Computer Journal最新文献_第3页

Cryptanalysis Of A Type Of White-Box Implementations Of The SM4 Block Cipher 一种SM4分组密码白盒实现的密码分析

4区计算机科学

Computer Journal Pub Date : 2023-09-19 DOI: 10.1093/comjnl/bxad091

Jiqiang Lu, Jingyu Li, Zexuan Chen, Yanan Li

{"title":"Cryptanalysis Of A Type Of White-Box Implementations Of The SM4 Block Cipher","authors":"Jiqiang Lu, Jingyu Li, Zexuan Chen, Yanan Li","doi":"10.1093/comjnl/bxad091","DOIUrl":"https://doi.org/10.1093/comjnl/bxad091","url":null,"abstract":"Abstract The SM4 block cipher is a Chinese national standard and an ISO international standard. Since white-box cryptography has many real-life applications nowadays, a few white-box implementations of SM4 has been proposed, among which a type of constructions is dominated, which uses a linear or affine diagonal block encoding to protect the original three 32-bit branches entering a round function and uses its inverse as the input encoding to the S-box layer. In this paper, we analyse the security of this type of constructions against Lepoint et al.’s collision-based attack method. Our experiment under a small fraction of (encodings, round key) combinations shows that the rank of the concerned linear system is much less than the number of the involved unknowns, meaning these white-box SM4 implementations should resist Lepoint et al.’s method, but we leave it as an open problem whether there are such encodings that the rank of the corresponding linear system is slightly less than the number of the involved unknowns, in which scenario Lepoint et al.’s method may be used to recover a round key for the case with linear encodings and to remove most white-box operations until mainly some Boolean masks for the case with affine encodings.","PeriodicalId":50641,"journal":{"name":"Computer Journal","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135011338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Hybrid Solution For The Cold Start Problem In Recommendation 推荐系统冷启动问题的混合解决方案

4区计算机科学

Computer Journal Pub Date : 2023-08-26 DOI: 10.1093/comjnl/bxad088

Syed Irteza Hussain Jafri, Rozaida Ghazali, Irfan Javid, Yana Mazwin Mohmad Hassim, Mubashir Hayat Khan

{"title":"A Hybrid Solution For The Cold Start Problem In Recommendation","authors":"Syed Irteza Hussain Jafri, Rozaida Ghazali, Irfan Javid, Yana Mazwin Mohmad Hassim, Mubashir Hayat Khan","doi":"10.1093/comjnl/bxad088","DOIUrl":"https://doi.org/10.1093/comjnl/bxad088","url":null,"abstract":"Abstract Recommender systems are becoming more and more significant in today’s digital world and in the modern economy. They make a substantial contribution to company operations by offering tailored advice and decreasing overwhelm. Collaborative filtering, being popular in the domain of recommendation, is used to offer recommendations to attract the target audience based on the feedback of people with comparable interests. This method has some limitations, such as a cold-start issue, which makes the system less effective in anticipating unknown objects. We provide a hybrid deep-learning-based strategy centered on a method to enrich user and item profiles to address the cold-start issue in the recommendation process using a collaborative filtering approach. We employ pretrained deep learning models to produce rich user and item feature vectors that aid in the creation of useful suggestions and handling of user and item cold-start issues. The creation of more precise and tailored similarity matrices is made possible by adding metadata to the extracted features of the user and item. The results of the experiment demonstrate that in terms of precision and rate coverage, the proposed method performs better than the baseline techniques.","PeriodicalId":50641,"journal":{"name":"Computer Journal","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135236050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Revisiting the Software-Efficient Stream Ciphers RCR-64 and RCR-32 重新审视软件高效流密码RCR-64和RCR-32

4区计算机科学

Computer Journal Pub Date : 2023-08-14 DOI: 10.1093/comjnl/bxad084

Mabin Joseph, Gautham Sekar, R Balasubramanian

引用次数: 0

Knowledge-Aware Dual-Channel Graph Neural Networks For Denoising Recommendation 基于知识感知的双通道图神经网络去噪推荐

4区计算机科学

Computer Journal Pub Date : 2023-08-11 DOI: 10.1093/comjnl/bxad085

Hanwen Zhang, Li-e Wang, Zhigang Sun, Xianxian Li

{"title":"Knowledge-Aware Dual-Channel Graph Neural Networks For Denoising Recommendation","authors":"Hanwen Zhang, Li-e Wang, Zhigang Sun, Xianxian Li","doi":"10.1093/comjnl/bxad085","DOIUrl":"https://doi.org/10.1093/comjnl/bxad085","url":null,"abstract":"Abstract Knowledge graph (KG) is introduced as side information into recommender systems, which can alleviate the sparsity and cold start problems in collaborative filtering. Existing studies mainly focus on modeling users’ historical behavior data and KG-based propagation. However, they have the limitation of ignoring noise information during recommendation. We consider that noise exists in two parts (i.e. KG and user-item interaction data). In this paper, we propose Knowledge-aware Dual-Channel Graph Neural Networks (KDGNN) to improve the recommendation performance by reducing the noise in the recommendation process. Specifically, (1) for the noise in KG, we design a personalized gating mechanism, namely dual-channel balancing mechanism, to block the propagation of redundant information in KG. (2) For the noise in user-item interaction data, we integrate personalized and knowledge-aware signals to capture user preferences fully and use personalized knowledge-aware attention to denoise user-item interaction data. Compared with existing KG-based methods, we aim to propose a knowledge-aware recommendation method from a new perspective of denoising. We perform performance analysis on three real-world datasets, and experiment results demonstrate that KDGNN achieves strongly competitive performance compared with several compelling state-of-the-art baselines.","PeriodicalId":50641,"journal":{"name":"Computer Journal","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135444069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AKGF: Automatic Kernel Generation for DNN on CPU-FPGA AKGF:在CPU-FPGA上自动生成DNN内核

4区计算机科学

Computer Journal Pub Date : 2023-08-11 DOI: 10.1093/comjnl/bxad086

Dong Dong, Hongxu Jiang, Boyu Diao

引用次数: 0

KEFSAR: A Solar-Aware Routing Strategy For Rechargeable IoT Based On High-Accuracy Prediction KEFSAR:基于高精度预测的可充电物联网太阳能感知路由策略

4区计算机科学

Computer Journal Pub Date : 2023-07-29 DOI: 10.1093/comjnl/bxad074

Dongchao Ma, Dongmei Wang, Xiaofu Huang, Yuekun Hu, Li Ma

{"title":"KEFSAR: A Solar-Aware Routing Strategy For Rechargeable IoT Based On High-Accuracy Prediction","authors":"Dongchao Ma, Dongmei Wang, Xiaofu Huang, Yuekun Hu, Li Ma","doi":"10.1093/comjnl/bxad074","DOIUrl":"https://doi.org/10.1093/comjnl/bxad074","url":null,"abstract":"Abstract The high energy density of solar energy gives wireless sensor networks advantages in outdoor monitoring applications. However, long-term stable monitoring is challenging due to frequent weather changes, shading by buildings and trees, etc. The existing research usually uses two technologies to solve the above problems: (1) the energy prediction algorithm, and (2) the energy-aware routing strategy. However, in an actual deployment, frequent weather changes can significantly reduce the accuracy of the existing prediction algorithms. When using the algorithms as the support for energy-aware routing, the network lifetime is less than ideal. The existing routing strategies are in need of further improvement. Because of its lack of environmental adaptability, nodes consume energy quickly and have a high mortality rate. Therefore, aiming at the long-term stability of solar wireless sensor networks, this paper proposes a prediction algorithm based on classification and recurrent neural networks, and integrates the shadow judgement method from our previous research to correct the predicted values. Furthermore, we propose a routing optimization model that can flexibly adjust the target according to the solar intensity. The experimental results show that the prediction and routing scheduling algorithm can significantly improve the energy prediction accuracy (30–50%) and prolong the network lifetime (10–42%) in outdoor small sensor scenarios.","PeriodicalId":50641,"journal":{"name":"Computer Journal","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134919155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Super Structure Fault-Tolerance Assessment of the Generalized Hypercube 广义超立方体的超结构容错性评估

4区计算机科学

Computer Journal Pub Date : 2023-07-29 DOI: 10.1093/comjnl/bxad072

Chang Shu, Yan Wang, Jianxi Fan, Guijuan Wang

引用次数: 0

A Toolbox for Migrating the Blockchain-Based Application From Ethereum to Hyperledger Fabric 将基于区块链的应用程序从以太坊迁移到超级账本结构的工具箱

4区计算机科学

Computer Journal Pub Date : 2023-06-16 DOI: 10.1093/comjnl/bxad061

Zhonghao Zhai, Subin Shen, Yanqin Mao

{"title":"A Toolbox for Migrating the Blockchain-Based Application From Ethereum to Hyperledger Fabric","authors":"Zhonghao Zhai, Subin Shen, Yanqin Mao","doi":"10.1093/comjnl/bxad061","DOIUrl":"https://doi.org/10.1093/comjnl/bxad061","url":null,"abstract":"Abstract The low transaction capacity, high transaction cost and long-term privacy concerns of the current Ethereum platform are notorious. Developers are seeking alternative blockchain platforms to migrate their blockchain-based applications to reduce their applications’ use-cost and improve their applications’ user experience. The Hyperledger Fabric (HLF) platform with resiliency, flexibility, scalability and confidentiality is preferred for developers to migrate their Ethereum blockchain-based applications. However, it is laborious for developers to migrate blockchain-based applications from the Ethereum platform to the HLF platform. In this paper, we first propose a complete and secure migration solution to ease the migration process. The main idea of our solution is to design a toolbox to help developers automatically eliminate the adverse effects that the differences between Ethereum and HLF may bring to the migrated application. Developers with the toolbox can migrate the application with little time and minimal modification. It is theoretically proved that the migrated application with the toolbox is secure. Besides, a prototype of the toolbox is implemented. The extensive experiments demonstrate that the time for the migration process is acceptable, and the toolbox has little impact on the migrated application’s performance.","PeriodicalId":50641,"journal":{"name":"Computer Journal","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135525799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Correction to: Metaheuristic-Enabled Artificial Neural Network Framework For Multimodal Biometric Recognition With Local Fusion Visual Features 修正:局部融合视觉特征的多模态生物识别的元启发式人工神经网络框架

4区计算机科学

Computer Journal Pub Date : 2023-06-02 DOI: 10.1093/comjnl/bxad064

引用次数: 0

2-Layer k-Planar Graphs Density, Crossing Lemma, Relationships And Pathwidth 2层k-平面图密度，交叉引理，关系和路径宽度

4区计算机科学

Computer Journal Pub Date : 2023-04-21 DOI: 10.1093/comjnl/bxad038

Patrizio Angelini, Giordano Da Lozzo, Henry Förster, Thomas Schneck

引用次数: 0