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Towards Securing Machine Learning Models Against Membership Inference Attacks

Computers, Materials & Continua 2022年第3期70卷 4897-4919页

作者： sana Ben Hamida Hichem Mrabet sana belguith Adeeb Alhomoud Abderrazak Jemai Departement of STIC Higher Institute of Technological Studies of GabesGeneral Directorate of Technological StudiesRades2098Tunisia Research Team on Intelligent Machines National Engineering School of GabesGabes UniversityGabes6072Tunisia SERCOM-Lab. Tunisia Polytechnic SchoolCarthage UniversityTunis1054Tunisia Department of IT College of Computing and InformaticsSaudi Electronic UniversityMedina42376Saudi Arabia School of Science Engineering and EnvironmentUniversity of SalfordManchesterM54WTUK Department of Science College of Science and Theoretical StudiesSaudi Electronic UniversityRiyadh11673Saudi Arabia INSAT SERCOM-Lab.Tunisia Polytechnic SchoolCarthage UniversityTunis1080Tunisia

From fraud detection to speech recognition,including price prediction,Machine Learning(ML)applications are manifold and can significantly improve different ***,machine learning models are vulnerable and are exposed to different security and privacy ***,these issues should be addressed while using ML models to preserve the security and privacy of the data *** is a need to secure ML models,especially in the training phase to preserve the privacy of the training datasets and to minimise the information *** this paper,we present an overview of ML threats and vulnerabilities,and we highlight current progress in the research works proposing defence techniques againstML security and privacy *** relevant background for the different attacks occurring in both the training and testing/inferring phases is introduced before presenting a detailed overview of Membership Inference Attacks(MIA)and the related *** this paper,we introduce a countermeasure against membership inference attacks(MIA)on Conventional Neural Networks(CNN)based on dropout and L2 *** experimental analysis,we demonstrate that this defence technique can mitigate the risks of MIA attacks while ensuring an acceptable accuracy of the ***,using CNN model training on two datasets CIFAR-10 and CIFAR-100,we empirically verify the ability of our defence strategy to decrease the impact of MIA on our model and we compare results of five different ***,we present a solution to achieve a trade-off between the performance of themodel and the mitigation of MIA attack.

关键词： Machine learning security and privacy defence techniques membership inference attacks dropout L2 regularization

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Primary Synovial Sarcoma of the Kidney: A Case Report

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Journal of Cancer Therapy 2021年第10期12卷 579-584页

作者： Nouha Ammar Imene Chabchoub Rihab Ben Jaafar Hiba Sboui Makram Hochlef Faten Ezzaairi Sami Sfar Imtinane Belaid Leila Ben Fatma Manel Njim Nadia Bouzid Mohsen belguith Rzig Ahmed Zakhama Abdelfateh Slim Ben Ahmed Medical Onocology Department University Hospital Farhat Hached Sousse Tunisia Pediatric Surgery Department University Hospital Fatouma Bourguiba Monastir Tunisia Anathomopathology Department University Hospital Fatouma Bourguiba Monastir Tunisia Radiotherapy Department University Hospital Farhat Hached Sousse Tunisia Radiology Department University Hospital Fatouma Bourguiba Monastir Tunisia

Synovial sarcoma originating from the kidney is extremely rare. A 13-year-old girl presented with a mild left flank pain of one-week duration, with no associated history of hematuria or any other systemic symptoms. Computed tomography (CT) demonstrated a 6 × 13 × 9 cm mass in the left kidney. No soft tissue or extrarenal masses were identified. The patient received a combined of treatment with doxorubicin and ifosfamide. A radical nephrectomy was performed in the left kidney with no complications. Postoperative pathology revealed post-chemotherapy residue of monophasic spindle cell synovialosarcoma of the left kidney. She received a combined treatment with doxorubicin and ifosfamide in concomittance with external radiation therapy. The patient was re-examined 4 months after surgery. An abdominal and pulmonary CT found no recurrence or metastasis.

关键词： Synovial Sarcoma Kidney

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