Computer Science ›› 2020, Vol. 47 ›› Issue (1): 321-328.doi: 10.11896/jsjkx.190100027

• Information Security • Previous Articles    

Energy-efficient Password Recovery Method for 7-Zip Document Based on FPGA

CHEN Xiao-jie1,ZHOU Qing-lei1,LI Bin1,2   

  1. (School of Information Engineering,Zhengzhou University,Zhengzhou 450001,China)1;
    (State Key Laboratory of Mathematical Engineering and Advanced Computing,Information Engineering University,Zhengzhou 450001,China)2
  • Received:2019-01-05 Published:2020-01-19
  • About author:CHEN Xiao-jie,born in 1993,postgra-duate,is not member of China ComputerFederation (CCF).His main research interests include information security;ZHOU Qing-lei,born in 1962,Ph.D,professor,Ph.D supervisor,is member of China Computer Federation (CCF).His main research interests include information security,automata theory and computational complexity theory.
  • Supported by:
    This work was supported by the National Key R&D Program of China (2016YFB0800100) and General Program of National Natural Science Foundation of China (61572444).

Abstract: With the wide range of 7-Zip compression software,7-Zip password cracking is very important for information security.Currently,cracking 7-Zip encryption documents mainly uses CPU and GPU platforms,and the potential for a large password space and high computational complexity requires a higher performance computing platform to find the correct password within a limited time.Therefore,by analyzing PMC characteristics of decryption algorithm,this paper adopted reconfigurable FPGA hardware computing platform,uses pipeline technology to realize data splicing and SHA-256 algorithm,used precomputation and CSA method to optimize the key path of SHA-256 algorithm,and used dual-port RAM to store verification data,thus satisfying the computational and storage requirements of the algorithm and realizing high-performance 7-Zip decryption algorithm.The experimental data show that the optimization method in this paper can greatly improve the performance of SHA-256 algorithm,making it throughput reach 110.080Gbps.The decryption algorithm is optimized by various methods,and finally the 10bit password is cracked to10608 per second,226 times that of the CPU,1.4 times that of the GPU,and 8 times that of the GPU, which greatly improves the performance and reduces the demand for high power consumption.

Key words: 7-Zip decryption, Energy-efficient password recovery, Pipeline, Reconfigurable, SHA-256, Dual port RAM

CLC Number: 

  • TP309
[1]CHEN F T,YUAN J L.Enhanced Key Derivation Function of HMAC-SHA-256 Algorithm in LTE Network[C]∥Fourth International Conference on Multimedia Information NETWORKING and Security.IEEE Computer Society,Washingdon,DC,USA,2012:15-18.
[2]ZHAO X J,GUO S Z,WANG T,et al.Improved Cache trace driven attack on AES and CLEFIA[J].Journal on Communications,2011,32(8):101-110.
[3]WANG D,JIAN G P,HUANG X Y,et al.Zipf’s Law in Passwords[J].IEEE Transactions on Information Forensics and Security,2017,12(11):2776-2791.
[4]MA J,YANG W N,LUO M,et al.A Study of Probabilistic Password Models[C]∥IEEE Symposium on Security and Privacy.USA:IEEE,2014:689-704.
[5]WANG D,ZHANG Z J,WANG P,et al.Targeted Online Password Guessing:An Underestimated Threat[C]∥Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security.New York:USA,ACM,2016:1242-1254.
[6]WANG P,WANG D,HUANG X Y.Advances in password security[J].Journal of Computer Research and Development,2016,53(10):2173-2188.
[7]KOZIEL B,AZARDERAKHSH R,KERMANI M M,et al. Post-Quantum Cryptography on FPGA Based on Isogenies on Elliptic Curves[J].IEEE Transactions on Circuits and Systems I:Regular Papers,2017,64(1):86-99.
[8]ZHANG C,LI P,SUN G,et al.Optimizing FPGA-based Acce- lerator Design for Deep Convolutional Neural Networks[C]∥Proceesing of the 2015 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays.New York:ACM,2015:161-170.
[9]DABHADE S D,RATHNA G N,CHAUDHURY K N.A Reconfigurable and Scalable FPGA Architecture for Bilateral Filtering[J].IEEE Transactions on Industrial Electronics,2018,65:1459-1469.
[10]LIU P,LI S,DING Q.An Energy-Efficient Accelerator Based on Hybrid CPU-FPGA Devices for Password Recovery[J].IEEE Transactions on Computers,2019,68(2):170-181.
[11]ZHOU B,ZHANG Y Q,AN X J,et al.Optimization of RAR password brute-force cracking based on OpenCL [C]∥High-Performance Computing China 2014.2014:871-874.
[12]AN X J,JIA H P,ZHANG Y Q.Optimized Password Recovery for Encrypted RAR on GPUs[C]∥IEEE InternationalConfe-rence on High PERFORMANCE Computing and Communications.IEEE Computer Society,2015:591-598.
[13]LIU Z L,DONG X,LI D F.On the Hardware Implementations of the SHA-2(256,384,512) Hash Function[J].Microelectro-nics & Computer,2012,29(12):51-54.
[14]ALGREDO-BADILLO I,FEREGRINO-URIBE C,CUMPLIDO R,et al.FPGA-based implementation alternatives for the inner loop of the Secure Hash Algorithm SHA-256[J].Microprocessors & Microsystems,2013,37(6/7):750-757.
[15]JULIATO M,GEBOTYS C.A Quantitative Analysis of a Novel SEU-Resistant SHA-2 and HMAC Architecture for Space Missions Security[J].IEEE Transactions on Aerospace &Electronic Systems,2013,49(3):1536-1554.
[16]MICHAIL H E,ATHANASIOU G S,KELEFOURAS V,et al.On the exploitation of a high-throughput SHA-256 FPGA design for HMAC[J].Acm Transactions on Reconfigurable Technology & Systems,2012,5(1):1-28.
[17]TAN J,ZHOU Q L,SI X M,et al.Implementation and improvement of full-pipeline MD5 algorithm based on mimic compiter[J].Journal of Chinese Computer Systems,2017,38(6):1216-1220.
[18]LEI Y W,DOU Y,GUO S.High precision Scientific Computation Accumulator on FPGA[J].Chinese Journal of Computers,2012,35(1):112-122.
[19]WU Q,WANG X W,HUANG M.OpenFlow Switch Packets Pipeline Processing Mechanism Based on SDN[J].Computer Science,2018,45(10):295-299.
[20]LI Y,ZHANG D X,YU F.Technology Mapping of FPGA On-Chip-RAM in RTL Synthesis[J].Acta Electronica Sinica,2016,44(11):2660-2667.
[21]YU X F,LIU X B,HU B L,et al.Design of FIFO in High Speed Data Storage System Based on FPGA[J].Nuclear Electronics & Detection Technology,2010,30(1):59-62.
[22]LI B,ZHOU Q L,SI X M.Mimic computing for password reco- very[J].Future Generation Computer Systems,2018,84:58-77.
[23]ZHANG K,GUO F,ZHENG W et al.Design of a Pipeline-Coupled Instruction Loop Cache for Many-Core Processors[J].Journal of Computer Research and Development,2017,54(4):813-820.
[24]LIN B,LI S S,LIAO X K,et al.Seadown:SLA-Aware Size-Sca- ling Power Management in Heterogeneous MapReduce Cluster[J].Chinese Journal of Camputers,2013,36(5):977-987.
[1] WU Qi, WANG Xing-wei, HUANG Min. OpenFlow Switch Packets Pipeline Processing Mechanism Based on SDN [J]. Computer Science, 2018, 45(10): 295-299.
[2] HE Lu-bei, LI Jun-nan, YANG Xiang-rui and SUN Zhi-gang. RESSP:An FPGA-based REconfigurable SDN Switching Architecture [J]. Computer Science, 2018, 45(1): 205-210.
[3] MA Ding, ZHUANG Lei and LAN Ju-long. Research on End-to-End Model of Reconfigurable Information Communication Basal Network [J]. Computer Science, 2017, 44(6): 114-120.
[4] ZHU Shu-qin, WANG Wen-hong and SUN Zhong-gui. Chosen Plaintext Attack on Image Encryption Algorithm Based on Bit Scrambling and Hyperchaos [J]. Computer Science, 2017, 44(11): 273-278.
[5] DU Zhi-hui, LIN Zhang-xi, GU Yan-qi, Eric O.LEBIGOT and GUO Xiang-yu. GPU Accelerated cWB Pipeline for Gravitational Waves Discovery [J]. Computer Science, 2017, 44(10): 26-32.
[6] ZHU Shu-qin, LI Jun-qing and GE Guang-ying. New Image Encryption Algorithm Based on New Four-dimensional Discrete-time Chaotic Map [J]. Computer Science, 2017, 44(1): 188-193.
[7] WANG Jing, WANG Bin-qiang and SHEN Juan. Measurement Component Transfer Model-based Conformance Testing Approach of Reconfigurable Measurement Component [J]. Computer Science, 2015, 42(9): 165-170.
[8] YIN Meng-jia, XU Xian-bin, XIONG Zeng-gang and ZHANG Tao. Quantitative Performance Analysis Model of Matrix Multiplication Based on GPU [J]. Computer Science, 2015, 42(12): 13-17, 22.
[9] YANG Jin, PANG Jian-min, WANG Jun-chao, YU Jin-tao and LIU Rui. High-productivity Model Based on Proactive Cognition and Decision [J]. Computer Science, 2015, 42(11): 68-72.
[10] FANG Juan and CHEN Xin. Research of Reconfigurable Cache Method for Power Calculation in CMP [J]. Computer Science, 2014, 41(Z6): 114-117.
[11] LI Ling,DU Xue-hui and BAO Yi-bao. Research on Optimization Technology of Reconfigurable Security Protocols Based on Reconfigurable Component [J]. Computer Science, 2014, 41(Z11): 245-249.
[12] CHEN Jin-hui and DONG Biao. Reconfigurable Management for Large Scale Dynamic Publish/ Subscribe Systems [J]. Computer Science, 2014, 41(3): 137-140.
[13] YU Jing,ZHANG Jian-hui and WANG Bin-qiang. Service Overlay Networks Construction Algorithm Based on Node Potential Oriented Multi-nexthop Routing Protocol [J]. Computer Science, 2014, 41(1): 168-171.
[14] WANG Zhuo-wei,CHENG Liang-lun and ZHAO Wu-qing. Parallel Computation Performance Analysis Model Based on GPU [J]. Computer Science, 2014, 41(1): 31-38.
[15] SHEN Lai-xin,ZENG Guo-sun and WANG Wei. Reconfigurable Architecture Model Based on Layered Hypergraph [J]. Computer Science, 2013, 40(4): 26-30.
Full text



[1] SHI Chao, XIE Zai-peng, LIU Han and LV Xin. Optimization of Container Deployment Strategy Based on Stable Matching[J]. Computer Science, 2018, 45(4): 131 -136 .
[2] PANG Bo, JIN Qian-kun, HENIGULI·Wu Mai Er and QI Xing-bin. Routing Scheme Based on Network Slicing and ILP Model in SDN[J]. Computer Science, 2018, 45(4): 143 -147 .
[3] ZHANG Jing and ZHU Guo-bin. Hot Topic Discovery Research of Stack Overflow Programming Website Based on CBOW-LDA Topic Model[J]. Computer Science, 2018, 45(4): 208 -214 .
[4] WENG Li-guo, KONG Wei-bin, XIA Min and CHOU Xue-fei. Satellite Imagery Cloud Fraction Based on Deep Extreme Learning Machine[J]. Computer Science, 2018, 45(4): 227 -232 .
[5] XIANG Ying-zhuo, TAN Ju-xian, HAN Jie-si, SHI Hao. Survey of Graph Matching Algorithms[J]. Computer Science, 2018, 45(6): 27 -31,45 .
[6] HU Qing-cheng, ZHANG Yong, XING Chun-xiao. K-clique Heuristic Algorithm for Influence Maximization in Social Network[J]. Computer Science, 2018, 45(6): 32 -35 .
[7] LI Xiao, XIE Hui and LI Li-jie. Research on Sentence Semantic Similarity Calculation Based on Word2vec[J]. Computer Science, 2017, 44(9): 256 -260 .
[8] QIN Ke-yun, JING Si-hui. Attribute Reduction of Decision Systems Based on Indiscernibility Relation and Discernibility Relation[J]. Computer Science, 2018, 45(6): 247 -250 .
[9] CHEN Rong, LI Peng, HUANG Yong. Moving Shadow Removal Algorithm Based on Multi-feature Fusion[J]. Computer Science, 2018, 45(6): 291 -295 .
[10] WANG Hao-liang and GAO Jian-hua. Segmentation and Application of Multilevel Morphology Model in GUI Testing[J]. Computer Science, 2017, 44(9): 190 -194, 199 .