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Ensuring data confidentiality via plausibly deniable encryption and secure deletion-a survey

Cybersecurity 2018年第1期1卷 106-125页

作者： Qionglu Zhang Shijie Jia Bing Chang Bo Chen Data Assurance and Communication Security Research Center Chinese Academy of SciencesBeijingChina State Key Laboratory of Information Security Institute of Information EngineeringChinese Academy of SciencesBeijingChina School of Cyber Security University of Chinese Academy of SciencesBeijingChina School of Information Systems Singapore Management UniversitySingaporeSingapore Department of Computer Science Michigan Technological UniversityHoughtonUSA

Ensuring confidentiality of sensitive data is of paramount importance,since data leakage may not only endanger data owners’privacy,but also ruin reputation of businesses as well as violate various regulations like HIPPA and Sarbanes-Oxley *** provide confidentiality guarantee,the data should be protected when they are preserved in the personal computing devices(i.e.,confidentiality during their lifetime);and also,they should be rendered irrecoverable after they are removed from the devices(i.e.,confidentiality after their lifetime).Encryption and secure deletion are used to ensure data confidentiality during and after their lifetime,*** work aims to perform a thorough literature review on the techniques being used to protect confidentiality of the data in personal computing devices,including both encryption and secure *** for encryption,we mainly focus on the novel plausibly deniable encryption(PDE),which can ensure data confidentiality against both a coercive(i.e.,the attacker can coerce the data owner for the decryption key)and a non-coercive attacker.

关键词： Data confidentiality Plausibly deniable encryption Secure deletion

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Initial ASEAN digital security and interoperability standard proposal

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AIP Conference Proceedings 2023年第1期2739卷

作者： Sangsuree Vasupongayya Gunawan Hutagalung Obrina Candra Chalee Vorakulpipat Doni Purnomo Parinda Wattanasri Eko Supriyanto Shukor Abd Razak Othman Ibrahim Anazida Zainal Sri Devi Ravana Hiep Cong Pham Tharith Sriv Daw Khin Myo Su Mora Hertanto Agus Winarno Prabaswari Raden Muhammad Taufik Yuniantoro Badrus Zaman Fatmawati Retna Apsari Yutika Amelia Effendi Norjihan Abdul Ghani Zarina Shukur Hamidah Ibrahim Nur Izura Udzir Marnel Peradilla Jude Michael Teves Nestor Michael Tiglao Cenon Alfonso Pg Emeroylariffion Abas Mueen Uddin Agustin Kusumayati Brian Sri Prahastuti Department of Computer Engineering Faculty of Engineering Prince of Songkla University Hatyai Songkhla 90110 THAILAND Directorate General of Post and Information Technology Ministry of Communication and Information Technology Jakarta INDONESIA Politeknik Siber dan Sandi Negara National Cyber & Crypto Agency (BSSN) Depok West Java INDONESIA Information Security Research Team at National Electronics and Computer Technology Center Bangkok THAILAND National Standardization Agency of Indonesia Jakarta INDONESIA Department of Disease Control Ministry of Public Health Mueang Nonthaburi Nonthaburi THAILAND School of Biomedical Engineering and Health Sciences Faculty of Engineering Universiti Teknologi Malaysia Johor Bahru Johor MALAYSIA IJN-UTM Cardiovascular Engineering Center Institute of Human Centered Engineering Universiti Teknologi Malaysia Johor Bahru Johor MALAYSIA School of Computing Faculty of Engineering Universiti Teknologi Malaysia Johor Bahru Johor MALAYSIA Faculty of Computer Science & Information Technology Universiti Malaya Kuala Lumpur MALAYSIA RMIT University Vietnam Ho Chi Minh City VIETNAM Royal University of Phnom Penh Phnom Penh CAMBODIA Yangon University of Economics Yangon MYANMAR Agency for the Assessment and Application of Technology (BPPT) Jakarta INDONESIA Faculty of Science and Technology Universitas Airlangga Surabaya East Java INDONESIA Faculty of Advanced Technology and Multidiscipline Universitas Airlangga Surabaya East Java INDONESIA Centre for Cyber Security Universiti Kebangsaan Malaysia Bangi Selangor MALAYSIA Faculty of Computer Science and Information Technology Universiti Putra Malaysia Serdang Selangor MALAYSIA Computer Technology Department College of Computer Studies De La Salle University Manila PHILIPPINES Software Technology Department College of Computer Studies De La Salle University Manila PHILIPPINES Electrical and Electronics Engineering Institute University of the Philippines Diliman Quezon City P

In this work, the result of the initial attempt to propose an Association of Southeast Asian Nations (ASEAN) digital security and interoperability standard to support the mobility among ASEAN countries is presented. Literature reviews on existing coronavirus disease 2019 (COVID-19) related digital technologies of six ASEAN member countries are conducted. Several concerns related to creating/implementing the ASEAN digital security and interoperability standard are discussed including the technology accessing concern, the data security and privacy concern, and the data interoperability and availability concern. The proposed solution toward creating an ASEAN digital security and interoperability standard is then presented. To evaluate the proposed solution, a survey has been conducted on representatives of nine ASEAN countries on four main issues including the security standards and requirements, the interoperability standard and requirements, the certifications, and the implementation challenges. According to the survey and the discussion, seven recommendations were proposed toward creating an ASEAN digital security and interoperability standard. First, each country collects and maintains the data of its own citizens and also provides a method to authenticate and access the data by authorized requests. Second, QR code standard or ASEAN QR code standard must be agreed upon so that it can be authenticated and verified by ASEAN countries. Third, health risk assessment must be agreed upon to be used. Forth, the security standard, the data, the data format and the exchange protocol must be agreed upon at the ASEAN policy level while adoption of international standards as an implementation guideline will ease of the process and neutralize different requirements from various countries. Fifth, any accountability of incidents must be agreed upon at the ASEAN policy level. Sixth, certification might be extended to certification of risk assessment for organizations, products or

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A Novel Fine-Grained Method for Vehicle Type Recognition Based on the Locally Enhanced PCANet Neural Network

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Journal of computer science & Technology 2018年第2期33卷 335-350页

作者： Qian Wang You-Dong Ding School of Computer Enqineering and Science Shan qhai University Shanqhai 200072 China Information Center Criminal Investigation Department of Shanghai Public Security Bureau Shanghai 200083 China Shanghai Engineering Research Center of Motion Picture Special Effects Shanghai 200072 China Shanghai Film Academy Shanghai University Shanghai 200072 China

In this paper, we propose a locally enhanced PCANet neural network for fine-grained classification of vehicles. The proposed method adopts the PCANet unsupervised network with a smaller number of layers and simple parameters compared with the majority of state-of-the-art machine learning methods. It simplifies calculation steps and manual labeling, and enables vehicle types to be recognized without time-consuming training. Experimental results show that compared with the traditional pattern recognition methods and the multi-layer CNN methods, the proposed method achieves optimal balance in terms of varying scales of sample libraries, angle deviations, and training speed. It also indicates that introducing appropriate local features that have different scales from the general feature is very instrumental in improving recognition rate. The 7-angle in 180° （12-angle in 360°） classification modeling scheme is proven to be an effective approach, which can solve the problem of suffering decrease in recognition rate due to angle deviations, and add the recognition accuracy in practice.

关键词： fine-grained classification PCANet local enhancement vehicle type recognition

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Improved meet-in-the-middle attacks on reduced-round Piccolo

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science China(information sciences) 2018年第3期61卷 95-107页

作者： Ya LIU Liang CHENG Zhiqiang LIU Wei LI Qingju WANG Dawu GU Department of Computer Science and Engineering University of Shanghai for Science and Technology State Key Laboratory of Cryptology Department of Computer Science and Engineering Shanghai Jiao Tong University School of Computer Science and Technology Donghua University Shanghai Key Laboratory of Integrated Administration Technologies for Information Security Department of Applied Mathematics and Computer Science Technical University of Denmark

Piccolo is a lightweight block cipher that adopts a generalized Feistel network structure with4 branches, each of which is 16 bit long. The key length is 80 or 128 bit, denoted by Piccolo-80 and Piccolo-128, respectively. In this paper, we mounted meet-in-the-middle attacks on 14-round Piccolo-80 without preand post-whitening keys and 18-round Piccolo-128 with post-whitening keys by exploiting the properties of the key schedule and Maximum Distance Separable（MDS） matrix. For Piccolo-80, we first constructed a 5-round distinguisher. Then 4 rounds and 5 rounds were appended at the beginning and at the end,respectively. Based on this structure, we mounted an attack on 14-round Piccolo-80 from the 5 th round to the 18 th round. The data, time, and memory complexities were 252chosen plaintexts, 267.44encryptions, and 264.91blocks, respectively. For Piccolo-128, we built a 7-round distinguisher to attack 18-round Piccolo-128 from the 4 th round to the 21st round. The data, time, and memory complexities were 252chosen plaintexts,2126.63encryptions, and 2125.29blocks, respectively. If not considering results on biclique cryptanalysis,these are currently the best public results on this reduced version of the Piccolo block cipher.

关键词： block cipher lightweight Piccolo meet-in-the-middle attack distinguisher

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Data sharing and privacy for patient IoT devices using blockchain 7th

Data sharing and privacy for patient IoT devices using block...

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7th International Conference on Smart City and Informatization, iSCI 2019

作者： Srivastava, Gautam Parizi, Reza M. Dehghantanha, Ali Choo, Kim-Kwang Raymond Department of Mathematics and Computer Science Brandon University BrandonMBR7A 6A9 Canada Research Center for Interneural Computing China Medical University Taichung40402 Taiwan College of Computing and Software Engineering Kennesaw State University KennesawGA30144 United States Cyber Science Lab School of Computer Science University of Guelph GuelphONN1G 2W1 Canada Department of Information Systems and Cyber Security University of Texas at San Antonio San AntonioTX78249 United States

ISBN: (纸本)9789811513008

Once a fitness fad, wearable and other related Internet of Things (IoT) devices are fast becoming common place in many different smart city applications such as healthcare. However, IoT devices, particularly inexpensive devices, often trade security and privacy for usability. One solution to protect privacy in the healthcare domain which has begun to be explored is blockchain-based technology. However, there are a number of limitations underpinning the use of blockchain, which limits its adoption particularly in applications that require low energy and computational footprints. In this paper, we present a transactional protocol for remote patient monitoring using directed acyclic graphs. We use a newer blockchain protocol called GHOSTDAG in both a public blockchain and a private blockchain. Our novel proposed solution aims to resolve known security issues for healthcare, without affecting scalability (a feature of classic blockchain architecture). © Springer Nature Singapore Pte Ltd. 2019.

关键词： Internet of things

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DPHL:A DIA Pan-human Protein Mass Spectrometry Library for Robust Biomarker Discovery

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Genomics, Proteomics & Bioinformatics 2020年第2期18卷 104-119页

作者： Tiansheng Zhu Yi Zhu Yue Xuan Huanhuan Gao Xue Cai Sander R.Piersma Thang V.Pham Tim Schelfhorst Richard R.G.D.Haas Irene V.Bijnsdorp Rui Sun Liang Yue Guan Ruan Qiushi Zhang Mo Hu Yue Zhou Winan J.Van Houdt Tessa Y.S.Le Large Jacqueline Cloos Anna Wojtuszkiewicz Danijela Koppers-Lalic Franziska Bottger Chantal Scheepbouwer Ruud H.Brakenhoff Geert J.L.H.van Leenders Jan N.M.Ijzermans John W.M.Martens Renske D.M.Steenbergen Nicole C.Grieken Sathiyamoorthy Selvarajan Sangeeta Mantoo Sze S.Lee Serene J.Y.Yeow Syed M.F.Alkaff Nan Xiang Yaoting Sun Xiao Yi Shaozheng Dai Wei Liu Tian Lu Zhicheng Wu Xiao Liang Man Wang Yingkuan Shao Xi Zheng Kailun Xu Qin Yang Yifan Meng Cong Lu Jiang Zhu Jin'e Zheng Bo Wang Sai Lou Yibei Dai Chao Xu Chenhuan Yu Huazhong Ying Tony K.Lim Jianmin Wu Xiaofei Gao Zhongzhi Luan Xiaodong Teng Peng Wu Shi'ang Huang Zhihua Tao Narayanan G.Iyer Shuigeng Zhou Wenguang Shao Henry Lam Ding Ma Jiafu Ji Oi L.Kon Shu Zheng Ruedi Aebersold Connie R.Jimenez Tiannan Guo Zhejiang Provincial Laboratory of Life Sciences and Biomedicine Westlake UniversityHangzhou 310024China Key Laboratory of Structural Biology of Zhejiang Province School of Life SciencesWestlake UniversityHangzhou 310024China Institute of Basic Medical Sciences Westlake Institute for Advanced StudyHangzhou 310024China School of Computer Science Shanghai Key Laboratory of Intelligent Information ProcessingFudan UniversityShanghai 200433China Thermo Fisher Scientific(BREMEN)GmbH Bremen 28195Germany OncoProteomics Laboratory Department of Medical OncologyVU University Medical CenterVU UniversityAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamUrologyCancer Center AmsterdamAmsterdam 1011The Netherlands Thermo Fisher Scientific Shanghai 201206China The Netherlands Cancer Institute Surgical OncologyAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamSurgeryCancer Center AmsterdamAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamPediatric Oncology/HematologyCancer Center AmsterdamAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamHematologyCancer Center AmsterdamAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamMedical OncologyCancer Center AmsterdamAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamNeurosurgeryCancer Center AmsterdamAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamPathologyCancer Center AmsterdamAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamOtolaryngology/Head and Neck SurgeryCancer Center AmsterdamAmsterdam 1011The Netherlands Erasmus MC University Medical Center PathologyRotterdam 1016LVThe Netherlands Erasmus MC University Medical Center SurgeryRotterdam 1016LVThe Netherlands Erasmus MC University Medical Center Medical OncologyRotterdam 1016LVThe Netherlands Department of Anatomical Pathology Singapore General HospitalSingapore 169608Singapore Division of Medical Scie

To address the increasing need for detecting and validating protein biomarkers in clinical specimens,mass spectrometry(MS)-based targeted proteomic techniques,including the selected reaction monitoring(SRM),parallel reaction monitoring(PRM),and massively parallel dataindependent acquisition(DIA),have been *** optimal performance,they require the fragment ion spectra of targeted peptides as prior *** this report,we describe a MS pipeline and spectral resource to support targeted proteomics studies for human tissue *** build the spectral resource,we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on *** then applied the workflow to generate DPHL,a comprehensive DIA pan-human library,from 1096 data-dependent acquisition(DDA)MS raw files for 16 types of cancer *** extensive spectral resource was then applied to a proteomic study of 17 prostate cancer(PCa)***,PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was *** a second application,the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma(DLBCL)patients and 18 healthy control *** expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by *** data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker *** is freely accessible at https://***/page/***?id=IPX0001400000.

关键词： Data-independent acquisition Parallel reaction monitoring Spectral library Prostate cancer Diffuse large B cell lymphoma

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A Genetic-Algorithm Based Method For Storage Location Assignments In Mobile Rack Warehouses

A Genetic-Algorithm Based Method For Storage Location Assign...

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IEEE Global Communications Conference

作者： Dongwen Zhang Yaqi Si Zhihong Tian Lihua Yin Jing Qiu Xiaojiang Du Department of Information Science and Engineering Hebei University of Science and Technology Shijiazhuang China Cyberspace Institute of Advanced Technology Guangzhou University Guangzhou China Cyberspace Security Research Center Peng Cheng Laboratory Shenzhen China Department of Computer and Information Sciences Temple University Philadelphia PA USA

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

In recent years, mobile racks or auto robots have been widely used in e-commerce warehouses where storage location assignment is a fundamental problem in the order picking process. The present storage location assignment strategies mainly allocate stocks into various racks according to a specific objective function or the relationships between stocks. These strategies include the random storage assignment strategy (RAS) and the good-clustering storage location assignment strategy (GCAS). In this paper, we first analyze the key factors that affect the efficiency of the order picking system. The results show that the rack-moved-number (RMN) is a significant factor in the order picking process. Then, we propose a genetic-algorithm (GA) based method for the storage location assignment problem which adopts RMN as its fitness function. To find a better solution, we take the natural deduplicated stock sequence of history orders (NDSSHO) as a seed to initialize the population of chromosomes. We also define a specific cross mutation strategy to avoid checking the validity of chromosomes by exchanging selected genes and adjusting new generated chromosomes. At last, we compare the RMN of our proposed method with RAS and GCAS. The experimental results show that the RMN of our proposed method is about 50% less than RAS and GCAS.

关键词： Robots Biological cells Sociology Statistics Genetic algorithms Linear programming History

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Towards the Trust-Enhancements of Single Sign-On Services

Towards the Trust-Enhancements of Single Sign-On Services

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IEEE Conference on Dependable and Secure Computing

作者： Xuhua Bao Xiaokun Zhang Jingqiang Lin Dawei Chu Qiongxiao Wang Fengjun Li Legendsec Information Technology (Beijing) Inc. CHINA Joint Laboratory of Institute of Information Engineering Chinese Academy of Sciences and QiAnXin Group Academy of Opto-Electronics Chinese Academy of Sciences State Key Laboratory of Information Security Chinese Academy of Sciences Data Assurance and Communication Security Research Center Chinese Academy of Sciences School of Cyber Security University of Chinese Academy of Sciences Department of Electrical Engineering and Computer Science University of Kansas USA

Single sign-on (SSO) becomes popular as the identity management and authentication infrastructure in the Internet. A user receives an SSO ticket after being authenticated by the identity provider (IdP), and this IdP-issued ticket enables him to sign onto the relying party (RP). However, there are vulnerabilities (e.g., Golden SAML) that allow attackers to arbitrarily issue SSO tickets and then sign onto any RP on behalf of any user. Meanwhile, several incidents of certification authorities (CAs) also indicate that the trusted third party of security services is not so trustworthy as expected, and fraudulent TLS server certificates are signed by compromised or deceived CAs to launch TLS man-in-the-middle attacks. Various approaches are then proposed to tame the absolute authority of (compromised) CAs, to detect or prevent fraudulent TLS server certificates in the TLS handshakes. The trust model of SSO services is similar to that of certificate services. So this paper investigates the defense strategies of these trust-enhancements of certificate services, and attempts to apply these strategies to SSO to derive the trust-enhancements applicable in the SSO services. Our analysis derives (a) some security designs which have been commonly-used in the SSO services or non-SSO authentication services, and (b) two schemes effectively improving the trustworthiness of SSO services, which are not widely discussed or adopted.

关键词： Servers Public key Browsers Authentication Authorization Pins

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Benchmarking quality-dependent and cost-sensitive score-level multimodal biometric fusion algorithms

arXiv

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arXiv 2021年

作者： Poh, Norman Bourlai, Thirimachos Kittler, Josef Allano, Lorene Alonso-Fernandez, Fernando Ambekar, Onkar Baker, John Dorizzi, Bernadette Fatukasi, Omolara Fierrez, Julian Ganster, Harald Ortega-Garcia, Javier Maurer, Donald Salah, Albert Ali Scheidat, Tobias Vielhauer, Claus Centre for Vision Speech and Signal Processing School of Electronics and Physical Sciences University of Surrey Guildford SurreyGU2 7XH United Kingdom Biometrics Center Lane Department of Computer Science and Electrical Engineering College of Engineering and Mineral Resources West Virginia University MorgantownWV26506-6109 United States Institut Telecom Telecom and Management SudParis Evry91011 France Biometric Recognition Group – ATVS Escuela Politecnica Superior Universidad Autonoma de Madrid Madrid28049 Spain Amsterdam1098 XG Netherlands Applied Physics Laboratory Johns Hopkins University LaurelMD20723 United States Electronics and Physics Department Institut Telecom Telecom and Management SudParis Evry91011 France Institute of Digital Image Processing Joanneum Research Graz8010 Austria ISLA-ISIS University of Amsterdam Amsterdam1098 XG Netherlands Department of Informatics and Media Brandenburg University of Applied Sciences Brandenburg an der HavelD-14770 Germany Research Group Multimedia and Security Department of Technical and Business Information Systems Faculty of Computer Science Otto-von-Guericke-University of Magdeburg MagdeburgD-39106 Germany

Automatically verifying the identity of a person by means of biometrics (e.g., face and fingerprint) is an important application in our day-to-day activities such as accessing banking services and security control in airports. To increase the system reliability, several biometric devices are often used. Such a combined system is known as a multimodal biometric system. This paper reports a benchmarking study carried out within the framework of the BioSecure DS2 (Access Control) evaluation campaign organized by the University of Surrey, involving face, fingerprint, and iris biometrics for person authentication, targeting the application of physical access control in a medium-size establishment with some 500 persons. While multimodal biometrics is a well-investigated subject in the literature, there exists no benchmark for a fusion algorithm comparison. Working towards this goal, we designed two sets of experiments: quality-dependent and cost-sensitive evaluation. The quality-dependent evaluation aims at assessing how well fusion algorithms can perform under changing quality of raw biometric images principally due to change of devices. The cost-sensitive evaluation, on the other hand, investigates how well a fusion algorithm can perform given restricted computation and in the presence of software and hardware failures, resulting in errors such as failure-to-acquire and failure-to-match. Since multiple capturing devices are available, a fusion algorithm should be able to handle this nonideal but nevertheless realistic scenario. In both evaluations, each fusion algorithm is provided with scores from each biometric comparison subsystem as well as the quality measures of both the template and the query data. The response to the call of the evaluation campaign proved very encouraging, with the submission of 22 fusion systems. To the best of our knowledge, this campaign is the first attempt to benchmark quality-based multimodal fusion algorithms. In the presence of changing

关键词： Benchmarking

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Deep learning driven interpretable and informed decision making model for brain tumour prediction using explainable AI

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Scientific reports 2025年第1期15卷 19223页

作者： Khan Muhammad Adnan Taher M Ghazal Muhammad Saleem Muhammad Sajid Farooq Chan Yeob Yeun Munir Ahmad Sang-Woong Lee Pattern Recognition and Machine Learning Lab Faculty of Artificial Intelligence and Software Gachon University Seongnam-si 13557 Republic of Korea. Department of Networks and Cybersecurity Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman 19111 Jordan. Chitkara University Institute of Engineering and Technology Chitkara University Rajpura Punjab 140401 India. Department of Cyber Security NASTP Institute of Information Technology Lahore 58810 Pakistan. Center for Secure Cyber-Physical Systems (C2PS) Computer Science Department Khalifa University Abu Dhabi United Arab Emirates. chan.yeun@ku.ac.ae. University College Korea University Seoul 02841 Republic of Korea. Pattern Recognition and Machine Learning Lab Faculty of Artificial Intelligence and Software Gachon University Seongnam-si 13557 Republic of Korea. slee@gachon.ac.kr.

Brain Tumours are highly complex, particularly when it comes to their initial and accurate diagnosis, as this determines patient prognosis. Conventional methods rely on MRI and CT scans and employ generic machine learning techniques, which are heavily dependent on feature extraction and require human intervention. These methods may fail in complex cases and do not produce human-interpretable results, making it difficult for clinicians to trust the model's predictions. Such limitations prolong the diagnostic process and can negatively impact the quality of treatment. The advent of deep learning has made it a powerful tool for complex image analysis tasks, such as detecting brain Tumours, by learning advanced patterns from images. However, deep learning models are often considered "black box" systems, where the reasoning behind predictions remains unclear. To address this issue, the present study applies Explainable AI (XAI) alongside deep learning for accurate and interpretable brain Tumour prediction. XAI enhances model interpretability by identifying key features such as Tumour size, location, and texture, which are crucial for clinicians. This helps build their confidence in the model and enables them to make better-informed decisions. In this research, a deep learning model integrated with XAI is proposed to develop an interpretable framework for brain Tumour prediction. The model is trained on an extensive dataset comprising imaging and clinical data and demonstrates high AUC while leveraging XAI for model explainability and feature selection. The study findings indicate that this approach improves predictive performance, achieving an accuracy of 92.98% and a miss rate of 7.02%. Additionally, interpretability tools such as LIME and Grad-CAM provide clinicians with a clearer understanding of the decision-making process, supporting diagnosis and treatment. This model represents a significant advancement in brain Tumour prediction, with the potential to enhance pat

关键词： Brain tumour CT scans MRI XAI

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