基于高阶异构度的执行体动态调度算法

doi:10.11959/j.issn.1000-436x.2022055

Abstract

Abstract:

At present, most isomer scheduling models in DHR systems only considered second-order isomerism and lack dynamics.In order to solve these problems, a dynamic scheduling algorithm was proposed, which combined heterogeneity and dynamics by determining a scheduling scheme with maximum scheduling value.The value was obtained by combining high-order heterogeneity and historical information.The experimental results show that the proposed algorithm has better defense capabilities than other scheduling algorithms, and its strategy can achieve a balance of dynamics and security.

Key words: mimic defense, high-order heterogeneity, negative feedback, dynamic heterogeneous redundancy, executive scheduling

CLC Number:

TP393.08

Hongyong JIA, Yunfei PAN, Wenhe LIU, Junjie ZENG, Jianhui ZHANG. Executive dynamic scheduling algorithm based on high-order heterogeneity[J]. Journal on Communications, 2022, 43(3): 233-245.

Figures/Tables 25

高阶异构度	计算式
H ⁽¹⁾	0
H ⁽²⁾	$- (\sum S^{(2)})$
H ⁽³⁾	$- (\sum S^{(2)} - 2 \sum S^{(3)})$
H ⁽⁴⁾	$- (\sum S^{(3)} - 3 \sum S^{(4)})$
H ⁽⁵⁾	$- (\sum S^{(3)} - 3 \sum S^{(4)} + 6 \sum S^{(5)})$

算法	失效率
HFAWA	$\frac{\sum_{i = 1}^{τ_{i}} N_{i}^{(⌈ \frac{k}{2} ⌉)} \|_{\min (N^{(k)} \|_{\min (N^{(k - 1)} \|_{\min (...)} + P (HI))} + P (H I))}}{N_{sum}}$
FAWA	$\frac{\sum_{i = 1}^{τ_{i}} N_{i}^{(⌈ \frac{k}{2} ⌉)} \|_{\min (P (H I))}}{N_{sum}}$
Ramdom, FIFO	$\frac{\sum_{i = 1}^{τ_{i}} N_{i}^{(⌈ \frac{k}{2} ⌉)}}{N_{sum}}$
H2	$\frac{\sum_{i = 1}^{τ_{i}} N_{i}^{(⌈ \frac{k}{2} ⌉)} \|_{\min (\bar{N_{}^{(2)}} + P (H I))}}{N_{sum}}$

实验方式	运行池大小	等待池大小	异构执行体容量
碰撞实验	5	20	10
LSA实验	5	20	${\begin{cases} 10 ，威胁数 \leq 100 \\ \frac{威胁数}{10} ，威胁数＞ 100 \end{cases}$

References 28

[1]	ZHENG J J , NAMIN A S . A survey on the moving target defense strategies:an architectural perspective[J]. Journal of Computer Science and Technology, 2019,34(1): 207-233.
[2]	石乐义, 郭宏彬, 温晓 ,等. 端信息跳扩混合的主动网络防御技术研究[J]. 通信学报, 2019,40(5): 125-135.
	SHI L Y , GUO H B , WEN X ,et al. Research on end hopping and spreading for active cyber defense[J]. Journal on Communications, 2019,40(5): 125-135.
[3]	何永忠, 陈美玲 . 基于协议的拟态研究综述[J]. 北京交通大学学报, 2016,40(5): 1-8.
	HE Y Z , CHEN M L . Protocol mimicry technique and its development[J]. Journal of Beijing Jiaotong University, 2016,40(5): 1-8.
[4]	VANO-GARCIA F , MARCO-GISBERT H , . KASLR-MT:kernel address space layout randomization for multi-tenant cloud systems[J]. Journal of Parallel and Distributed Computing, 2020,137: 77-90.
[5]	马多贺, 李琼, 林东岱 . 基于POF的网络窃听攻击移动目标防御方法[J]. 通信学报, 2018,39(2): 73-87.
	MA D H , LI Q , LIN D D . Moving target defense against network eavesdropping attack using POF[J]. Journal on Communications, 2018,39(2): 73-87.
[6]	KRYLOV V , KRAVTSOV K . Principles of network security protocols based on dynamic address space randomization[J]. Journal of Communication and Computer, 2016,13(2): 77-89.
[7]	FENSKE E , BROWN D , MARTIN J ,et al. Three years later:a study of MAC address randomization in mobile devices and when it succeeds[J]. Proceedings on Privacy Enhancing Technologies, 2021,2021(3): 164-181.
[8]	马博林, 张铮, 陈源 ,等. 基于指令集随机化的抗代码注入攻击方法[J]. 信息安全学报, 2020,5(4): 30-43.
	MA B L , ZHANG Z , CHEN Y ,et al. The defense method for code-injection attacks based on instruction set randomization[J]. Journal of Cyber Security, 2020,5(4): 30-43.
[9]	郝志宇, 翟健宏, 云晓春 ,等. 动态路由模拟策略研究[J]. 通信学报, 2007,28(12): 19-24.
	HAO Z Y , ZHAI J H , YUN X C ,et al. Research on dynamic routing mechanism in network simulation[J]. Journal on Communications, 2007,28(12): 19-24.
[10]	邬江兴 . 网络空间拟态安全防御[J]. 保密科学技术, 2014(10): 4-9,1.
	WU J X . Mimic security defense in cyberspace[J]. Secrecy Science and Technology, 2014(10): 4-9,1.
[11]	姜远海 . 基于分离映射的网络层主动变迁技术研究[D]. 北京:北京交通大学, 2016.
	JIANG Y H . Research on active change technology of network layer based on separation mapping[D]. Beijing:Beijing Jiaotong University, 2016.
[12]	宋克, 刘勤让, 魏帅 ,等. 基于拟态防御的以太网交换机内生安全体系结构[J]. 通信学报, 2020,41(5): 18-26.
	SONG K , LIU Q R , WEI S ,et al. Endogenous security architecture of Ethernet switch based on mimic defense[J]. Journal on Communications, 2020,41(5): 18-26.
[13]	吴铤, 胡程楠, 陈庆南 ,等. 基于执行体划分的防御增强型动态异构冗余架构[J]. 通信学报, 2021,42(3): 122-134.
	WU T , HU C N , CHEN Q N ,et al. Defense-enhanced dynamic heterogeneous redundancy architecture based on executor partition[J]. Journal on Communications, 2021,42(3): 122-134.
[14]	朱正彬, 刘勤让, 刘冬培 ,等. 拟态多执行体调度算法研究进展[J]. 通信学报, 2021,42(5): 179-190.
	ZHU Z B , LIU Q R , LIU D P ,et al. Research progress of mimic multi-execution scheduling algorithm[J]. Journal on Communications, 2021,42(5): 179-190.
[15]	杨林, 王永杰, 张俊 . FAWA:一种异构执行体的负反馈动态调度算法[J]. 计算机科学, 2021,48(8): 284-290.
	YANG L , WANG Y J , ZHANG J . FAWA:a negative feedback dynamic scheduling algorithm for heterogeneous executor[J]. Computer Science, 2021,48(8): 284-290.
[16]	武兆琪, 张帆, 郭威 ,等. 一种基于执行体异构度的拟态裁决优化方法[J]. 计算机工程, 2020,46(5): 12-18.
	WU Z Q , ZHANG F , GUO W ,et al. A mimic arbitration optimization method based on heterogeneous degree of executors[J]. Computer Engineering, 2020,46(5): 12-18.
[17]	沈丛麒, 陈双喜, 吴春明 ,等. 基于信誉度与相异度的自适应拟态控制器研究[J]. 通信学报, 2018,39(S2): 173-180.
	SHEN C Q , CHEN S X , WU C M ,et al. Adaptive mimic defensive controller framework based on reputation and dissimilarity[J]. Journal on Communications, 2018,39(S2): 173-180.
[18]	刘勤让, 林森杰, 顾泽宇 . 面向拟态安全防御的异构功能等价体调度算法[J]. 通信学报, 2018,39(7): 188-198.
	LIU Q R , LIN S J , GU Z Y . Heterogeneous redundancies scheduling algorithm for mimic security defense[J]. Journal on Communications, 2018,39(7): 188-198.
[19]	魏帅, 张辉华, 苏野 ,等. 面向拟态防御系统的高阶异构度大数判决算法[J]. 计算机工程, 2021,47(5): 30-35.
	WEI S , ZHANG H H , SU Y ,et al. Majority voting algorithm based on high-order heterogeneity for mimic defense system[J]. Computer Engineering, 2021,47(5): 30-35.
[20]	杨欣欣, 黄少滨 . 高阶异构数据层次联合聚类算法[J]. 计算机研究与发展, 2015,52(1): 200-210.
	YANG X X , HUANG S B . A hierarchical co-clustering algorithm for high-order heterogeneous data[J]. Journal of Computer Research and Development, 2015,52(1): 200-210.
[21]	李超 . 高阶多数据集建模新方法与应用研究[D]. 哈尔滨:哈尔滨工程大学, 2017.
	LI C . Study on novel modeling methods and applications for multiple higher order datasets[D]. Harbin:Harbin Engineering University, 2017.
[22]	黄少滨, 杨欣欣, 申林山 ,等. 高阶异构数据模糊联合聚类算法[J]. 通信学报, 2014,35(6): 15-24.
	HUANG S B , YANG X X , SHEN L S ,et al. Fuzzy co-clustering algorithm for high-order heterogeneous data[J]. Journal on Communications, 2014,35(6): 15-24.
[23]	丁绍虎, 齐宁, 郭义伟 . 基于 M-FlipIt 博弈模型的拟态防御策略评估[J]. 通信学报, 2020,41(7): 186-194.
	DING S H , QI N , GUO Y W . Evaluation of mimic defense strategy based on M-FlipIt game model[J]. Journal on Communications, 2020,41(7): 186-194.
[24]	蔡雨彤, 常晓林, 石禹 ,等. 动态平台技术防御攻击的瞬态效能量化分析[J]. 信息安全学报, 2019,4(4): 59-67.
	CAI Y T , CHANG X L , SHI Y ,et al. Analyzing transient effectiveness of dynamic platform technique in resisting attacks[J]. Journal of Cyber Security, 2019,4(4): 59-67.
[25]	张兴明, 顾泽宇, 魏帅 ,等. 拟态防御马尔可夫博弈模型及防御策略选择[J]. 通信学报, 2018,39(10): 143-154.
	ZHANG X M , GU Z Y , WEI S ,et al. Markov game modeling of mimic defense and defense strategy determination[J]. Journal on Communications, 2018,39(10): 143-154.
[26]	吴正江, 姚琪, 冯四风 ,等. 基于数据库二进制日志的竞赛式仲裁优化方案[J]. 计算机工程, 2021,47(5): 24-29.
	WU Z J , YAO Q , FENG S F ,et al. Optimization scheme of competitive arbitration based on binary database log[J]. Computer Engineering, 2021,47(5): 24-29.
[27]	高振斌, 贾广瑞, 张文建 ,等. 基于异常值的拟态裁决优化方法[J]. 计算机应用研究, 2021,38(7): 2066-2071.
	GAO Z B , JIA G R , ZHANG W J ,et al. Mimic ruling optimization method based on executive outliers[J]. Application Research of Computers, 2021,38(7): 2066-2071.
[28]	CHOI J , GOH K I . Dynamics of consensus formation on multiplex networks:the majority-vote model[C]// APS March Meeting.Washington,D.C. :American Physical Society, 2018: 1-15.

Metrics

Recommended 0

No Suggested Reading articles found!

执行体编号	漏洞编号
1	1,2,3,4,5
2	3,5,7,8,9
3	1,5,9,10,11
4	1,2,7,8,9

调度编号	相似度值
1,2,3	6
1,2,4	7
2,3,4	7
1,3,4	6

符号	定义
?	异构执行体池
N_W	等待池执行体容量
N_R	运行池执行体容量
A_i	异构执行体i，1<i<N_W
P	高阶防御面积矩阵
S	高阶相似度矩阵
H	高阶异构体矩阵
M	执行体调度概率矩阵
D	调度值
Sel	选取执行体集

威胁个数	FAWA	HFAWA	Random	FIFO	H2
20	0.950 8	1.000 0	0.806 4	0.753 8	0.900 7
30	0.774 1	0.835 5	0.649 8	0.670 2	0.735 0
40	0.599 2	0.776 5	0.555 4	0.588 1	0.600 8
50	0.601 4	0.639 7	0.408 5	0.404 2	0.420 7
60	0.432 6	0.566 2	0.417 2	0.395 2	0.299 1
70	0.528 5	0.498 4	0.363 4	0.386 1	0.270 4
80	0.476 9	0.489 2	0.275 7	0.301 8	0.389 5
90	0.442 7	0.401 0	0.234 2	0.249 6	0.311 0
100	0.376 5	0.399 0	0.269 7	0.262 4	0.349 8
110	0.343 0	0.346 9	0.205 4	0.220 9	0.235 6
120	0.294 0	0.306 7	0.225 5	0.196 9	0.141 5
130	0.314 1	0.276 0	0.191 8	0.146 4	0.177 4
140	0.278 7	0.314 9	0.191 5	0.184 1	0.164 1
150	0.260 6	0.268 0	0.176 3	0.152 0	0.186 6
250	0.152 3	0.166 7	0.104 0	0.128 5	0.072 0
500	0.084 4	0.092 7	0.054 7	0.055 0	0.074 3
750	0.058 9	0.062 4	0.031 0	0.043 2	0.033 3
1 000	0.042 1	0.041 9	0.022 0	0.027 8	0.040 8

威胁个数	FAWA	HFAWA	Random	FIFO	H2
20	0.924 9	0.999 9	0.765 2	0.759 9	0.710 2
30	0.777 0	0.870 6	0.573 6	0.623 6	0.430 1
40	0.716 7	0.721 1	0.439 7	0.492 4	0.758 7
50	0.572 8	0.663 6	0.510 2	0.448 4	0.456 3
60	0.516 8	0.563 9	0.407 1	0.388 6	0.421 1
70	0.497 0	0.513 1	0.419 1	0.364 8	0.312 7
80	0.457 8	0.444 0	0.272 1	0.317 8	0.360 5
90	0.443 2	0.407 3	0.321 2	0.286 4	0.277 5
100	0.393 8	0.398 3	0.269 3	0.269 4	0.274 9
110	0.388 9	0.368 7	0.257 6	0.268 8	0.238 4
120	0.369 8	0.377 6	0.238 2	0.225 9	0.210 4
130	0.327 3	0.343 4	0.230 0	0.235 7	0.207 8
140	0.350 8	0.346 0	0.212 3	0.227 9	0.229 4
150	0.350 4	0.335 2	0.201 7	0.206 8	0.210 8
250	0.239 1	0.262 3	0.153 6	0.117 0	0.144 8
500	0.157 4	0.147 5	0.074 1	0.083 9	0.103 5
750	0.116 3	0.121 0	0.067 2	0.065 6	0.079 8
1 000	0.103 1	0.085 2	0.042 4	0.055 6	0.052 0

Executive dynamic scheduling algorithm based on high-order heterogeneity

RichHTML

PDF

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 25

References 28

Related Articles 12

Metrics

Recommended 0

实验方式	装载方式	威胁构造
碰撞实验	部分装载	负反馈
LSA实验	全装载	随机

条目	参数
CPU型号	Intel(R) Core(TM)i5-7300HQ CPU@2.50 GHz
内存大小	8 GB
操作系统	Windows 10
运行语言	Python

威胁个数	FAWA/s	HFAWA/s	Random/s	FIFO/s	H2/s
20	4.991 6	7.872 9	1.686 5	4.616 7	17.165 1
30	5.391 6	8.100 3	1.811 2	4.893 9	17.824 3
40	5.820 4	8.576 1	2.012 6	4.969 7	17.916 1
50	6.039 8	8.892 2	2.319 8	5.171 2	17.951 0
60	6.288 2	9.019 9	2.453 4	5.408 5	18.414 7
70	6.695 1	9.293 1	2.744 7	5.659 9	17.980 9
80	7.223 6	9.586 4	2.962 1	5.894 2	17.858 2
90	7.437 1	9.804 8	3.159 5	6.189 4	18.202 3
100	7.745 3	10.276 5	3.678 2	6.557 5	18.321 0
110	8.124 3	10.505 9	3.798 8	6.661 2	18.705 4
120	8.596 0	11.144 2	3.931 5	6.599 4	19.000 2
130	9.309 1	11.283 8	4.283 5	6.862 6	19.165 8
140	9.093 7	11.765 5	4.255 6	7.167 3	19.285 4
150	9.497 6	12.495 6	4.546 8	7.377 3	19.297 4
250	12.747 9	15.552 4	6.559 5	9.276 2	21.753 8
500	21.969 2	23.834 3	12.948 4	15.232 3	27.765 7
750	29.718 5	31.714 2	18.338 0	20.575 0	33.197 2
1 000	38.137 0	39.749 8	25.672 3	26.013 4	38.853 1

算法	防御能力	运行速度
HFAWA	高	中
FAWA	较高	中
H2	中	较慢
FIFO	较低	较快
Random	较低	快

[1]	Jin ZHANG, Qiang GE, Weihai XU, Yiming JIANG, Hailong MA, Hongtao YU. Design, implementation and formal verification of BGP proxy for mimic router [J]. Journal on Communications, 2023, 44(3): 33-44.
[2]	Dacheng ZHOU, Hongchang CHEN, Guozhen CHENG, Weizhen HE, Ke SHANG, Hongchao HU. Design and implementation of adaptive mimic voting device oriented to persistent connection [J]. Journal on Communications, 2022, 43(6): 71-84.
[3]	Zhengbin ZHU, Qinrang LIU, Dongpei LIU, Chong WANG. Research progress of mimic multi-execution scheduling algorithm [J]. Journal on Communications, 2021, 42(5): 179-190.
[4]	Ting WU, Chengnan HU, Qingnan CHEN, Anbang CHEN, Qiuhua ZHENG. Defense-enhanced dynamic heterogeneous redundancy architecture based on executor partition [J]. Journal on Communications, 2021, 42(3): 122-134.
[5]	Chuanxing PAN, Zheng ZHANG, Bolin MA, Yuan YAO, Xinsheng JI. Method against process control-flow hijacking based on mimic defense [J]. Journal on Communications, 2021, 42(1): 37-47.
[6]	Shaohu DING,Ning QI,Yiwei GUO. Evaluation of mimic defense strategy based on M-FlipIt game model [J]. Journal on Communications, 2020, 41(7): 186-194.
[7]	Qinglei ZHOU,Shaohuan BAN,Yingjie HAN,Feng FENG. Mimic defense authentication method for physical access control [J]. Journal on Communications, 2020, 41(6): 80-87.
[8]	Ke SONE,Qinrang LIU,Shuai WEI,Wenjian ZHANG,Libo TAN. Endogenous security architecture of Ethernet switch based on mimic defense [J]. Journal on Communications, 2020, 41(5): 18-26.
[9]	Liming PU,Shuxin LIU,Ruihao DING,Kai WANG. Heterogeneous executor scheduling algorithm for mimic cloud service [J]. Journal on Communications, 2020, 41(3): 17-24.
[10]	Yuan YAO,Chuanxing PAN,Zheng ZHANG,Gaofei ZHANG. Method of quantitative assessment for diversified software system [J]. Journal on Communications, 2020, 41(3): 120-125.
[11]	Xingming ZHANG,Zeyu GU,Shuai WEI,Jianliang SHEN. Markov game modeling of mimic defense and defense strategy determination [J]. Journal on Communications, 2018, 39(10): 143-154.
[12]	Jin-guang JIANG,Yao-nan WANG. Design and simulation of a tunable frequency OTA -C Chebyshev filter [J]. Journal on Communications, 2006, 27(6): 81-87.

威胁个数	FAWA	HFAWA	Random	FIFO	H2
20	0.044 2	0	0.141 6	0.139 1	0.150 4
30	0.025 7	0	0.058 3	0.044 8	0.132 8
40	0	0	0.013 6	0.012 9	0.074 9
50	0.000 2	0	0.010 2	0.020 3	0
60	0	0	0.007 8	0.014 8	0.016 9
70	0	0	0.001 8	0.005 8	0.028 0
80	0	0	0.001 8	0.001 0	0
90	0	0	0.001 0	0.002 3	0
100	0	0	0.001 3	0.001 3	0
110	0	0	0.001 6	0.001 2	0
120	0	0	0.000 4	0.001 3	0
130	0	0	0.000 6	0.001 1	0
140	0	0	0.000 9	0.000 8	0
150	0	0	0.001 3	0.000 6	0
250	0	0	0.000 8	0.001 7	0
500	0	0	0.000 8	0.001 4	0.003 9
750	0	0	0.000 6	0.002 1	0.002 6
1 000	0	0	0.001 4	0.001 2	0.005 0

威胁个数	FAWA	HFAWA	Random	FIFO	H2
20	0.149 1	0	0.127 3	0.199 2	0.149 9
30	0.107 3	0	0.087 7	0.062 1	0.328 3
40	0	0	0.013 8	0.048 4	0
50	0	0	0.019 3	0.017 0	0
60	0	0	0.008 4	0.010 6	0
70	0	0	0.010 3	0.004 8	0
80	0	0	0.003 2	0.008 5	0
90	0	0	0.004 9	0.001 5	0
100	0	0	0.001 1	0.008 6	0
110	0	0	0.002 8	0.001 4	0
120	0	0	0.000 6	0.003 4	0
130	0	0	0.003 4	0.000 1	0
140	0	0	0.000 3	0.001 8	0
150	0	0	0.002 4	0.000 4	0
250	0	0	0.002 6	0	0
500	0	0	0.003 0	0	0
750	0	0	0.002 0	0	0
1 000	0	0	0.001 6	0	0.006 2