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15 December 2022, Volume 8 Issue 6

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Perspective

Academic connotation and research trends of privacy computing

Fenghua LI, Hui LI, Ben NIU, Weidong QIU

2022, 8(6):  1-8.  doi:10.11959/j.issn.2096-109x.2022078

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The authors of this paper first proposed the concept, definition and academic connotation of privacy computing, and formed a relatively mature theoretical and technical system accordingly.In order to continuously promote the academic research and industrial application of privacy computing, the academic connotation of privacy computing was elaborated, including how to understand the full-life cycle, extended control, privacy quantification and mapping, desensitization effect evaluation.Besides, the necessity of iterative on-demand desensitization and the motivation to study the language of privacy computing were presented.The role of audit log self-storage in ubiquitous sharing was explained and some distorted academic concepts were also clarified.Moreover, 37 research points in 9 aspects of privacy computing and 40 research points in 8 aspects of data security were given.It helps to better understand the research scope of privacy computing and correctly distinguish between privacy computing and data security.

Topic: Techniques and applications of cryptography

Anti malicious KGC certificateless signature scheme based on blockchain and domestic cryptographic SM9

Fei TANG, Ning GAN, Xianggui YANG, Jinyang WANG

2022, 8(6):  9-19.  doi:10.11959/j.issn.2096-109x.2022073

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The certificateless cryptosystem can solve the problems of certificate management and key escrow at the same time, but its security model always assumes that Type II adversary (named malicious KGC) will not launch public key replacement attacks.This security assumption has certain limitations in real-world applications.As an efficient identity-based cryptographic scheme, SM9 signature scheme adopts R-ate bilinear pairing which has good security and high computational efficiency.However, it requires KGC to generate and manage keys for users, so it has the problem of key escrow.In view of the above problems, a certificateless signature scheme against malicious KGC was constructed based on blockchain and SM9 signature algorithm.Based on the properties of decentralization and tamper-proof of blockchain, the proposed scheme used the smart contract to record part of the public key corresponding to the user’s secret value on the blockchain.Then, the verifier can revoke the smart contract to query the user’s public key during the signature verification stage.Therefore, the proposed scheme ensured the authenticity of the user’s public key.The user’s private key consisted of the partial private key generated by KGC and a secret randomly chosen by the user.The user required the partial private key generated by KGC to endorse his identity identifier when the user generates the private key for the first time.Subsequently, the private key can be independently updated by changing the secret and the corresponding partial public key.During this process, the identity remains unchanged, which provided a viable solution for key management in decentralized application scenarios.The blockchain relied on the consensus mechanism to ensure the consistency of the distributed data.Based on the traceability of the blockchain, the change log of user’s partial public key was stored in the blockchain, which can trace the source of malicious public key replacement attacks and thereby prevent malicious KGC from launching public key replacement attacks.According to the experimental simulation and security proof results, the total overhead of signature and verification of the proposed scheme is only 7.4ms.Compared with similar certificateless signature schemes, the proposed scheme can effectively resist public key replacement attacks and has higher computational efficiency.

Automotive ethernet controller authentication method based on national cryptographic algorithms

Hui GUO, Yong LUO, Xiaolu GUO

2022, 8(6):  20-28.  doi:10.11959/j.issn.2096-109x.2022079

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With the development of intelligent and connected cars, cyber security of automotive ethernet becomes the focus of automotive industry.Authentication is one of the key technologies for automotive ethernet security.The existing authentication methods have shortcomings to meet the requirements of both safety and electronic controllers’ performance.Besides, national cryptographic algorithms are becoming a trend for automotive network security, while the related research in automotive ethernet area is still in starting phase.In order to balance the limited computing performance of electronic controllers and high security requirements of automotive ethernet, a two-stage trust chain authentication method based on national cryptographic algorithms was proposed.The method can be used in different automotive ethernet topologies.A trust chain was built up based on authentication credentials, which linked the two authentication stages, namely the initial stage and the vehicle using stage.The initial stage was triggered by diagnosis instrument at end of line or controller replacement.It deployed complete authentication based on SM2 algorithm and certificates in the initial stage.The vehicle using stage was triggered by ethernet gateway at vehicle power-on or network wakeup.In this stage, the method deployed fast authentication based on SM4 algorithm and authentication credential trust chain.The authentication credentials for trust chain were generated by credential functions.In order to ensure security, each credential was generated based on last successful authentication parameters dynamically.The test results on automotive ethernet controllers show that the method has lower computing cost and higher security level, and it can guarantee both performance and security.

Public key cryptographic algorithm SM2 optimized implementation on low power embedded platform

Ganqin LIU, Hui LI, Hui ZHU, Yukun HUANG, Xingdong LIU

2022, 8(6):  29-38.  doi:10.11959/j.issn.2096-109x.2022080

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With the development of wireless communication technology and the popularization of intelligent terminals, more and more cryptographic algorithms are applied to IoT devices to ensure the security of communication and data.Among them, the SM2 elliptic curve public key cryptography proposed by the State Cryptography Administration is an elliptic curve public key cryptography algorithm developed domestically, which has the advantages of high security and short key.SM2 has been widely deployed in various communication systems and is used in essential parts such as identity authentication and key negotiation.However, since SM2 involves large integer operations on finite fields, the computational cost is high, and its execution on a low-power embedded platform seriously affects the user experience.Therefore, an efficient implementation scheme of SM2 algorithm for low-power embedded platform was proposed for ARM-m series processors.Specifically, Thumb-2 instruction set was adopted to handle carry and save addressing cycles, basic operations such as modulo addition and sub-traction of large integers were optimized, and the number of available registers on the platform was combined to build efficient basic operations.Besides, based on the short multiplication and accumulation instruction cycle of ARM-m series processors, the implementation of Montgomery multiplication was optimized, and an efficient modular multiplication scheme was designed in combination with the CIOS algorithm.The scheme was no longer limited to Mersenne primes, and greatly improved the speed and flexibility of modular multiplication.Based on the theoretical analysis and experimental test, the window length selection method of the multiple point-scalar multiplication wNAF sliding window method on the embedded platform was given.The experimental test results show that the proposed scheme can effectively improve the computational efficiency of the SM2 algorithm on the resource-constrained low-power embedded platform.Without pre-calculation, the test signature speed can reach 0.204s/time, the signature verification speed is 0.388s/time, the encryption speed is 0.415s/time, and the decryption speed is 0.197s/time.

Two-party cooperative blind signature based on SM2

Xue BAI, Baodong QIN, Rui GUO, Dong ZHENG

2022, 8(6):  39-51.  doi:10.11959/j.issn.2096-109x.2022081

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SM2, issued by China in 2010, is a public key cryptography standard based on elliptic curves.It has been widely used in finance, social security and other fields thanks to its advantages of improved signature efficiency, decreased storage space and computing complexity than RSA.With the popularization and application of SM2, the issues of its key security and data privacy are of great concern.The single-key mode inhibits the potential application in multi-user settings, and the leakage of the key will threaten the security of the entire cryptosystem due to the centralization.The problem of secure storage and reasonable utilization of keys needs to be solved urgently.In addition, the SM2 digital signature algorithm cannot guarantee the message privacy.Aiming at the issues of key security and data privacy of the signature algorithm, many researchers have proposed the idea of cooperative signature and blind signature for SM2.However, there isn’t SM2 collaborative blind signature scheme proposed.Then a two-party cooperative blind signing protocol based on SM2 was proposed in this paper, which allowed two parties to sign except the user.The signing process did not require recovering the complete private key, while not revealing the information of the partial private key and secret number.The key was stored separately to improve the security of the key, while the blind signature protected the privacy of the message.In terms of security, the protocol satisfied unforgeability and unlinkability.The protocol was implemented using C to demonstrate the efficiency of each participant’s local operation.In the honest model, the time cost of each entity in the cooperative signature phase was similar as that of executing a lightweight SM2 blind signature.Overall, the proposed protocol has certain advantages in terms of function and efficiency.

Survey of key management schemes for cluster networks

Jun LIU, Lin YUAN, Zhishang FENG

2022, 8(6):  52-69.  doi:10.11959/j.issn.2096-109x.2022082

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With the rapid development of artificial intelligence and communication network technology, increasing attention has been paid to cluster intelligence.Cluster network is an important part of cluster intelligence, the security of information interaction has attracted much attention, and cluster key management has become a research hotspot in network information security.In recent years, many cluster key management schemes have been proposed, which provide effective solutions for information security interaction of complex cluster network systems.The existing cluster key management schemes were analyzed and summarized, and the future research direction and application scenarios were discussed.The typical three-layer cluster network model was introduced, including the control layer, cluster head layer and node layer.The characteristics of cluster network were summarized, such as large number and scale, dynamic topology change, and hierarchical cluster heterogeneity.According to the key management strategy and cluster networking scenarios, the cluster key management process before and after the network deployment was summarized.The key management evaluation index was analyzed from the aspects of security, efficiency, and flexibility.Then, three key management schemes including pre-distribution management, healing management and dynamic management were discussed.Their basic ideas, advantages and disadvantages were analyzed, and their performance from the aspects of techniques, security, flexibility, and efficiency was compared.Besides, the research hotspots related to cluster key management were prospected from cross-domain heterogeneity, cluster authentication, healing mechanism, and technology fusion.The security function of cluster key management in future application scenarios such as ubiquitous IoT, all-domain operation, and smart city was discussed.

Papers and Reports

Dynamic and efficient vehicular cloud management scheme with privacy protection

Min XIAO, Tao YAO, Yuanni LIU, Yonghong HUANG

2022, 8(6):  70-83.  doi:10.11959/j.issn.2096-109x.2022083

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The vehicular cloud (VC) formed by vehicles is used for localization processing and consumption of traffic sensing data to achieve timely intelligent traffic management.The vehicle cloud is highly dynamic, self-organizing and timely, in which the identity and location privacy of vehicle users need to be protected as this poses challenges to the vehicular cloud management.A dynamic and self-organizing vehicle cloud management scheme based on the asymmetric group key agreement protocol was designed, where the vehicle cloud is automatically formed through the self-organized group key agreement of vehicles.The group key was used to control the provision and access of vehicle cloud services, and the dynamic management of the vehicle cloud was implemented through group key update.The scheme used traceable one-time pseudonym technology to achieve anonymous authentication and conditional privacy protection of vehicle users, and the group key agreement stage only included one bilinear pair operation to achieve high efficiency.In addition, the key negotiation and update process used lightweight signatures, supporting batch verification, to achieve efficient message source authentication and integrity authentication.Then the security and efficiency of vehicle cloud communications in the self-organizing environment can be ensured.The dynamic key update mechanism of the key agreement protocol realized the dynamic joining or exiting of vehicles in the vehicle cloud, adapting to the dynamic characteristics of the vehicle cloud.Under the random oracle model and the difficult assumption of the inverse computational Diffie Hellman (ICDH) problem, it was proved that the asymmetric group key agreement scheme satisfied the selective-plaintext security.The security analysis shows that the scheme can protect the identity and location privacy of vehicle users, realize the legal tracking of malicious vehicles, and ensure the confidentiality, integrity and anti-counterfeiting of communications, as well as the forward security of vehicle cloud dynamic management.The performance comparison analysis shows that this scheme has certain advantages in communication and computing efficiency under the condition of the same function and security level.

Encrypted traffic classification method based on convolutional neural network

Rongna XIE, Zhuhong MA, Zongyu LI, Ye TIAN

2022, 8(6):  84-91.  doi:10.11959/j.issn.2096-109x.2022077

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Aiming at the problems of low accuracy, weak generality, and easy privacy violation of traditional encrypted network traffic classification methods, an encrypted traffic classification method based on convolutional neural network was proposed, which avoided relying on original traffic data and prevented overfitting of specific byte structure of the application.According to the data packet size and arrival time information of network traffic, a method to convert the original traffic into a two-dimensional picture was designed.Each cell in the histogram represented the number of packets with corresponding size that arrive at the corresponding time interval, avoiding reliance on packet payloads and privacy violations.The LeNet-5 convolutional neural network model was optimized to improve the classification accuracy.The inception module was embedded for multi-dimensional feature extraction and feature fusion.And the 1*1 convolution was used to control the feature dimension of the output.Besides, the average pooling layer and the convolutional layer were used to replace the fully connected layer to increase the calculation speed and avoid overfitting.The sliding window method was used in the object detection task, and each network unidirectional flow was divided into equal-sized blocks, ensuring that the blocks in the training set and the blocks in the test set in a single session do not overlap and expanding the dataset samples.The classification experiment results on the ISCX dataset show that for the application traffic classification task, the average accuracy rate reaches more than 95%.The comparative experimental results show that the traditional classification method has a significant decrease in accuracy or even fails when the types of training set and test set are different.However, the accuracy rate of the proposed method still reaches 89.2%, which proves that the method is universally suitable for encrypted traffic and non-encrypted traffic.All experiments are based on imbalanced datasets, and the experimental results may be further improved if balanced processing is performed.

Network security of the National Natural Science Foundation of China: today and prospects

Dong LI, Yanni HAO, Shenghui PENG, Ruijie ZI, Ximeng LIU

2022, 8(6):  92-101.  doi:10.11959/j.issn.2096-109x.2022076

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The National Natural Science Foundation of China (hereinafter referred to as the Natural Science Foundation of China) is responsible for effectively utilizing the National Natural Science Foundation of China, supporting basic research, adhering to free exploration, playing a guiding role, and discovering and cultivating science and technology in accordance with the national guidelines, policies and plans for the promotion of scientific and technological progress and coordinated economic and social development.With the continuous development of new productive forces represented by information technology, the Natural Science Foundation of China has been committed to promoting the informatization and intelligence of fund management.With the increasing complexity of business types, various types of network attacks, such as information leakage attacks, are encountered in the construction of informatization and make network security face severe challenges.The network security construction of the Natural Science Foundation of China was took as the main line and the network security construction of the existing platform was introduced.At present, a network security system structure with the science fund project management as the core has been established to ensure the safe and stable operation of the network system.The main information systems of the Natural Science Foundation of China (Natural Science Foundation Shared Service Network, business department website, email system) and its main threats were analyzed and introduced.Then the thoughts and suggestions in the follow-up informatization and network security construction were given.The Natural Science Foundation of China will start the construction of a new generation of secure network.Under the premise of fully considering the characteristics of science fund review, management, and open sharing, it will achieve the overall goal of “smarter, safer, and better” and carry out network security system construction for relevant units.

Lightweight defense mechanism against adversarial attacks via adaptive pruning and robust distillation

Bin WANG, Simin LI, Yaguan QIAN, Jun ZHANG, Chaohao LI, Chenming ZHU, Hongfei ZHANG

2022, 8(6):  102-109.  doi:10.11959/j.issn.2096-109x.2022074

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Adversarial training is one of the commonly used defense methods against adversarial attacks, by incorporating adversarial samples into the training process.However, the effectiveness of adversarial training heavily relied on the size of the trained model.Specially, the size of trained models generated by the adversarial training will significantly increase for defending against adversarial attacks.This imposes constraints on the usability of adversarial training, especially in a resource-constraint environment.Thus, how to reduce the model size while ensuring the robustness of the trained model is a challenge.To address the above issues, a lightweight defense mechanism was proposed against adversarial attacks, with adaptive pruning and robust distillation.A hierarchically adaptive pruning method was applied to the model generated by adversarial training in advance.Then the trained model was further compressed by a modified robust distillation method.Experimental results on CIFAR-10 and CIFAR-100 datasets showed that our hierarchically adaptive pruning method presented stronger robustness under various FLOP than the existing pruning methods.Moreover, the fusion of pruning and robust distillation presented higher robustness than the state-of-art robust distillation methods.Therefore, the experimental results prove that the proposed method can improve the usability of the adversarial training in the IoT edge computing environment.

Image inpainting forensics method based on dual branch network

Dengyong ZHANG, Huang WEN, Feng LI, Peng CAO, Lingyun XIANG, Gaobo YANG, Xiangling DING

2022, 8(6):  110-122.  doi:10.11959/j.issn.2096-109x.2022084

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Image inpainting is a technique that uses information from known areas of an image to repair missing or damaged areas of the image.Image editing software based on it has made it easy to edit and modify the content of digital images without any specialized foundation.When image inpainting techniques are used to maliciously remove the content of an image, it will cause confidence crisis on the real image.Current researches in image inpainting forensics can only effectively detect a certain type of image inpainting.To address this problem, a passive forensic method for image inpainting was proposed, which is based on a two-branch network.The high-pass filtered convolutional network in the dual branch first used a set of high-pass filters to attenuate the low-frequency components in the image.Then features were extracted using four residual blocks, and two transposed convolutions were performed with 4x up-sampling to zoom in on the feature map.And thereafter a 5×5 convolution was used to attenuate the tessellation artifacts from the transposed convolutions to generate a discriminative feature map on the high-frequency components of the image.The dual-attention feature fusion branch in the dual branch first added a local binary pattern feature map to the image using a preprocessing block.Then the dual-attention convolution block was used to adaptively integrate the image’s local features and global dependencies to capture the differences in content and texture between the inpainted and pristine regions of the image.Additionally, the features extracted from the dual-attention convolution block were fused, and the feature maps were up-sampled identically to generate the discriminative image content and texture on the feature maps.The extensive experimental results show the proposed method improved the F1 score by 2.05% and the Intersection over Union(IoU) by 3.53% for the exemplar-based method and by 1.06% and 1.22% for the deep-learning-based method in detecting the inpainted region of the removed object.Visualization of the results shows that the edges of the removed objects can be accurately located on the detected inpainted area.

Metrics for code obfuscation based on symbolic execution and N-scope complexity

Yuqiang XIAO, Yunfei GUO, Yawen WANG

2022, 8(6):  123-134.  doi:10.11959/j.issn.2096-109x.2022085

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Code obfuscation has been well developed as mitigated endogenous security technology, to effectively resist MATE attacks (e.g.reverse engineering).And it also has important value for the reasonable metrics of code obfuscation effect.Since symbolic execution is widely used in anti-obfuscation attacks, metrics for code obfuscation resilience can refer to the efforts of generating input test set for executing all program paths.However, some adversarial techniques could reduce the symbol execution efficiency significantly based on the nested structure of the program and increase the error of the resilience reference.To solve the above problems, a metrics for code obfuscation was proposed based on symbolic execution and N-scope complexity.The obfuscation resilience was defined with symbolic execution time and obfuscation potency was defined based on the proposed N-scope complexity for better robustness in measuring the resilience of multi-nested structure programs.Furthermore, the correlation analysis of obfuscation effect was proposed and the effect was quantified by symbolic execution and control flow diagram extraction of programs.Over 4000 obfuscated programs from 3 open-sourced assemblies were evaluated with proposed metrics in the experiment, which indicated the generalization performance and practicality of the metrics.And an example of this metrics application was presented in a simulated obfuscation scenario which provided references of obfuscation technology metrics and obfuscation configuration for obfuscation users.

Software diversity evaluation method based on the properties of ROP/JOP gadgets

Yuning CHI, Yunfei GUO, Yawen WANG, Hongchao HU

2022, 8(6):  135-145.  doi:10.11959/j.issn.2096-109x.2022086

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In order to reduce the risk of rapid spread of homogeneous attacks in network systems, and enhance network and software security, software diversification technologies are applied widely nowadays.Software diversification aims to generate functionally equivalent but internally changed program variants, thereby alter a single operating environment and mitigating homogenization attacks.The existing diversified technical evaluation index ROP gadgets survival rate is difficult to directly reflect the safety impact and the evaluation method is single.In order to evaluate the effectiveness of the diversification method more comprehensively and effectively, a software diversification evaluation method based on the properties of ROP/JOP gadgets is proposed, by analyzing common code reuse attacks, and turns abstract quantification into concrete indicators evaluates the security gain and effect of diversified methods from three aspects of space, time and quality.The method first discusses how diversification techniques affect ROP/JOP attacks according to the three properties of gadgets similarity, damage degree and availability.Nine kinds of diversification methods, such as instruction replacement, NOP insertion, and control flow flattening, are used to diversify the GNU coreutils assembly to generate diversification assembly.Experiments based on the property of gadgets are carried out on the diverse assemblies, and the effectiveness of different diversification methods and the impact on attacks are evaluated according to the experimental results.The experimental results show that this method can accurately evaluate the security gain of software diversification methods, the diversification technology will lead to the increase of the attack chain space required by the ROP/JOP attack, the longer time to construct the attack chain and the lower the attack success rate.The effects of different diversification methods are different, it has a guiding role for the follow-up research on diversified technologies with higher safety gains.

Lip forgery detection via spatial-frequency domain combination

Jiaying LIN, Wenbo ZHOU, Weiming ZHANG, Nenghai YU

2022, 8(6):  146-155.  doi:10.11959/j.issn.2096-109x.2022075

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In recent years, numerous “face-swapping” videos have emerged in social networks, one of the representatives is the lip forgery with speakers.While making life more entertaining for the public, it poses a significant crisis for personal privacy and property security in cyberspace.Currently, under non-destructive conditions, most of the lip forgery detection methods achieve good performance.However, the compression operations are widely used in practice especially in social media platforms, face recognition and other scenarios.While saving pixel and time redundancy, the compression operations affect the video quality and destroy the coherent integrity of pixel-to-pixel and frame-to-frame in the spatial domain, and then the degradation of its detection performance and even misjudgment of the real video will be caused.When the information in the spatial domain cannot provide sufficiently effective features, the information in the frequency domain naturally becomes a priority research object because it can resist compression interference.Aiming at this problem, the advantages of frequency information in image structure and gradient feedback were analyzed.Then the lip forgery detection via spatial-frequency domain combination was proposed, which effectively utilized the corresponding characteristics of information in spatial and frequency domains.For lip features in the spatial domain, an adaptive extraction network and a light-weight attention module were designed.For frequency features in the frequency domain, separate extraction and fusion modules for different components were designed.Subsequently, by conducting a weighted fusion of lip features in spatial domain and frequency features in frequency domain, more texture information was preserved.In addition, fine-grained constraints were designed during the training to separate the inter-class distance of real and fake lip features while closing the intra-class distance.Experimental results show that, benefiting from the frequency information, the proposed method can enhance the detection accuracy under compression situation with certain transferability.On the other hand, in the ablation study conducted on the core modules, the results verify the effectiveness of the frequency component for anti-compression and the constraint of the dual loss function in training.

Identity-based anonymous cloud auditing scheme with compact tags

Chenxin LU, Bing CHEN, Ning DING, Liquan CHEN, Ge WU

2022, 8(6):  156-168.  doi:10.11959/j.issn.2096-109x.2022087

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Cloud storage has the advantages of high efficiency and scalability.Users can save local storage cost and share data with others through cloud storage technology.However, when data is uploaded to cloud servers, its owner also loses the physical control, and hence there needs a corresponding mechanism to ensure the integrity of data stored in the cloud.The Provable Data Possession (PDP) mechanism allows users or a Third-Party Auditor (TPA) appointed by the user to verify data integrity.In practice, data is usually maintained by multiple users.Users may reveal their identities while making an integrity verification request in traditional auditing processes.Anonymous cloud auditing ensures anonymity of users against the TPA during auditing.Currently, in identity-based systems, anonymous cloud auditing schemes usually resort to identity-based ring signature or group signature schemes.As a result, the size of a tag is related to the number of users, which makes it not compact and causes high storage cost.In order to solve this issue, a general construction of identity-based anonymous cloud auditing scheme was proposed.With a signature scheme and an anonymous cloud auditing scheme, a concrete identity-based anonymous cloud auditing scheme based on the general construction was proposed.It combined theBLS signature and an anonymous cloud auditing scheme with compact tags.The main advantage of this solution is that the tags are compact, which can significantly reduce storage cost and improve storage efficiency.Furthermore, the uncheatability and anonymity of the scheme are proved.

Online medical privacy protection strategy under information value-added mechanism

Shengzhi MING, Jianming ZHU, Zhiyuan SUI, Xian ZHANG

2022, 8(6):  169-177.  doi:10.11959/j.issn.2096-109x.2022072

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China’s economic level and people’s living standards have developed rapidly in recent years, and the medical level and medical technology have made breakthroughs continuously.With the promotion and deepening of“Internet Plus” to business model innovation in various fields, the development of “Internet Plus” medical has been rapidly developed.Due to the continuous development of data processing technologies such as machine learning and data mining, the risk of users’ personal medical data disclosure in the process of online medical treatment has also attracted the attention of researchers.Considering the deductibility of information, the discount mechanism was adopted to describe the change of user’s private information value in different stages of the game.Combined with the current research status in the field of online medical privacy protection motivation, how to mobilize the enthusiasm of both players from the level of privacy protection motivation was explored with game analysis.In view of the game characteristics of users’ strong willingness to continually use the online medical platform and intermittently provide privacy, the repeated game method was adopted to better describe the game process between users and the online medical platform.The tendency change law of the players on both sides of the game was obtained.Moreover, the Nash equilibrium of the game model was analyzed under different model parameters and the change trend of the game strategy of both sides with the progress of the game stage.When the parameters were met 2(c_p-c_n)≥l_p(p_n-p_p), the user started to choose from “agree to share private data” to “refuse to share private data”.The above conclusion was verified by simulation experiments.Based on the above conclusions, from the perspective of online medical platform and users, policy suggestions on how to realize privacy protection from the level of privacy protection motivation in the process of online medical treatment were given.