipti Vashisth Sharma, Sandeep Lahu Sarkale, Sachin Chavan

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Application research on network security operation automation practice based on RPA technology by ZHOU Ying

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VIRTUAL REALITY: U.S. INFORMATION SECURITY THREATS CONCEPT AND ITS INTERNATIONAL DIMENSION by E. V. Batueva

Subjects: “…information security…”
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Research on endogenous security data sharing mechanism of F-RAN for 6G by Yang LIU, Jun LI, Wenyun CHEN, Mugen PENG

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Multi-source data security protection of smart grid based on combination key by Jian GAO, Wenbin CHEN, Jianmin PANG, Huadong YU, Guorui SONG

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ENVIRONMENTAL EXTREMISM AS A NEW CHALLENGE OF ECONOMIC SECURITY OF INDUSTRIAL ORGANIZATIONS IN RUSSIA by A. Savin

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Efficient and secure multi-user outsourced image retrieval scheme with access control by Fuyuan SONG, Zheng QIN, Jixin ZHANG, Yu LIU

“…In the cloud-based image retrieval services, the cloud server may not be fully trusted in which may arise privacy concerns.Some privacy-preserving image retrieval schemes have been proposed to protect image privacy.However, the traditional privacy-preserving image retrieval schemes have some weaknesses, such as inefficient and single-user setting.Therefore, an efficient and secure multi-user outsourced image retrieval (EMIR) scheme with access control was proposed.EMIR utilized matrix decomposition and proxy re-encryption to achieve multi-user outsourced image retrieval.By leveraging the techniques of one-time pad and matrix transformation, EMIR supported efficient and secure image retrieval based on Euclidean distance similarity in a privacy-preserving manner.In addition, EMIR applied locality sensitive hashing (LSH) to build searchable indexes in a privacy-preserving manner, which could improve the image retrieval performance.Specifically, a lightweight access control strategy by using role-based polynomial function was designed to authorize the legality of the query user.Security analysis shows that EMIR can protect the confidentiality of the images and the queries.The extensive experiments demonstrate that EMIR achieves efficient image retrieval.…”
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Goodness-of-Fit Based Secure Cooperative Spectrum Sensing for Cognitive Radio Network by Hiep Vu-Van, Insoo Koo

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The Effect of HIV/AIDS Scourge on Food Security in Nyabbani Subcounty, Kitagwenda District. by Ainembabazi, Docus

“…The purpose of this research was to assess, analyze, find out, and gather the effect of HIV/AIDS scourge on food security in Nyabbani sub-county, Kitagwenda district.…”
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Impact of Climate Change on Food Security in Kashare Sub-County, Mbarara District. by Agaba, Richard

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Impact of Climate Change on Food Security in Kashare Sub-County Mbarara District. by Agaba, Richard

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Transport Systems Tracking and Inventory Security: A Case of Mega Bakery, Kabale. by Ntaribi, Elijah

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School of English for Applied Economics by L. K. Raitskaya

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Empirical and methodological foundations on the impact of climate-smart agriculture on food security studies: Review by Girma Tilahun, Amare Bantider, Desalegn Yayeh

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New time-frequency method of harmonic signal extraction in chaotic secure communication system by WANG Er-fu, WANG Dong-qing, DING Qun

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Defending against social engineering attacks: A security pattern‐based analysis framework by Tong Li, Chuanyong Song, Qinyu Pang

“…IET Information Security…”
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Secure and high throughput routing protocol with QoS constraints in cognitive wireless Mesh networks by Zhu-fang KUANG, Zhi-gang CHEN, Guo-jun WANG, Hui LIU

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Cyber security entity recognition method based on residual dilation convolution neural network by Bo XIE, Guowei SHEN, Chun GUO, Yan ZHOU, Miao YU

“…In recent years,cybersecurity threats have increased,and data-driven security intelligence analysis has become a hot research topic in the field of cybersecurity.In particular,the artificial intelligence technology represented by the knowledge graph can provide support for complex cyberattack detection and unknown cyberattack detection in multi-source heterogeneous threat intelligence data.Cybersecurity entity recognition is the basis for the construction of threat intelligence knowledge graphs.The composition of security entities in open network text data is very complex,which makes traditional deep learning methods difficult to identify accurately.Based on the pre-training language model of BERT (pre-training of deep bidirectional transformers),a cybersecurity entity recognition model BERT-RDCNN-CRF based on residual dilation convolutional neural network and conditional random field was proposed.The BERT model was used to train the character-level feature vector representation.Combining the residual convolution and the dilation neural network model to effectively extract the important features of the security entity,and finally obtain the BIO annotation of each character through CRF.Experiments on the large-scale cybersecurity entity annotation dataset constructed show that the proposed method achieves better results than the LSTM-CRF model,the BiLSTM-CRF model and the traditional entity recognition model.…”
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National, International and Legal Mechanisms of Control over the Activity of Non-Government Security Entities by M. V. Zavalnyi

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