Sekar R and Ravi G author a paper called Taylor Sun Flower Optimization-Based Compressive Sensing for Image Compression and Recovery, which appears in the The Computer Journal (Volume 66, issue 4, April 2023)
Sekar R和Ravi G撰写了一篇题为“基于Taylor Sun Flower优化的图像压缩和恢复压缩感知”的论文，发表在《计算机杂志》(第66卷第4期，2023年4月)上。
{"title":"Taylor Sun Flower Optimization-Based Compressive Sensing for Image Compression and Recovery","authors":"R. Sekar, G. Ravi","doi":"10.1093/comjnl/bxab202","DOIUrl":"https://doi.org/10.1093/comjnl/bxab202","url":null,"abstract":"\u0000 Sekar R and Ravi G author a paper called Taylor Sun Flower Optimization-Based Compressive Sensing for Image Compression and Recovery, which appears in the The Computer Journal (Volume 66, issue 4, April 2023)","PeriodicalId":21872,"journal":{"name":"South Afr. Comput. J.","volume":"10 1","pages":"873-887"},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86218036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Special Issue on Failed Approaches and Insightful Losses in Cryptology - Foreword","authors":"T. Ashur, C. Mitchell","doi":"10.1093/comjnl/bxac191","DOIUrl":"https://doi.org/10.1093/comjnl/bxac191","url":null,"abstract":"","PeriodicalId":21872,"journal":{"name":"South Afr. Comput. J.","volume":"12 1","pages":"1311"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84180133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Privacy and security in the medical field are major aspects to consider in the current era. This is due to the huge necessity for data among providers, payers and patients, respectively. Recently, more researchers are making their contributions in this field under different aspects. But, there need more enhancements concerning security. In this circumstance, this paper intends to propose a new IoT-dependent health care privacy preservation model with the impact of the machine learning algorithm. Here, the information or data from IoT devices is subjected to the proposed sanitization process via generating the optimal key. In this work, the utility of the machine learning model is the greatest gateway to generating optimal keys as it is already trained with the neural network. Moreover, identifying the optimal key is the greatest crisis, which is done by a new Improved Dragonfly Algorithm algorithm. Thereby, the sanitization process works, and finally, the sanitized data are uploaded to IoT. The data restoration is the inverse process of sanitization, which gives the original data. Finally, the performance of the proposed work is validated over state-of-the-art models in terms of sanitization and restoration analysis.
{"title":"Role of Machine Learning on Key Extraction for Data Privacy Preservation of Health Care Sectors in IoT Environment","authors":"P. N. Kathavate","doi":"10.1093/comjnl/bxad016","DOIUrl":"https://doi.org/10.1093/comjnl/bxad016","url":null,"abstract":"\u0000 Privacy and security in the medical field are major aspects to consider in the current era. This is due to the huge necessity for data among providers, payers and patients, respectively. Recently, more researchers are making their contributions in this field under different aspects. But, there need more enhancements concerning security. In this circumstance, this paper intends to propose a new IoT-dependent health care privacy preservation model with the impact of the machine learning algorithm. Here, the information or data from IoT devices is subjected to the proposed sanitization process via generating the optimal key. In this work, the utility of the machine learning model is the greatest gateway to generating optimal keys as it is already trained with the neural network. Moreover, identifying the optimal key is the greatest crisis, which is done by a new Improved Dragonfly Algorithm algorithm. Thereby, the sanitization process works, and finally, the sanitized data are uploaded to IoT. The data restoration is the inverse process of sanitization, which gives the original data. Finally, the performance of the proposed work is validated over state-of-the-art models in terms of sanitization and restoration analysis.","PeriodicalId":21872,"journal":{"name":"South Afr. Comput. J.","volume":"45 1","pages":"1549-1562"},"PeriodicalIF":0.0,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82864408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
When generating primes $p$ and $q$ for an RSA key, the algorithm specifies that if $p-1$ and $q-1$ must be relatively prime to the public exponent $e$. If this is not done, then the decryption exponent is not well defined. However, what if a software bug allows the generation of public parameters $N$ and $e$ of an RSA key with this property and then it is subsequently used for encryption? Though this may seem like a purely academic question, a software bug in a preview release of the Windows 10 operating system makes this question of more than purely theoretical. Without a well defined decryption exponent, plaintexts encrypted to such keys will be undecryptable thus potentially losing user data, a serious software defect. Though the decryption exponent is no longer well defined, it is in fact possible to recover the a small number of potential plaintexts, if the prime factors $p$ and $q$ of the public modulus $N$ are known. This paper presents an analysis of what steps fail in the RSA algorithm and derives a plaintext recovery algorithm. The runtime of this algorithm is $O(e)$ making it practical to use, and it has been implemented in python.
{"title":"Incorrectly Generated RSA Keys: How I Learned To Stop Worrying And Recover Lost Plaintexts","authors":"D. Shumow","doi":"10.1093/comjnl/bxac199","DOIUrl":"https://doi.org/10.1093/comjnl/bxac199","url":null,"abstract":"\u0000 When generating primes $p$ and $q$ for an RSA key, the algorithm specifies that if $p-1$ and $q-1$ must be relatively prime to the public exponent $e$. If this is not done, then the decryption exponent is not well defined. However, what if a software bug allows the generation of public parameters $N$ and $e$ of an RSA key with this property and then it is subsequently used for encryption? Though this may seem like a purely academic question, a software bug in a preview release of the Windows 10 operating system makes this question of more than purely theoretical. Without a well defined decryption exponent, plaintexts encrypted to such keys will be undecryptable thus potentially losing user data, a serious software defect. Though the decryption exponent is no longer well defined, it is in fact possible to recover the a small number of potential plaintexts, if the prime factors $p$ and $q$ of the public modulus $N$ are known. This paper presents an analysis of what steps fail in the RSA algorithm and derives a plaintext recovery algorithm. The runtime of this algorithm is $O(e)$ making it practical to use, and it has been implemented in python.","PeriodicalId":21872,"journal":{"name":"South Afr. Comput. J.","volume":"31 1","pages":"1342-1349"},"PeriodicalIF":0.0,"publicationDate":"2023-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77359452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hisaki Kobayashi, Y. Sudo, H. Kakugawa, T. Masuzawa
{"title":"A Self-Stabilizing Distributed Algorithm for the Generalized Dominating Set Problem With Safe Convergence","authors":"Hisaki Kobayashi, Y. Sudo, H. Kakugawa, T. Masuzawa","doi":"10.1093/comjnl/bxac021","DOIUrl":"https://doi.org/10.1093/comjnl/bxac021","url":null,"abstract":"","PeriodicalId":21872,"journal":{"name":"South Afr. Comput. J.","volume":"17 1","pages":"1452-1476"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75477431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhiruo Zhao, Lei Cao, Xi-liang Chen, Jun Lai, Legui Zhang
{"title":"Improvement of MADRL Equilibrium Based on Pareto Optimization","authors":"Zhiruo Zhao, Lei Cao, Xi-liang Chen, Jun Lai, Legui Zhang","doi":"10.1093/comjnl/bxac027","DOIUrl":"https://doi.org/10.1093/comjnl/bxac027","url":null,"abstract":"","PeriodicalId":21872,"journal":{"name":"South Afr. Comput. J.","volume":"66 1","pages":"1573-1585"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78423213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"F2SO: An Energy Efficient Cluster Based Routing Protocol Using Fuzzy Firebug Swarm Optimization Algorithm in WSN","authors":"K. Suresh, S. Mole, A. Joseph Selva Kumar","doi":"10.1093/comjnl/bxac002","DOIUrl":"https://doi.org/10.1093/comjnl/bxac002","url":null,"abstract":"","PeriodicalId":21872,"journal":{"name":"South Afr. Comput. J.","volume":"258 1","pages":"1126-1138"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78458010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Horizontal and vertical scalability have been widely studied in the context of computational resources. However, with the exponential growth in the number of connected objects, functional scalability (in terms of the size of software systems) is rapidly becoming a central challenge for building efficient service-oriented IoT systems that generate huge volumes of data continuously. As systems scale up, a centralised approach for moving data between services becomes infeasible because it leads to a single performance bottleneck. A distributed approach avoids such a bottleneck but it incurs additional network traffic as data streams pass through multiple mediators. Decentralised data exchange is the only solution for realising totally efficient IoT systems, since it avoids a single performance bottleneck and dramatically minimises network traffic. In this paper, we present a functionally scalable approach that separates data and control for the realisation of decentralised data flows in service-oriented IoT systems. Our approach is evaluated empirically, and the results show that it scales well with the size of IoT systems by substantially reducing both the number of data flows and network traffic in comparison with distributed data flows.
{"title":"Decentralized Data Flows for the Functional Scalability of Service-Oriented IoT Systems","authors":"Damian Arellanes, K. Lau, R. Sakellariou","doi":"10.1093/comjnl/bxac023","DOIUrl":"https://doi.org/10.1093/comjnl/bxac023","url":null,"abstract":"Horizontal and vertical scalability have been widely studied in the context of computational resources. However, with the exponential growth in the number of connected objects, functional scalability (in terms of the size of software systems) is rapidly becoming a central challenge for building efficient service-oriented IoT systems that generate huge volumes of data continuously. As systems scale up, a centralised approach for moving data between services becomes infeasible because it leads to a single performance bottleneck. A distributed approach avoids such a bottleneck but it incurs additional network traffic as data streams pass through multiple mediators. Decentralised data exchange is the only solution for realising totally efficient IoT systems, since it avoids a single performance bottleneck and dramatically minimises network traffic. In this paper, we present a functionally scalable approach that separates data and control for the realisation of decentralised data flows in service-oriented IoT systems. Our approach is evaluated empirically, and the results show that it scales well with the size of IoT systems by substantially reducing both the number of data flows and network traffic in comparison with distributed data flows.","PeriodicalId":21872,"journal":{"name":"South Afr. Comput. J.","volume":"8 1","pages":"1477-1506"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81298707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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