3篇
您的检索式：作者名="Jingdian Yang"
|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Transparency order versus confusion coefficient:a case study of NIST lightweight cryptography S‑Boxes显示文摘Side-channel resistance is nowadays widely accepted as a crucial factor in deciding the security assurance level of cryptographic implementations.In most cases,non-linear components(e.g.S-Boxes)of cryptographic algorithms will be chosen as primary targets of side-channel attacks(SCAs).In order to measure side-channel resistance of S-Boxes,three theoretical metrics are proposed and they are reVisited transparency order(VTO),confusion coefficients variance(CCV),and minimum confusion coefficient(MCC),respectively.However,the practical effectiveness of these metrics remains still unclear.Taking the 4-bit and 8-bit S-Boxes used in NIST Lightweight Cryptography candidates as concrete examples,this paper takes a comprehensive study of the applicability of these metrics.First of all,we empirically investigate the relations among three metrics for targeted S-boxes,and find that CCV is almost linearly correlated with VTO,while MCC is inconsistent with the other two.Furthermore,in order to verify which metric is more effective in which scenarios,we perform simulated and practical experiments on nine 4-bit S-Boxes under the nonprofiled attacks and profiled attacks,respectively.The experiments show that for quantifying side-channel resistance of S-Boxes under non-profiled attacks,VTO and CCV are more reliable while MCC fails.We also obtain an interesting observation that none of these three metrics is suitable for measuring the resistance of S-Boxes against profiled SCAs.Finally,we try to verify whether these metrics can be applied to compare the resistance of S-Boxes with different sizes.Unfortunately,all of them are invalid in this scenario. | Huizhong Li Guang Yang Jingdian Ming Yongbin Zhou Chengbin Jin | 2021 | Cybersecurity2021，4，1： | 0 |
| 2 | Evaluation of Factors Affecting Driver’s Behaviors Using Association Rule显示文摘In this paper,association rule mining algorithm is utilized to analyze the correlations of various factors of causing traffic accidents,from which the relationship model of dangerous driving behaviors is established.In this model,the factors and their correlations include:ability of risk control,ability of driving self-confidence,individual characteristics,and incorrect driving operations.By selecting the drivers in the city of Chengdu to be the objects of investigation,a group of valid sample data is obtained.Based on these data,the Support and Confidence for association rules are analyzed.In the analysis,the two stage computing of Apriori algorithm programming is simulated,and from which some important rules are obtained.With these rules,departments of traffic administration can focus on these key factors in their processing of traffic transactions.By the training of drivers’skills and their physical and mental behaviors,the incorrect driving operations can be greatly reduced and the traffic safety can be effectively guaranteed. | Jingdian Yang | 2020 | 现代交通(中英文版)2020，8，1： | 0 |
| 3 | Transparency order versus confusion coefficient:a case study of NIST lightweight cryptography S-Boxes显示文摘Side-channel resistance is nowadays widely accepted as a crucial factor in deciding the security assurance level of cryptographic implementations.In most cases,non-linear components(e.g.S-Boxes)of cryptographic algorithms will be chosen as primary targets of side-channel attacks(SCAs).In order to measure side-channel resistance of S-Boxes,three theoretical metrics are proposed and they are revisited transparency order(VTO),confusion coefficients variance(CCV),and minimum confusion coefficient(MCC),respectively.However,the practical effectiveness of these metrics remains still unclear.Taking the 4-bit and 8-bit S-Boxes used in NIST Lightweight Cryptography candidates as concrete examples,this paper takes a comprehensive study of the applicability of these metrics.First of all,we empirically investigate the relations among three metrics for targeted S-boxes,and find that CCV is almost linearly correlated with VTO,while MCC is inconsistent with the other two.Furthermore,in order to verify which metric is more effective in which scenarios,we perform simulated and practical experiments on nine 4-bit S-Boxes under the non-profiled attacks and profiled attacks,respectively.The experiments show that for quantifying side-channel resistance of S-Boxes under non-profiled attacks,VTO and CCV are more reliable while MCC fails.We also obtain an interesting observation that none of these three metrics is suitable for measuring the resistance of S-Boxes against profiled SCAs.Finally,we try to verify whether these metrics can be applied to compare the resistance of S-Boxes with different sizes.Unfortunately,all of them are invalid in this scenario. | Huizhong Li Guang Yang Jingdian Ming Yongbin Zhou Chengbin Jin | 2022 | Cybersecurity2022，5，1： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员