Journal of Information Security and Applications最新文献_第3页

Editorial: Special issue on software protection and attacks 社论：软件保护与攻击特刊

IF 3.8 2区计算机科学

Journal of Information Security and Applications Pub Date : 2024-09-20 DOI: 10.1016/j.jisa.2024.103889

Michele Ianni, Mila Dalla Preda, Kim-Kwang Raymond Choo, Miguel Pupo Correia

引用次数: 0

HierFedPDP:Hierarchical federated learning with personalized differential privacy HierFedPDP：具有个性化差异隐私的分层联合学习

IF 3.8 2区计算机科学

Journal of Information Security and Applications Pub Date : 2024-09-18 DOI: 10.1016/j.jisa.2024.103890

Sitong Li , Yifan Liu , Fan Feng , Yi Liu , Xiaofei Li , Zhenpeng Liu

{"title":"HierFedPDP:Hierarchical federated learning with personalized differential privacy","authors":"Sitong Li , Yifan Liu , Fan Feng , Yi Liu , Xiaofei Li , Zhenpeng Liu","doi":"10.1016/j.jisa.2024.103890","DOIUrl":"10.1016/j.jisa.2024.103890","url":null,"abstract":"<div><p>Federated Learning (FL) is an innovative approach that enables multiple parties to collaboratively train a machine learning model while keeping their data private. This method significantly enhances data security as it avoids sharing raw data among participants. However, a critical challenge in FL is the potential leakage of sensitive information through shared model updates. To address this, differential privacy techniques, which add random noise to data or model updates, are used to safeguard individual data points from being inferred. Traditional approaches to differential privacy typically utilize a fixed privacy budget, which may not account for the varying sensitivity of data, potentially affecting model accuracy. To overcome these limitations, we introduce HierFedPDP, a new FL framework that optimizes data privacy and model performance. HierFedPDP employs a three-tier client–edge–cloud architecture, maximizing the use of edge computing to alleviate the computational load on the central server. At the core of HierFedPDP is a personalized local differential privacy mechanism that tailors privacy settings based on data sensitivity, thereby enhancing data protection while maintaining high utility. Our framework not only fortifies privacy but also improves model accuracy. Specifically, experiments on the MNIST dataset show that HierFedPDP outperforms existing models, increasing accuracy by 0.84% to 2.36%, and CIFAR-10 has also achieved effective improvements. This research advances the capabilities of FL in protecting data privacy and provides valuable insights for designing more efficient distributed learning systems.</p></div>","PeriodicalId":48638,"journal":{"name":"Journal of Information Security and Applications","volume":"86 ","pages":"Article 103890"},"PeriodicalIF":3.8,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142243778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Enhanced Fourier–Mellin domain watermarking for social networking platforms 针对社交网络平台的增强型傅立叶-梅林域水印技术

IF 3.8 2区计算机科学

Journal of Information Security and Applications Pub Date : 2024-09-17 DOI: 10.1016/j.jisa.2024.103884

Jinghong Xia , Hongxia Wang , Sani M. Abdullahi , Heng Wang , Fei Zhang , Bingling Luo

{"title":"Enhanced Fourier–Mellin domain watermarking for social networking platforms","authors":"Jinghong Xia , Hongxia Wang , Sani M. Abdullahi , Heng Wang , Fei Zhang , Bingling Luo","doi":"10.1016/j.jisa.2024.103884","DOIUrl":"10.1016/j.jisa.2024.103884","url":null,"abstract":"<div><p>Robustness to common hybrid distortions is a crucial requirement for effective watermarking, particularly on social networking platforms (SNPs). Images on SNPs undergo complex attacks initiated by both platforms and users, involving diverse distortion operations. However, there are few image watermarking schemes designed to handle such hybrid attacks effectively. Existing schemes, especially those based on the Fourier-Mellin domain, often struggle due to their susceptibility to single attacks. For instance, the ring watermark structure in the frequency domain is prone to distortion, leading to difficulties in mapping watermark information and causing streak diffraction phenomena in the image. Additionally, these schemes lack robustness against large-size image downsampling and image flipping attacks on SNPs. To address these limitations, this paper introduces an enhanced robust watermarking framework tailored for SNPs. The framework comprises three key modules: a module to stabilize the ring watermark structure, an adaptive embedding strength and range module, and a sliding window and flip state detection module. These modules, coupled with log-polar mapping (LPM) in the Fourier-Mellin domain, effectively mitigate the lack of robustness to specific attacks, resulting in comprehensive robustness for the entire framework. Numerous experiments demonstrate that our proposed scheme outperforms other state-of-the-art (SOTA) works in handling hybrid distortions on SNPs.</p></div>","PeriodicalId":48638,"journal":{"name":"Journal of Information Security and Applications","volume":"86 ","pages":"Article 103884"},"PeriodicalIF":3.8,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142243915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Self-sovereign identity management in ciphertext policy attribute based encryption for IoT protocols 物联网协议基于密码策略属性加密的自主权身份管理

IF 3.8 2区计算机科学

Journal of Information Security and Applications Pub Date : 2024-09-11 DOI: 10.1016/j.jisa.2024.103885

Weichu Deng , Jin Li , Hongyang Yan , Arthur Sandor Voundi Koe , Teng huang , Jianfeng Wang , Cong Peng

{"title":"Self-sovereign identity management in ciphertext policy attribute based encryption for IoT protocols","authors":"Weichu Deng , Jin Li , Hongyang Yan , Arthur Sandor Voundi Koe , Teng huang , Jianfeng Wang , Cong Peng","doi":"10.1016/j.jisa.2024.103885","DOIUrl":"10.1016/j.jisa.2024.103885","url":null,"abstract":"<div><p>In the Internet of Things, access control and identity management rely on centralized platforms. However, centralized platforms will compromise user privacy with identity leakage. Self-sovereign identity (SSI) is a novel model for identity management that does not require third-party centralized authority. Thus, SSI is a potential solution to the identity management problem in IoT access control. This paper’s motivation is to address the problems of lack of identity sovereignty, centralized authorization, and high computational overhead for IoT access control. We propose a novel access control scheme for IoT that decentralizes identity management and tackles single-point-of-failure issues. This scheme leverages ciphertext policy attribute-based encryption (CP-ABE) and SSI to achieve the overall goal. Specifically, Our scheme eliminates the central authority and empowers users to manage their identity, allowing users to decide what attributes they disclose. Regarding the distribution of roles in the architecture, this paper follows the generic SSI model (ISSUER–HOLDER—VERIFIER) that allows a user to access a service from a service provider. To enable real-world deployment of our scheme, we establish an attribute authorization authority(such as the government) as a trusted identity point of entry. Users generate decentralized identifiers to enjoy services of interest in a privacy-preserving manner. The analysis demonstrates the practicality and superiority of our scheme. Our scheme requires less computation and is suitable for resource-constrained IoT scenarios.</p></div>","PeriodicalId":48638,"journal":{"name":"Journal of Information Security and Applications","volume":"86 ","pages":"Article 103885"},"PeriodicalIF":3.8,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142169320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Shared file protection against unauthorised encryption using a Buffer-Based Signature Verification Method 使用基于缓冲区的签名验证方法保护共享文件，防止未经授权的加密

IF 3.8 2区计算机科学

Journal of Information Security and Applications Pub Date : 2024-09-09 DOI: 10.1016/j.jisa.2024.103873

Arash Mahboubi , Seyit Camtepe , Keyvan Ansari , Marcin Pawłowski , Paweł Morawiecki , Hamed Aboutorab , Josef Pieprzyk , Jarek Duda

{"title":"Shared file protection against unauthorised encryption using a Buffer-Based Signature Verification Method","authors":"Arash Mahboubi , Seyit Camtepe , Keyvan Ansari , Marcin Pawłowski , Paweł Morawiecki , Hamed Aboutorab , Josef Pieprzyk , Jarek Duda","doi":"10.1016/j.jisa.2024.103873","DOIUrl":"10.1016/j.jisa.2024.103873","url":null,"abstract":"<div><p>Understanding the attributes of critical data and implementing suitable security measures help organisations bolster their data-protection strategies and diminish the potential impacts of ransomware incidents. Unauthorised extraction and acquisition of data are the principal objectives of most cyber invasions. We underscore the severity of this issue using a recent attack by the Clop ransomware group, which exploited the MOVEit Transfer vulnerability and bypassed network-detection mechanisms to exfiltrate data via a Command and Control server. As a countermeasure, we propose a method called Buffer-Based Signature Verification (BBSV). This approach involves embedding 32-byte tags into files prior to their storage in the cloud, thus offering enhanced data protection. The BBSV method can be integrated into software like MOVEit Secure Managed File Transfer, thereby thwarting attempts by ransomware to exfiltrate data. Empirically tested using a BBSV prototype, our approach was able to successfully halt the encryption process for 80 ransomware instances from 70 ransomware families. BBSV not only stops the encryption but also prevents data exfiltration when data are moved or written from the original location by adversaries. We further develop a hypothetical exploit scenario in which an adversary manages to bypass the BBSV, illicitly transmits data to a Command and Control server, and then removes files from the original location. We construct an extended state space, in which each state represents a tuple that integrates user authentication and system components at the filesystem level.</p></div>","PeriodicalId":48638,"journal":{"name":"Journal of Information Security and Applications","volume":"86 ","pages":"Article 103873"},"PeriodicalIF":3.8,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2214212624001753/pdfft?md5=68d74f2ecd64919a7bca1979c6adbfbd&pid=1-s2.0-S2214212624001753-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142157893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Detection of Evasive Android Malware Using EigenGCN 利用 EigenGCN 检测规避性安卓恶意软件

IF 3.8 2区计算机科学

Journal of Information Security and Applications Pub Date : 2024-09-07 DOI: 10.1016/j.jisa.2024.103880

Teenu S. John , Tony Thomas , Sabu Emmanuel

{"title":"Detection of Evasive Android Malware Using EigenGCN","authors":"Teenu S. John , Tony Thomas , Sabu Emmanuel","doi":"10.1016/j.jisa.2024.103880","DOIUrl":"10.1016/j.jisa.2024.103880","url":null,"abstract":"<div><p>Recently there is an upsurge in Android malware that use obfuscation and repackaging techniques for evasion. Malware may also combine both these techniques to create stealthy adversarial mimicry samples to launch mimicry attacks. In mimicry attacks, the adversary makes sure that the static and dynamic features present in the crafted malware mimics the features present in the legitimate applications. In such cases, the existing detection mechanisms may become less effective. We found that the malicious nature of Android applications can be determined by identifying certain subgraphs that appear in their system call graphs. These subgraphs can be determined with the help of spectral clustering mechanism present in EigenGCN. With this, the system call graph <span><math><mi>G</mi></math></span> will be partitioned into two subgraphs <span><math><msub><mrow><mi>G</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span> and <span><math><msub><mrow><mi>G</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span>, in which the malicious functionality if any will be present in the subgraph <span><math><msub><mrow><mi>G</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span>. The graph Fourier transform based pooling technique in EigenGCN then computes the features of the subgraphs in the form of graph signals. This graph signals serve as a robust signature to detect malware. The proposed mechanism gave an accuracy of 98.7% on common malware, 97.3% on obfuscated malware, 97.8% on repackaged malware, and 90% on adversarial mimicry malware datasets. As far as we know, this is the first work that proposes a malware detection mechanism, that can detect common as well as obfuscated, repackaged, and mimicry malware in Android.</p></div>","PeriodicalId":48638,"journal":{"name":"Journal of Information Security and Applications","volume":"86 ","pages":"Article 103880"},"PeriodicalIF":3.8,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142151348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Moment invariants based zero watermarking algorithm for trajectory data 基于矩不变式的轨迹数据零水印算法

IF 3.8 2区计算机科学

Journal of Information Security and Applications Pub Date : 2024-09-03 DOI: 10.1016/j.jisa.2024.103867

Na Ren , Yuchen Hu , Changqing Zhu , Shuitao Guo , Xianshu Zhu

{"title":"Moment invariants based zero watermarking algorithm for trajectory data","authors":"Na Ren , Yuchen Hu , Changqing Zhu , Shuitao Guo , Xianshu Zhu","doi":"10.1016/j.jisa.2024.103867","DOIUrl":"10.1016/j.jisa.2024.103867","url":null,"abstract":"<div><p>Zero watermarking is a lossless copyright protection technology that satisfies the need for copyright protection without compromising the accuracy of trajectory data. However, existing zero watermarking algorithms for trajectory data are unable to resist random deletion point attack. Therefore, a trajectory data zero watermarking algorithm based on moment invariants was proposed to address the problem. Firstly, two compression algorithms are utilized to extract feature points from the trajectory data. Then, a coordinate system is constructed using the minimum area bounding rectangle (MABR) of the feature points. Next, based on the constructed coordinate system, the feature points are divided into subtrajectories, and the linear moment invariants generated by the subtrajectories are calculated. Finally, the zero watermark information is constructed based on the linear moment invariants, and the watermark copyright information is generated by exclusive-ORing (XOR) it with the copyright image. Experimental results demonstrate that the zero watermark information constructed by the proposed algorithm has good uniqueness and strong robustness against random deletion, compression, and other common attacks. Furthermore, the proposed algorithm has good algorithm efficiency and is applicable to vector data with plane coordinates. The study makes a positive contribution to copyright protection for trajectory data and provides useful references for research on lossless watermarking of vector geographic data.</p></div>","PeriodicalId":48638,"journal":{"name":"Journal of Information Security and Applications","volume":"86 ","pages":"Article 103867"},"PeriodicalIF":3.8,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142129429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

P-Chain: Towards privacy-aware smart contract using SMPC P-Chain：使用 SMPC 实现隐私感知智能合约

IF 3.8 2区计算机科学

Journal of Information Security and Applications Pub Date : 2024-09-03 DOI: 10.1016/j.jisa.2024.103872

Yiqing Diao , Ayong Ye , Yuexin Zhang , Ji Zhang , Li Xu

{"title":"P-Chain: Towards privacy-aware smart contract using SMPC","authors":"Yiqing Diao , Ayong Ye , Yuexin Zhang , Ji Zhang , Li Xu","doi":"10.1016/j.jisa.2024.103872","DOIUrl":"10.1016/j.jisa.2024.103872","url":null,"abstract":"<div><p>Smart contract, as the representative application of blockchain, has recently fueled extensive research interests from both academia and industry. However, with its wide applications, the weaknesses of smart contract have been gradually revealed. The major barrier to the widespread adoption of smart contract involves concerns about on-chain privacy which refers to the details of input/output privacy. To address privacy concerns, we propose in this paper, P-Chain, a privacy-aware framework for smart contracts of permissioned blockchain to protect sensitive data of users based on Secure Multi-party Computation (SMPC). Unlike existing work that suffer several key drawbacks, including introducing a third party who could get the details of the deal, and high overhead for on-chain and off-chain communication, as well as lacking a privacy protection for output data, we enhance the privacy protection for smart contracts system by adding a new secure multi-party computation layer in P-Chain. Through secure multi-party computing, sensitive inputs of smart contracts are divided into multiple sub-inputs and sent to computing participants for operation respectively, which ensures that each participant can only access part of the user’s information. A stochastic strategy based on <span><math><mrow><mo>(</mo><mi>t</mi><mo>;</mo><mi>n</mi><mo>)</mo></mrow></math></span> threshold secret sharing to select calculating parties is also been proposed, which makes it difficult for an attacker to aggregate <span><math><mi>t</mi></math></span> of <span><math><mi>n</mi></math></span> participants for launching a collusive attack. In addition, we propose the output privacy protection method that makes it possible to reach a consensus without the need to know the output. The extensive experimental evaluation and analysis demonstrate that our scheme enjoys the advantages of calculation correctness, input–output privacy as well as anti-collusion.</p></div>","PeriodicalId":48638,"journal":{"name":"Journal of Information Security and Applications","volume":"86 ","pages":"Article 103872"},"PeriodicalIF":3.8,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142129428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Visualization-based comprehensive feature representation with improved EfficientNet for malicious file and variant recognition 基于可视化的综合特征表示与改进的 EfficientNet，用于识别恶意文件和变体

IF 3.8 2区计算机科学

Journal of Information Security and Applications Pub Date : 2024-09-03 DOI: 10.1016/j.jisa.2024.103865

Liangwei Yao , Bin Liu , Yang Xin

{"title":"Visualization-based comprehensive feature representation with improved EfficientNet for malicious file and variant recognition","authors":"Liangwei Yao , Bin Liu , Yang Xin","doi":"10.1016/j.jisa.2024.103865","DOIUrl":"10.1016/j.jisa.2024.103865","url":null,"abstract":"<div><p>Malicious file attacks seriously affect network and data security, and recognizing malicious files and variants is crucial for preventing network attacks. Faced with the challenge of traditional methods in quickly, effectively, and efficiently recognizing malicious files or variants, visualization-based feature representation methods have shown promising results. However, practical applications encounter issues such as loss of crucial information, high spatiotemporal overhead, and the need for model performance improvement. Therefore, this paper introduces a novel recognition framework focusing on feature representation and model performance. The framework uses the proposed <strong>v</strong>isualization-based <strong>c</strong>omprehensive <strong>f</strong>eature <strong>r</strong>epresentation method (VCFR) to extract file information into the Gray-Level Co-occurrence Matrix (GLCM), 2-gram frequency matrix, and interval 2-gram frequency matrix, followed by feature fusion to generate the three-channel RGB images. Subsequently, the proposed lightweight model is applied for recognizing those files, which utilizes ideas such as group convolution, channel shuffle, and attention mechanisms to improve model performance while significantly reducing model parameters, size, and FLOPs. In summary, through a series of experiments conducted on manually collected <strong>m</strong>alicious <strong>f</strong>ile <strong>d</strong>ataset (MFD) and public dataset MMCC, the proposed framework significantly outperformed other state-of-the-art technologies and has F1-Score as high as 94.10% and 98.58%, respectively, further verifying its outstanding effectiveness and efficiency.</p></div>","PeriodicalId":48638,"journal":{"name":"Journal of Information Security and Applications","volume":"86 ","pages":"Article 103865"},"PeriodicalIF":3.8,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142129334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Robust secret color image sharing anti-cropping and tampering in shares 稳健的秘密彩色图像共享，防止共享中的裁剪和篡改

IF 3.8 2区计算机科学

Journal of Information Security and Applications Pub Date : 2024-09-01 DOI: 10.1016/j.jisa.2024.103869

Shengyang Luo, Yaqi Liu, Xuehu Yan, Yuyuan Sun

{"title":"Robust secret color image sharing anti-cropping and tampering in shares","authors":"Shengyang Luo, Yaqi Liu, Xuehu Yan, Yuyuan Sun","doi":"10.1016/j.jisa.2024.103869","DOIUrl":"10.1016/j.jisa.2024.103869","url":null,"abstract":"<div><p>Secret image sharing (SIS) has excellent properties such as loss tolerance and relatively low computational complexity, providing a brand-new solution for image security protection. However, there has been little research on the robustness of SIS systems, such as how to resist cropping or malicious tampering in shares. Existing related schemes generally focus on grayscale images and suffer from issues such as lossy recovery, weak robustness, and serious pixel expansion, which are challenging to meet the requirements of high-quality sensitive image applications. In this regard, a robust SIS scheme for color images is proposed, which can resist large-scale cropping and malicious tampering in shares. According to the idea of “breaking up the whole cropped area into parts, repairing the shares independently”, the proposed scheme can realize lossless recovery of secret images through organic fusion of secret sharing, error-correcting code, and pixel re-arrangement techniques. Even if all the shares are cropped by 25%, it can still achieve lossless recovery regardless of whether the cropping positions intersect or overlap. It can also resist various malicious tampering (such as marking, defacing, and copy-move forgery) as well as image noise. Moreover, it avoids pixel expansion and requires no auxiliary encryption or preprocessing. Theoretical analysis and experimental results demonstrate that the proposed scheme is superior to existing schemes in terms of robustness and comprehensive performance, and is expected to promote the practical application of SIS.</p></div>","PeriodicalId":48638,"journal":{"name":"Journal of Information Security and Applications","volume":"85 ","pages":"Article 103869"},"PeriodicalIF":3.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142096958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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