20 September 2023
Volume 58 Issue 9
Meta computing: a new computing paradigm under zero trust
CHENG Xiuzhen, LYU Weifeng, XU Minghui, PAN Runyu, YU Dongxiao, WANG Chenxu, YU Yong, XIAO Xue
2023, 58(9):  1-15.  doi:10.6040/j.issn.1671-9352.0.2023.168
Abstract ( 58 )   PDF (6738KB) ( 70 )   Save
References | Related Articles | Metrics
The popularity of the Internet has had a significant impact on the development of computing paradigms. With the continuous improvement of the new generation of information technology infrastructures, academia and industry have been constantly exploring new computing paradigms to fully exploit computing powers. The huge data generated by massive IoT devices gradually exceeds the processing capability of the high-performance back-end represented by cloud servers. Edge computing alleviates this problem through cloud-edge-end coordination, but there still exist difficulties and challenges such as low computing power utilization, low computing and storage fault tolerance capability, and low integration of computing resorces. “Meta Computing” is a new computing paradigm that aims to break down the barriers of computing powers in a zero-trust environment. It can integrate all available connected computing and storage resources, provide efficient, byzantine fault-tolerant, and personalized services, while protecting the data and user privacy. Furthermere, meta computing can ensure the correctness of results, and realize “the entire network can be regarded as a giant computer for a user”, that is, “Network-as-a-Computer, NaaC”, which is also called “Meta Computer”. The meta computer architecture includes a number of function modules including a device management module and a zero-trust computing management module, as well as the cloud-edge-end device resources. The device management module abstracts massive heterogeneous device resources into objects that can be freely manipulated, while the zero-trust computing management module can transparently allocate computing resources to user tasks according to service requirements, complete the tasks with strong fault tolerance and verifiable outputs, and finally settle accounts. Based on the analysis of the architecture and the functional characteristics of meta computing, we put forward suggestions and advice on the development path of meta computing, that is, transitioning from local to global, and analyze the most-influential future application scenarios of meta computing and provide a reasonable plan for the implementation and development of meta computing in future.
Time-controlled designated tester proxy re-encryption with keyword search scheme
LYU Jiao, ZHANG Xi, QIN Jing
2023, 58(9):  16-27.  doi:10.6040/j.issn.1671-9352.0.2022.154
Abstract ( 41 )   PDF (1490KB) ( 23 )   Save
References | Related Articles | Metrics
To solve the problem that the proxy re-encryption with keyword search is used to implement ciphertext data exchange and sharing, but it does not support time-controlled access authorization and cannot resist off-line keyword guessing attack, a time-controlled designated tester proxy re-encryption with keyword search scheme is proposed, which supports the data owner to grant dynamically the search and decryption rights of the ciphertext data in the cloud to the data user within a specified time range, and can resist the off-line keyword guessing attack by external adversaries. In addition, the scheme is applied to the scenario of sharing patients electronic medical records between different hospitals, and a specific electronic medical records sharing scheme is designed based on the consortium blockchain.
An encryption scheme supporting wildcard and fuzzy search
ZHAO Bo, QIN Jing, LIU Jinlu
2023, 58(9):  28-38.  doi:10.6040/j.issn.1671-9352.0.2022.471
Abstract ( 34 )   PDF (1726KB) ( 18 )   Save
References | Related Articles | Metrics
Based on n-gram technology, this paper proposes an encryption scheme that can support both wildcard and fuzzy search. In addition, using the Bloom filter optimization scheme, it reduces the index storage overhead and search time. The given security analysis shows that the scheme is non-adaptive semantic security. The performance analysis shows that the optimized scheme has less overhead in storage, communication and trapdoor generation than the previous schemes.
An automatic protocol vulnerability detection framework for resource-constrained devices of LPWAN
LI Feixu, YAN Fei, CHENG Binlin, ZHANG Liqiang
2023, 58(9):  39-50.  doi:10.6040/j.issn.1671-9352.0.2022.660
Abstract ( 34 )   PDF (1037KB) ( 18 )   Save
References | Related Articles | Metrics
LPWAN(low power wide area network)as a protocol that emphasizes low power consumption usually runs on resource-constrained devices. On the one hand, limited resources bring serious challenges to the security of protocol implementation. Manufacturers may have trouble balancing security demands and resource consumption. On the other hand, protocol stacks are deployed on constrained devices as bare-metal firmware. The varying hardware characteristics make automatic analysis difficult. Therefore, a protocol stack analysis framework called ProSE is proposed. Based on symbolic execution and taint analysis, ProSE is specifically designed for protocol vulnerability detection on the firmware of constrained devices. LoRaWAN is chosen for analysis due to its popularity. The framework is capable of detecting various types of vulnerability. ProSE successfully detected 20 potential security vulnerabilities in the implementation of LoRaWAN of 6 manufacturers.
Research on cryptographic properties of generalized SIMON-like round functions
LU Jianwei, REN Jizhou, GUAN Jie
2023, 58(9):  51-58.  doi:10.6040/j.issn.1671-9352.0.2022.162
Abstract ( 29 )   PDF (446KB) ( 15 )   Save
References | Related Articles | Metrics
Based on the SIMON-like nonlinear function, a generalized nonlinear function Fnabcd(X)is obtained, and the structure is as follows:(x<<<a)& (x<<<b)⊕(x<<<c)&(x<<<d). The cryptographic properties of Fnabcd(X)such as difference and linearity are given. The corresponding relationship between the rank of the difference matrix, output difference and difference probability is given; the value of the difference probability is 0 or 1/2r, where r∈[0,n-1]; the difference probability is non-zero when β=0; under the selection of special shift parameters, the corresponding difference structure and counting formula are given when the difference probability is 1/2. By using the disjoint algorithm, the problem of the correlated advantage value can be transformed into calculating the number of quadratic terms in the disjoint quadratic form, and the value range of the correlated advantage is given. These conclusions provide a new method for the construction of lightweight nonlinear functions.
A object detection algorithm for aerial images
LI Cheng, CHE Wengang, GAO Shengxiang
2023, 58(9):  59-70.  doi:10.6040/j.issn.1671-9352.0.2022.349
Abstract ( 45 )   PDF (13222KB) ( 34 )   Save
References | Related Articles | Metrics
A object detection algorithm DSB-YOLO(depthwise separable convolutional backbone and YOLO)for aerial images is proposed. Based on YOLOv5s, firstly, from the perspective of extracting the perceptual field of the feature map from the backbone network, the perceptual field of the feature map is reduced by changing the interval sampling of the convolutional kernel to better extract the information of small objects. Secondly, the feature pyramid network(FPN)and path aggregation network(PAN)feature fusion paths in the Neck part of the network are improved, so that the large amount of location information in the shallow sampled feature maps can be better combined with the deep extracted feature maps of the network. This allows the network to combine the large amount of location information in the shallow sampled feature map with the deep extracted feature map, effectively improving the accurate detection rate of small objects. The C3Transformer module was then added to the backbone network to integrate the full image information; then, the network was lightened by replacing the partial convolution of the network backbone with a depth-separable convolution and integrating the SE attention mechanism, which aims to focus and select the information useful for the object detection task, thus improving the detection efficiency of the model. Comparative experimental results using the VisDrone dataset show that, at an input image resolution of 1 280×1 280 pixels, the DSB-YOLO algorithm proposed in this paper tests average accuracy metrics mAP50 and mAP0.5∶0.95 that are 11% and 17.5% higher, respectively, compared to the original model; Deployed on the embedded platform Jetson TX2, computing rates of up to 21FPS can be achieved and model performance meets applicable standards.
Context fusion-based knowledge graph completion
NA Yujia, XIE Jun, YANG Haiyang, XU Xinying
2023, 58(9):  71-80.  doi:10.6040/j.issn.1671-9352.4.2022.2743
Abstract ( 34 )   PDF (1407KB) ( 26 )   Save
References | Related Articles | Metrics
A knowledge graph completion model integrating context is constructed. Firstly, the deep interactive embedding of a given head-tail entity pair is obtained through the Inception network. Secondly, two types of context information of a given entity pair are defined and coded: adjacency and path context; Next, the attention mechanism based on head-to-tail interaction embedding is used to respectively aggregate the adjacency and path context of a given entity pair; Finally, the full connection layer is used to fuse the two types of context information of a given entity pair and consequently predict the relationship between the given entity pairs. Compared with other mainstream models in datasets FB15K-237, WN18RR and NELL-995, the experimental results show that the proposed model is effective.
Personalized recommendation of mobile users by integrating basic information and communication behavior
WU Xianjun, TANG Shaoshi, WANG Mingqiu
2023, 58(9):  81-93.  doi:10.6040/j.issn.1671-9352.0.2022.007
Abstract ( 33 )   PDF (1826KB) ( 11 )   Save
References | Related Articles | Metrics
Considering the factors which affect the mobile users product ordering, this paper proposes a new matrix factorization model integrating the basic information and communication behavior of the mobile users, and compares the performance of the proposed method with the traditional model on the prediction of rating and Top-N recommendation. For the prediction of rating, some indices are adjusted in the RFM model by combining with the characteristics of mobile users in the product ordering process. Then a user-product rating matrix, constructed by the adjusted RFM model, can accurately and objectively reflect the users preference for products. For the Top-N recommendation, a negative sampling method is adopted that popular products with no ordering behavior are preferred to be included in the negative samples. The numerical results show that the proposed method performs better.
Incomplete neighborhood weighted multi-granularity decision-theoretic rough sets and three-way decision
WANG Qian, ZHANG Xianyong
2023, 58(9):  94-104.  doi:10.6040/j.issn.1671-9352.0.2022.430
Abstract ( 34 )   PDF (6341KB) ( 17 )   Save
References | Related Articles | Metrics
Concerning the differences and imbalances of granularities, the classification capacity of granularity is considered to mine the granularity weight, and two rough set models based on the granularity weighting strategy are constructed to implement three-way decision. At first, the granularity significance is defined by the influence of boundary region for knowledge classification, and it induces the granularity weight; by fusing the granularity weights and condition probabilities, incomplete neighborhood weighted multi-granularity decision-theoretic rough sets are modeled to establish three-way decision. Then considering the specific restriction of important attribute, incomplete neighborhood weighted-restrictive multi-granularity decision-theoretic rough sets are further proposed, and relevant properties and mutual relationships are acquired. At last, example demonstrations and data experiments are performed by variable three-way decision, and the rationality and superiority of new models are verified. Regarding incomplete neighborhood multi-granularity decision-theoretic rough sets, the two weighted models optimally improve and systematically extend corresponding basic models, and they facilitate relevant data analysis and decision making.
Feasible region localization and fast causal instance selection for multi-instance learning
YANG Mei, KE Wenjing, WANG Dandong
2023, 58(9):  105-113.  doi:10.6040/j.issn.1671-9352.4.2022.5119
Abstract ( 28 )   PDF (2146KB) ( 12 )   Save
References | Related Articles | Metrics
This paper proposes a feasible region localization and fast causal instance selection(FFCM)algorithm for multi-instance learning, incorporating three techniques. To minimize the feasible region of data, the fast feasible region localization technique is used to select representative instances from the positive bags as candidate instances based on distance measurement, and reduces the negative referee bags through probability analysis. The fast causal instance-based selection technique uses the causal relationship between candidate instances and negative referee bags to construct fusion bags. Subsequently, prior knowledge is employed to select causal instances from candidate instances based on the designed causal instance criteria. The bag mapping technique maps bags into single vectors with high distinguishability using causal instances and a difference-based mapping function. The proposed algorithm is compared with 6 state-of-the-art MIL algorithms on 27 commonly used datasets. The experimental results show that the proposed FFCM exhibits comparable classification performance.
Polytomous knowledge structure and learning path in formal context
LIN Yujing, LI Jinjin, CHEN Huiqin
2023, 58(9):  114-126.  doi:10.6040/j.issn.1671-9352.0.2022.504
Abstract ( 24 )   PDF (685KB) ( 8 )   Save
References | Related Articles | Metrics
Based on the polytomous evaluation system of problem solving, a method of formal concept analysis is employed to construct the polytomous knowledge structure, to find the learning path and to evaluate operation procedure, in order to effectively guide the learning of learners. Firstly, a method of constructing polytomous knowledge structure from the formal concept lattice of operation procedure is proposed. Secondly, the formal context of well-formed operating procedure is introduced, in which step-by-step learning and effective evaluation of operating procedures can be carried out. Finally, the algorithm steps to find the learning path under the disjunctive model are designed, and the effectiveness of the algorithm steps is illustrated with examples.