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A New Encryption Mechanism Supporting the Update of Encrypted Data for Secure and Efficient Collaboration in the Cloud Environment

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 813-834页

作者： Chanhyeong Cho Byeori Kim Haehyun Cho Taek-Young Youn department of Cyber security Dankook UniversityYongin16890Republic of Korea department of Software Soongsil UniversitySeoul07027Republic of Korea

With the rise of remote collaboration,the demand for advanced storage and collaboration tools has rapidly ***,traditional collaboration tools primarily rely on access control,leaving data stored on cloud servers vulnerable due to insufficient *** paper introduces a novel mechanism that encrypts data in‘bundle’units,designed to meet the dual requirements of efficiency and security for frequently updated collaborative *** bundle includes updated information,allowing only the updated portions to be reencrypted when changes *** encryption method proposed in this paper addresses the inefficiencies of traditional encryption modes,such as Cipher Block Chaining(CBC)and Counter(CTR),which require decrypting and re-encrypting the entire dataset whenever updates *** proposed method leverages update-specific information embedded within data bundles and metadata that maps the relationship between these bundles and the plaintext *** utilizing this information,the method accurately identifies the modified portions and applies algorithms to selectively re-encrypt only those *** approach significantly enhances the efficiency of data updates while maintaining high performance,particularly in large-scale data *** validate this approach,we conducted experiments measuring execution time as both the size of the modified data and the total dataset size *** show that the proposed method significantly outperforms CBC and CTR modes in execution speed,with greater performance gains as data size ***,our security evaluation confirms that this method provides robust protection against both passive and active attacks.

关键词： Cloud collaboration mode of operation data update efficiency

Steel Surface Defect Recognition in Smart Manufacturing Using Deep Ensemble Transfer Learning-Based Techniques

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 231-250页

作者： Tajmal Hussain Jongwon Seok department of information and Communication Engineering Changwon National UniversityChangwon51140Republic of Korea

Smart manufacturing and Industry 4.0 are transforming traditional manufacturing processes by utilizing innovative technologies such as the artificial intelligence(AI)and internet of things(IoT)to enhance efficiency,reduce costs,and ensure product *** light of the recent advancement of Industry 4.0,identifying defects has become important for ensuring the quality of products during the manufacturing *** this research,we present an ensemble methodology for accurately classifying hot rolled steel surface defects by combining the strengths of four pre-trained convolutional neural network(CNN)architectures:VGG16,VGG19,Xception,and Mobile-Net V2,compensating for their individual *** evaluated our methodology on the Xsteel surface defect dataset(XSDD),which comprises seven different *** ensemble methodology integrated the predictions of individual models through two methods:model averaging and weighted *** evaluation showed that the model averaging ensemble achieved an accuracy of 98.89%,a recall of 98.92%,a precision of 99.05%,and an F1-score of 98.97%,while the weighted averaging ensemble reached an accuracy of 99.72%,a recall of 99.74%,a precision of 99.67%,and an F1-score of 99.70%.The proposed weighted averaging ensemble model outperformed the model averaging method and the individual models in detecting defects in terms of accuracy,recall,precision,and *** analysis with recent studies also showed the superior performance of our methodology.

关键词： Smart manufacturing CNN steel defects ensemble models

Semantic Segmentation of Lumbar Vertebrae Using Meijering U-Net(MU-Net)on Spine Magnetic Resonance Images

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 733-757页

作者： Lakshmi S V V Shiloah Elizabeth Darmanayagam Sunil Retmin Raj Cyril department of Computer Science and Engineering College of Engineering GuindyAnna UniversityChennai600025India department of information Technology Madras Institute of TechnologyAnna UniversityChrompetChennai600044India

Lower back pain is one of the most common medical problems in the world and it is experienced by a huge percentage of people *** to its ability to produce a detailed view of the soft tissues,including the spinal cord,nerves,intervertebral discs,and vertebrae,Magnetic Resonance Imaging is thought to be the most effective method for imaging the *** semantic segmentation of vertebrae plays a major role in the diagnostic process of lumbar *** is difficult to semantically partition the vertebrae in Magnetic Resonance Images from the surrounding variety of tissues,including muscles,ligaments,and intervertebral discs.U-Net is a powerful deep-learning architecture to handle the challenges of medical image analysis tasks and achieves high segmentation *** work proposes a modified U-Net architecture namely MU-Net,consisting of the Meijering convolutional layer that incorporates the Meijering filter to perform the semantic segmentation of lumbar vertebrae L1 to L5 and sacral vertebra ***-colour mask images were generated and used as ground truth for training the *** work has been carried out on 1312 images expanded from T1-weighted mid-sagittal MRI images of 515 patients in the Lumbar Spine MRI Dataset publicly available from Mendeley *** proposed MU-Net model for the semantic segmentation of the lumbar vertebrae gives better performance with 98.79%of pixel accuracy(PA),98.66%of dice similarity coefficient(DSC),97.36%of Jaccard coefficient,and 92.55%mean Intersection over Union(mean IoU)metrics using the mentioned dataset.

关键词： Computer aided diagnosis(CAD) magnetic resonance imaging(MRI) semantic segmentation lumbar vertebrae deep learning U-Net model

Quantum public-key crypto via EPR pairs

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 58-63页

作者： Xiang-Qun Fu Hong-Wei Li Jian-Hong Shi Tan Li Wan-Su Bao Henan Key Laboratory of Quantum information and Cryptography Information Engineering University Synergetic Innovation Center of Quantum information and Quantum Physics University of Science and Technology of China

With the development of quantum computing technology, quantum public-key cryptography is gradually becoming an alternative to the existing classical public-key cryptography. This paper designs a quantum trapdoor one-way function via EPR pairs and quantum measurements. Based on this, a new quantum public-key cryptosystem is presented, which offers forward security,and can resist the chosen-plaintext attack and chosen-ciphertext attack. Compared with the existing quantum public-key cryptos,eavesdropping can be automatically detected in this new quantum public-key cryptosystem under a necessary condition, which is also detailed in the paper.

关键词： quantum public-key crypto trapdoor one-way function EPR pairs

Three-Stage Transfer Learning with AlexNet50 for MRI Image Multi-Class Classification with Optimal Learning Rate

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 155-183页

作者： Suganya Athisayamani A.Robert Singh Gyanendra Prasad Joshi Woong Cho School of Computing Sastra Deemed to be UniversityThanjavur613401India department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203India department of AI and Software Engineering Kangwon National UniversitySamcheok25913Republic of Korea department of Electronics Information and Communication EngineeringKangwon National UniversitySamcheok25913Republic of Korea

In radiology,magnetic resonance imaging(MRI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological *** is particularly effective for detecting soft tissue ***,radiologists manually interpret these images,which can be labor-intensive and time-consuming due to the vast amount of *** address this challenge,machine learning,and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MRI *** manuscript presents the use of the Deep AlexNet50 model for MRI classification with discriminative learning *** are three stages for learning;in the first stage,the whole dataset is used to learn the *** the second stage,some layers of AlexNet50 are frozen with an augmented dataset,and in the third stage,AlexNet50 with an augmented dataset with the augmented *** method used three publicly available MRI classification datasets:Harvard whole brain atlas(HWBA-dataset),the School of Biomedical Engineering of Southern Medical University(SMU-dataset),and The National Institute of Neuroscience and Hospitals brain MRI dataset(NINS-dataset)for *** hyperparameter optimizers like Adam,stochastic gradient descent(SGD),Root mean square propagation(RMS prop),Adamax,and AdamW have been used to compare the performance of the learning ***-dataset registers maximum classification *** evaluated the performance of the proposed classification model using several quantitative metrics,achieving an average accuracy of 98%.

关键词： MRI tumors classification AlexNet50 transfer learning hyperparameter tuning optimizer

Controlled mutual quantum entity authentication using entanglement swapping

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Chinese Physics B 2015年第9期24卷 116-124页

作者： Min-Sung Kang Chang-Ho Hong Jino Heo Jong-In Lim Hyung-Jin Yang Center for information security Technologies (CIST) Korea University Graduate School of information security Korea University department of Physics Korea University

In this paper, we suggest a controlled mutual quantum entity authentication protocol by which two users mutually certify each other on a quantum network using a sequence of Greenberger–Horne–Zeilinger（GHZ）-like states. Unlike existing unidirectional quantum entity authentication, our protocol enables mutual quantum entity authentication utilizing entanglement swapping; moreover, it allows the managing trusted center（TC） or trusted third party（TTP） to effectively control the certification of two users using the nature of the GHZ-like state. We will also analyze the security of the protocol and quantum channel.

关键词： quantum authentication quantum cryptography quantum communication GHZ-like state

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RECTANGLE: a bit-slice lightweight block cipher suitable for multiple platforms

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Science China(information Sciences) 2015年第12期58卷 89-103页

作者： ZHANG WenTao BAO ZhenZhen LIN DongDai Vincent RIJMEN YANG Bo Han Ingrid VERBAUWHEDE State Key Laboratory of information security Institute of Information EngineeringChinese Academy of Sciences department of Electrical Engineering ESAT COSIC and i Minds Security Department

In this paper, we propose a new lightweight block cipher named RECTANGLE. The main idea of the design of RECTANGLE is to allow lightweight and fast implementations using bit-slice techniques. RECTANGLE uses an SP-network. The substitution layer consists of 16 4 × 4 S-boxes in parallel. The permutation layer is composed of 3 rotations. As shown in this paper, RECTANGLE offers great performance in both hardware and software environment, which provides enough flexibility for different application scenario. The following are3 main advantages of RECTANGLE. First, RECTANGLE is extremely hardware-friendly. For the 80-bit key version, a one-cycle-per-round parallel implementation only needs 1600 gates for a throughput of 246 Kbits/s at100 k Hz clock and an energy efficiency of 3.0 p J/bit. Second, RECTANGLE achieves a very competitive software speed among the existing lightweight block ciphers due to its bit-slice style. Using 128-bit SSE instructions,a bit-slice implementation of RECTANGLE reaches an average encryption speed of about 3.9 cycles/byte for messages around 3000 bytes. Last but not least, we propose new design criteria for the RECTANGLE *** to our careful selection of the S-box and the asymmetric design of the permutation layer, RECTANGLE achieves a very good security-performance tradeoff. Our extensive and deep security analysis shows that the highest number of rounds that we can attack, is 18(out of 25).

关键词： lightweight cryptography block cipher design bit-slice hardware efficiency software efficiency

Bidirectional transfer of quantum information for unknown photons via cross-Kerr nonlinearity and photon-number-resolving measurement

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Chinese Physics B 2016年第2期25卷 82-92页

作者： Jino Heo Chang-Ho Hong Dong-Hoon Lee Hyung-Jin Yang Graduate School of information security (GSIS) Korea University Center for information security Technologies (CIST) Korea University department of Physics Korea University

We propose an arbitrary controlled-unitary （CU） gate and a bidirectional transfer scheme of quantum information （BTQI） for unknown photons. The proposed CU gate utilizes quantum non-demolition photon-number-resolving measure- ment based on the weak cross-Kerr nonlinearities （XKNLs） and two quantum bus beams; the proposed CU gate consists of consecutive operations of a controlled-path gate and a gathering-path gate. It is almost deterministic and is feasible with current technology when a strong amplitude of the coherent state and weak XKNLs are employed. Compared with the existing optical multi-qubit or controlled gates, which utilize XKNLs and homodyne detectors, the proposed CU gate can increase experimental realization feasibility and enhance robustness against decoherence. According to the CU gate, we present a BTQI scheme in which the two unknown states of photons between two parties （Alice and Bob） are mutually swapped by transferring only a single photon. Consequently, by using the proposed CU gate, it is possible to experimentally implement the BTQI scheme with a certain probability of success.

关键词： cross-Kerr nonlinearity quantum non-demolition photon-number-resolving measurement bidirec-tional transfer of quantum information

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Bidirectional quantum teleportation of unknown photons using path-polarization intra-particle hybrid entanglement and controlled-unitary gates via cross-Kerr nonlinearity

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Chinese Physics B 2015年第5期24卷 210-222页

作者： Jino Heo Chang-Ho Hong Jong-In Lim Hyung-Jin Yang Graduate School of information security (GSIS) Korea University Center for information security Technologies (CIST) Korea University department of Physics Korea University

We propose an arbitrary controlled-unitary （CU） gate and a bidirectional quantum teleportation （BQTP） scheme. The proposed CU gate utilizes photonic qubits （photons） with cross-Kerr nonlinearities （XKNLs）, X-homodyne detectors, and linear optical elements, and consists of the consecutive operation of a controlled-path （C-path） gate and a gathering-path （G- path） gate. It is almost deterministic and feasible with current technology when a strong coherent state and weak XKNLs are employed. Based on the CU gate, we present a BQTP scheme that simultaneously teleports two unknown photons between distant users by transmitting only one photon in a path-polarization intra-particle hybrid entangled state. Consequently, it is possible to experimentally implement BQTP with a certain success probability using the proposed CU gate.

关键词： cross-Kerr nonlinearity bidirectional quantum teleportation intra-particle hybrid entanglement

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