ORIGINAL_ARTICLE
Impossible Differential Cryptanalysis of Reduced-Round Midori64 Block Cipher (Extended Version)
Impossible differential attack is a well-known mean to examine robustness of block ciphers. Using impossible differential cryptanalysis, we analyze security of a family of lightweight block ciphers, named Midori, that are designed considering low energy consumption. Midori state size can be either 64 bits for Midori64 or 128 bits for Midori128; however, both versions have key size equal to 128 bits. In this paper, we mainly study security of Midori64. To this end, we use various techniques such as early-abort, memory reallocation, miss-in-the-middle and turning to account the inadequate key schedule algorithm of Midori64. We first show two new 7round impossible differential characteristics which are, to the best of our knowledge, the longest impossible differential characteristics found for Midori64. Based on the new characteristics, we mount three impossible differential attacks for 10, 11, and 12 rounds on Midori64 with 2 87.7 , 2 90.63 , and 2 90.51 time complexity, respectively, to retrieve the master-key.
https://www.isecure-journal.com/article_57307_b1cced248995ff3b98bf42a1afe95acb.pdf
2018-01-01
3
13
10.22042/isecure.2018.110672.399
Midori
block cipher
impossible differential attack
Cryptanalysis
A.
Rezaei Shahmirzdi
rezaeishahmirzadi@ee.sharif.edu
1
Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
LEAD_AUTHOR
A.
Azimi
arashazimi@ee.sharif.edu
2
Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
AUTHOR
M.
Salmasizadeh
salmasi@sharif.edu
3
Electronics Research Institute, Sharif University of Technology, Tehran, Iran
AUTHOR
J.
Mohajeri
mohajer@sharif.edu
4
Electronics Research Institute, Sharif University of Technology, Tehran, Iran
AUTHOR
M. R.
Aref
isecure@sharif.ir
5
3Information Systems and Security Lab (ISSL), Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
AUTHOR
[1] Aein Rezaei Shahmirzadi, Seyyed Arash Azimi, Mahmoud Salmasizadeh, Javad Mohajeri, and Mohammad Reza Aref. Impossible differential cryptanalysis of reduced-round midori64 block cipher. In Information Security and Cryptology
1
(ISCISC), 2017 14th International ISC Conference on. IEEE, 2017.
2
[2] Andrey Bogdanov, Lars R Knudsen, Gregor Leander, Christof Paar, Axel Poschmann, Matthew JB Robshaw, Yannick Seurin, and Charlotte Vikkelsoe. Present: An ultralightweight block cipher. In International Workshop on Cryptographic Hardware and Embedded Systems, pages 450–466. Springer, 2007.
3
[3] Lars Knudsen, Gregor Leander, Axel Poschmann, and Matthew JB Robshaw. Printcipher: a block cipher for ic-printing. In International Workshop on Cryptographic Hardware and Embedded Systems, pages 16–32. Springer, 2010.
4
[4] Tomoyasu Suzaki, Kazuhiko Minematsu, Sumio Morioka, and Eita Kobayashi. Twine: A lightweight, versatile block cipher. In ECRYPT Workshop on Lightweight Cryptography, volume 2011, 2011.
5
[5] Julia Borghoff, Anne Canteaut, Tim Güneysu, Elif Bilge Kavun, Miroslav Knezevic, Lars R Knudsen, Gregor Leander, Ventzislav Nikov, Christof Paar, Christian Rechberger, et al. Prince–a low-latency block cipher for pervasive computing applications. In International Conference on the Theory and Application of Cryptology and Information Security, pages 208–225. Springer, 2012.
6
[6] WenlingWu and Lei Zhang. Lblock: a lightweight block cipher. In International Conference on Applied Cryptography and Network Security, pages 327–344. Springer, 2011.
7
[7] Taizo Shirai, Kyoji Shibutani, Toru Akishita, Shiho Moriai, and Tetsu Iwata. The 128-bit blockcipher clefia. In FSE, volume 4593, pages 181–195. Springer, 2007.
8
[8] Christophe De Canniere, Orr Dunkelman, and Miroslav Kneževic. Katan and ktantanâATa family of small and efficient hardware-oriented block ciphers. In International Workshop on Cryptographic Hardware and Embedded Systems, pages 272–288. Springer, 2009.
9
[9] Subhadeep Banik, Andrey Bogdanov, Takanori Isobe, Kyoji Shibutani, Harunaga Hiwatari, Toru Akishita, and Francesco Regazzoni. Midori: a block cipher for low energy. In International Conference on the Theory and Application of Cryptology and Information Security, pages 411–436. Springer, 2015.
10
[10] Jian Guo, Jérémy Jean, Ivica Nikolic, Kexin Qiao, Yu Sasaki, and Siang Meng Sim. Invariant subspace attack against full midori64. IACR Cryptology ePrint Archive, 2015:1189, 2015.
11
[11] Yosuke Todo, Gregor Leander, and Yu Sasaki. Nonlinear invariant attack: Practical attack on full scream, i scream, and midori 64. In Advances in Cryptology–ASIACRYPT 2016: 22nd International Conference on the Theory and Application
12
of Cryptology and Information Security, Hanoi, Vietnam, December 4-8, 2016, Proceedings, PartII 22, pages 3–33. Springer, 2016.
13
[12] Xiaoyang Dong and Yanzhao Shen. Cryptanalysis of reduced-round midori64 block cipher. Technical report, Cryptology ePrint Archive, Report 2016/676, 2016.
14
[13] David Gérault and Pascal Lafourcade. Relatedkey cryptanalysis of midori. In Progress in Cryptology–INDOCRYPT 2016: 17th International Conference on Cryptology in India, Kolkata, India, December 11-14, 2016, Proceedings 17, pages 287–304. Springer, 2016.
15
[14] Zhan Chen and Xiaoyun Wang. Impossible differential cryptanalysis of midori. IACR Cryptology ePrint Archive, 2016:535, 2016.
16
[15] Li Lin and Wenling Wu. Meet-in-the-middle attacks on reduced-round midori64. IACR Transactions on Symmetric Cryptology, 2017(1):215–239, 2017.
17
[16] Seyyed Arash Azimi, Zahra Ahmadian, Javad Mohajeri, and Mohammad Reza Aref. Impossible differential cryptanalysis of piccolo lightweight block cipher. In Information Security and Cryptology(ISCISC), 2014 11th International ISC Conference on, pages 89–94. IEEE, 2014.
18
[17] Christina Boura, María Naya-Plasencia, and Valentin Suder. Scrutinizing and improving impossible differential attacks: Applications to clefia, camellia, lblock and simon. ASIACRYPT(1), 8873:179–199, 2014.
19
[18] Masroor Hajari, Seyyed Arash Azimi, Poorya Aghdaie, Mahmoud Salmasizadeh, and Mohammad Reza Aref. Impossible differential cryptanalysis of reduced-round tea and xtea. In Information Security and Cryptology (ISCISC), 2015 12th International Iranian Society of Cryptology Conference on, pages 58–63. IEEE, 2015.
20
[19] Hamid Mala, Mohammad Dakhilalian, and Mohsen Shakiba. Impossible differential attacks on 13-round clefia-128. Journal of Computer Science and Technology, 26(4):744–750, 2011.
21
[20] Seyyed Arash Azimi, Siavash Ahmadi, Zahra Ahmadian, Javad Mohajeri, and Mohammad Reza Aref. Improved impossible differential and biclique cryptanalysis of hight. International Journal of Communication Systems, 31(1), 2018.
22
[21] Eli Biham and Adi Shamir. Differential cryptanalysis of des-like cryptosystems. In Advances
23
in Cryptology-CRYPTO, volume 90, pages 2–21. Springer, 1991.
24
[22] Lars R Knudsen. Deal a 128-bit cipher. Technical report, Technical Report, Department of Informatics, University of Bergen, Norway, 1998.
25
[23] Eli Biham, Alex Biryukov, and Adi Shamir. Miss in the middle attacks on idea and khufu. In FSE, volume 1636, pages 124–138. Springer, 1999.
26
[24] Eli Biham, Alex Biryukov, and Adi Shamir. Cryptanalysis of skipjack reduced to 31 rounds using impossible differentials. In International Conference on the Theory and Applications of Cryptographic Techniques, pages 12–23. Springer,1999.
27
[25] Joan Daemen and Vincent Rijmen. The design of Rijndael: AES-the advanced encryption standard. Springer Science & Business Media, 2013.
28
[26] Chae Hoon Lim. Crypton: A new 128-bit block cipher. NIsT AEs Proposal, 1998.
29
[27] Kazumaro Aoki, Tetsuya Ichikawa, Masayuki Kanda, Mitsuru Matsui, Shiho Moriai, Junko Nakajima, and Toshio Tokita. Camellia: A 128-bit block cipher suitable for multiple platformsdesign and analysis. In Selected Areas in Cryptography,
30
volume 2012, pages 39–56. Springer,2000.
31
[28] Daniel Dinu, Léo Perrin, Aleksei Udovenko, Vesselin Velichkov, Johann Großschädl, and Alex Biryukov. Design strategies for arx with provable bounds: Sparx and lax. In Advances in Cryptology–ASIACRYPT 2016: 22nd International
32
Conference on the Theory and Application of Cryptology and Information Security, Hanoi, Vietnam, December 4-8, 2016, Proceedings, PartI 22, pages 484–513. Springer, 2016.
33
[29] Jiqiang Lu, Orr Dunkelman, Nathan Keller, and Jongsung Kim. New impossible differential attacks on aes. In Indocrypt, volume 8, pages 279–293. Springer, 2008.
34
[30] Jung Hee Cheon, MunJu Kim, Kwangjo Kim,Lee Jung-Yeun, and SungWoo Kang. Improved impossible differential cryptanalysis of rijndael and crypton. In International Conference on Information Security and Cryptology, pages 39–49. Springer, 2001.
35
[31] Céline Blondeau. Impossible differential attack on 13-round camellia-192. Information Processing Letters, 115(9):660–666, 2015.
36
[32] Ahmed Abdelkhalek, Mohamed Tolba, and Amr M Youssef. Impossible differential attack on reduced round sparx-64/128. In AFRICACRYPT, pages 135–146, 2017.
37
[33] Yu Sasaki and Yosuke Todo. New impossible differential search tool from design and cryptanalysis aspects. In Annual International Conference on the Theory and Applications of Cryptographic Techniques, pages 185–215. Springer, 2017.
38
[34] Charles Bouillaguet, Orr Dunkelman, Pierre-Alain Fouque, and Gaëtan Leurent. New insights on impossible differential cryptanalysis. In Selected Areas in Cryptography, volume 7118, pages 243–259. Springer, 2011.
39
[35] Jongsung Kim, Seokhie Hong, and Jongin Lim. Impossible differential cryptanalysis using matrix method. Discrete Mathematics, 310(5):988–1002, 2010.
40
[36] Jongsung Kim, Seokhie Hong, Jaechul Sung, Sangjin Lee, Jongin Lim, and Soohak Sung. Impossible differential cryptanalysis for block cipher structures. In International Conference on Cryptology in India, pages 82–96. Springer, 2003.
41
[37] Jiqiang Lu, Jongsung Kim, Nathan Keller, and Orr Dunkelman. Improving the efficiency of impossible differential cryptanalysis of reduced camellia and misty1. In CT-RSA, volume 4964, pages 370–386. Springer, 2008.
42
ORIGINAL_ARTICLE
An Incentive-Aware Lightweight Secure Data Sharing Scheme for D2D Communication in 5G Cellular Networks
Due to the explosion of smart devices, data traffic over cellular networks has seen an exponential rise in recent years. This increase in mobile data traffic has caused an immediate need for offloading traffic from operators. Device-to-Device(D2D) communication is a promising solution to boost the capacity of cellular networks and alleviate the heavy burden on backhaul links. However, direct wireless connections between devices in D2D communication are vulnerable to certain security threats. In this paper, we propose an incentive-aware lightweight secure data sharing scheme for D2D communication. We have considered the major security challenges of the data sharing scheme, including data confidentiality, integrity, detecting message modification, and preventing the propagation of malformed data. We have also applied an incentive mechanism to motivate users involvement in the process of data sharing. Actually, D2D communication is highly dependent on user participation in sharing content, so, we apply the concept of virtual check to motivate users(named proxy users)to help the requesting user(client) in the process of obtaining the data. Unlike the previous studies, our proposed protocol is an stateless protocol and does not depend on the users contextual information. Therefore, it can be used at anytime and from anywhere. The security analysis proves that the proposed protocol resists the security attacks and meets the security requirements. The performance evaluation shows that the proposed protocol outperforms the previous works in terms of communication and computation cost. Thus, the proposed protocol is indeed an efficient and practical solution for secure data sharing in D2D communication.
https://www.isecure-journal.com/article_57447_b0811bf95521e02c8421310095dce002.pdf
2018-01-01
15
27
10.22042/isecure.2018.111195.401
D2D communications
traffic offloading
Security
lightweight
data sharing
incentive
A.
Mohseni-Ejiyeh
mohseniatefeh@ymail.com
1
Department of Information Technology Engineering, Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran
AUTHOR
M.
Ashouri-Talouki
m.ashouri@eng.ui.ac.ir
2
Department of Information Technology Engineering, Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran
LEAD_AUTHOR
M.
Mahdavi
m.mahdavi@eng.ui.ac.ir
3
Department of Information Technology Engineering, Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran
AUTHOR
[1] Cisco,Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update , 2015-2016,âAI Cisco, USA, Feb 2016.
1
[2] Andrews et al., “What will 5G be?.” IEEE Journal on selected areas in communications 32.6 (2014):1065-1082.
2
[3] Mohseni-Ejiyeh, Atefeh, and Maedeh Ashouri-Talouki. “SeVR+: Secure and privacy-aware cloudassisted video reporting service for 5G vehicular networks.” Electrical Engineering (ICEE), 2017 Iranian Conference on. IEEE, 2017.
3
[4] Aijaz, Adnan et al., A survey on mobile data offloading:technical and business perspectives,IEEE Wireless Communications, Vol 20, pp 104-112,2013.
4
[5] Andreev, Sergey, et al., Cellular traffic offloading onto network-assisted Device-to-Device connections, IEEE Communications Magazine,Vol 52,pp 20-31,2014.
5
[6] Asadi, Arash, et al., A survey on Device-to-Device communication in cellular networks, IEEE Communications
6
Surveys and Tutorials, Vol 16, pp1801-1819,2014.
7
[7] Wang, Mingjun, and Zheng Yan, A survey on security in D2D communications, Mobile Networks and Applications,1-14,2016.
8
[8] Naslcheraghi, Mansour, et al., FD Device-to-Device communication for wireless video distribution,
9
IET Communications, Vol 11, pp 1074-1081,2017.
10
[9] Golrezaei, Negin, et al. "Femtocaching and Deviceto-Device collaboration: A new architecture for wireless video distribution." IEEE Communications Magazine, Vol 51, pp 142-149, 2013.
11
[10] Ning, Ting, et al. "Self-interest-driven incentives for ad dissemination in autonomous mobile social networks." INFOCOM, 2013 Proceedings IEEE.IEEE, 2013.
12
[11] 3GPP, TR 33.401, v.14.2.0, Security Architecture,Release 14, 2017
13
[12] 3GPP, TS 33.105 version 14.0.0, Cryptographic Algorithm Requirements, Release 14, 2017
14
[13] Hossain, Ekram, et al., Evolution toward 5G multi-tier cellular wireless networks: An interference management perspective, IEEE Wireless Communications, Vol 21, pp 118-127,2014.
15
[14] Choi, Kae Won, and Zhu Han, Device-to-Device discovery for proximity-based service in LTEadvanced system, IEEE Journal on Selected Areas in Communications, Vol 33, pp 55-66, 2015
16
[15] Wang, Mingjun, and Zheng Yan. A survey on security in D2D communications, Mobile Networks and Applications,Vol 22, pp 195-208, 2017.
17
[16] Tehrani, Mohsen Nader, et al., Device-to-Device communication in 5G cellular networks: challenges,solutions, and future directions, IEEE Communications Magazine, Vol 52, pp 86-92,2014.
18
[17] Zhang, Aiqing, et al., Light-weight and robust security-aware d2d-assist data transmission protocol for mobile-health systems, IEEE Transactions on Information Forensics and Security, Vol 12, pp662-675, 2017.
19
[18] Li, Feng, Jie Wu, and Anand Srinivasan. Thwarting blackhole attacks in disruption-tolerant networks using encounter tickets, INFOCOM 2009,IEEE. IEEE, 2009.
20
[19] Schmittner, Milan, et al., SEMUD: Secure Multihop Device-to-Device Communication for 5G Public Safety Networks, IFIP, 2017.
21
[20] Zhang, Aiqing, et al., SeDS: Secure data sharing strategy for D2D communication in LTEAdvanced networks, IEEE Transactions on Vehicular Technology,Vol 65, pp 2659-2672, 2016.
22
[21] Mohseni-Ejiyeh, Atefeh, Maedeh Ashouri-Talouki, and Mojtaba Mahdavi. "A Lightweight and Secure Data Sharing Protocol for D2D Communication." Information Security and Cryptology (ISCISC), 14th International Iranian Society of Cryptology Conference on. IEEE, 2017.
23
[22] Zhang, Yanru, et al. “Contract-based incentive mechanisms for Device-to-Device communications in cellular networks.” IEEE Journal on Selected Areas in Communications, Vol 33, pp 2144-2155,2015.
24
[23] Wang, Yan, Mooi-Choo Chuah, and Yingying Chen. “Incentive based data sharing in delay tolerant mobile networks.” IEEE Transactions on wireless communications, Vol 13, pp 370-381, 2014.
25
[24] Zhao, Yiming, Wei Song, and Zhu Han. “Socialaware data dissemination via Device-to-Device communications: Fusing social and mobile networks with incentive constraints.” IEEE Transactions on Services Computing (2016).
26
[25] Wang, Mingjun,et al., UAKA-D2D: Universal Authentication and Key Agreement Protocol in D2D Communications, Mobile Networks and Applications,pp 1-16, 2017
27
[26] Alam, Muhammad, et al. Secure Device-to-Device communication in LTE-A, IEEE Communications Magazine, Vol 52, pp 66-73, 2014.
28
[27] Yang, Mi Jeong, et al., Solving the data overload:Device-to-Device bearer control architecture for cellular data offloading, IEEE Vehicular Technology Magazine, Vol 8, pp 31-39, 2013.
29
[28] Ghosh, Amitava, et al. “LTE-advanced: nextgeneration wireless broadband technology.” IEEE wireless communications, Vol 17, 2010.
30
[29] Han, Chan-Kyu, and Hyoung-Kee Choi., Security analysis of handover key management in 4G LTE/SAE networks, IEEE Transactions on Mobile Computing, Vol 13,2014
31
[30] Lai, Chengzhe, et al. “SE-AKA: A secure and efficient group authentication and key agreement protocol for LTE networks.” Computer Networks,Vol 57, pp 3492-3510, 2013.
32
[31] Alezabi, Kamal Ali, et al. "An efficient authentication and key agreement protocol for 4G (LTE) networks." Region 10 Symposium, 2014 IEEE.IEEE, 2014.
33
[32] Soran Sabah Hussein; Lightweight Security Solutions for LTE/LTE-A Networks; PHD thesis,Paris-SUD University, 2014
34
[33] Boneh, Dan, Ben Lynn, and Hovav Shacham."Short signatures from the Weil pairing." Advances in CryptologyâATASIACRYPT 2001(2001): 514-532.
35
[34] Scott, Michael. "Computing the Tate pairing."Topics in CryptologyâASCT-RSA 2005 (2005):293-304.
36
[35] Chatterjee et al., An Enhanced Access Control Scheme in Wireless Sensor Networks, Adhoc and Sensor Wireless Networks, Vol 21, 2014.
37
[36] Hsu, Ruei-Hau, et al. GRAAD: Group Anonymous and Accountable D2D Communication in Mobile Networks, arXiv preprint arXiv:1703.04262, 2017.
38
[37] Scott, Mike. Efficient implementation of cryptographic pairings, Online].http://www. pairing-conference. org/
39
2007/invited/Scott slide. pdf. 2007
40
[38] De Meulenaer, Giacomo, et al. "On the energy cost of communication and cryptography in wireless sensor networks." Networking and Communications,2008. WIMOB’08. IEEE International Conference on Wireless and Mobile Computing,
41
IEEE, 2008.
42
[39] Wu, Dan, et al. The role of mobility for D2D communications in LTE-Advanced networks: energy vs. bandwidth efficiency, IEEE Wireless Communications,Vol 21, (2014): 66-71.
43
[40] Orsino, Antonino, et al. "Direct Connection on the Move: Characterization of User Mobility in Cellular-Assisted D2D Systems." IEEE Vehicular Technology Magazine, Vol 11, pp 38-48, 2016.
44
[41] Wang, Rui, et al. "Mobility-aware caching in D2D networks." IEEE Transactions on Wireless Communications, Vol 16, pp 5001-5015 ,2017.
45
ORIGINAL_ARTICLE
Classification of encrypted traffic for applications based on statistical features
Traffic classification plays an important role in many aspects of network management such as identifying type of the transferred data, detection of malware applications, applying policies to restrict network accesses and so on. Basic methods in this field were using some obvious traffic features like port number and protocol type to classify the traffic type. However, recent changes in applications make these features imperfect for such tasks. As a remedy, network traffic classification using machine learning techniques is now evolving. In this article, a new semi-supervised learning is proposed which utilizes clustering algorithms and label propagation techniques. The clustering part is based on graph theory and minimum spanning tree (MST) algorithm. In the next level, some pivot data instances are selected for the expert to vote for their classes, and the identified class labels will be used for similar data instances with no labels. In the last part, the decision tree algorithm is used to construct the classification model. The results show that the proposed method has a precise and accurate performance in classification of encrypted traffic for the network applications. It also provides desirable results for plain un-encrypted traffic classification, especially for unbalanced streams of data.
https://www.isecure-journal.com/article_57480_1158922458543d3c86ca7b2395d7b6bd.pdf
2018-01-01
29
43
10.22042/isecure.2018.95316.390
: Traffic classification
Encrypted traffic
Network management
Traffic analysis
A.
fanian
a.fanian@cc.iut.ac.ir
1
Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran
LEAD_AUTHOR
E.
Mahdavi
ehsan.mahdavi@ec.iut.ac.ir
2
Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran
AUTHOR
H.
Hassannejad
h.hassannejad@ec.iut.ac.ir
3
Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran
AUTHOR
[1] A. Madhukar and C. Williamson, “A longitudinal study of P2P traffic classification,” in 14th IEEE International Symposium on Modeling, Analysis,and Simulation of Computer and Telecommunication Systems, 2006.
1
[2] A. Callado and et al., “A survey on internet traffic identification,” Communications Surveys & Tutorials IEEE, vol. 11, pp. 37-52, 2009.
2
[3] T. Nguyen and G. Armitage, “A survey of techniques for internet traffic classification using machine learning,” Communications Surveys & Tutorials,IEEE, vol. 10, pp. 56-76, 2008.
3
[4] A. Dainotti, A. Pescape and K. C. Claffy, “Issues and future directions in traffic classification,” IEEE Network, vol. 26, no. 1, pp. 35-40, 2012.
4
[5] A. W. Moore and D. Zuev, “Internet Traffic Classification Using Bayesian Analysis Techniques,”
5
SIGMETRICS Perform. Eval. Rev., vol. 33, no.1, pp. 50-60, 2005.
6
[6] R. Alshammari and A. N. Zincir-Heywood, “Can encrypted traffic be identified without port numbers,
7
IP addresses and payload inspection?,”Computer networks, vol. 55, pp. 1326-1350, 2011.
8
[7] C. Zigang, C. Shoufeng, X. Gang and G. Li,“Progress in Study of Encrypted Traffic Classification,”
9
in Trustworthy Computing and Services:International Conference, Beijing, 2013.
10
[8] Z. Meng, H. Zhang, B. Zhang and G. Lu, “Encrypted Traffic Classification Based on an Improved
11
Clustering Algorithm,” in Trustworthy Computing and Services: International Conference,Beijing, 2012.
12
[9] J. Erman, A. Mahanti, M. Arlitt and L. Cohen,“Offline/realtime traffic classification using semisupervised
13
learning,” Performance Evaluation,vol. 64, no. 9-12, p. 1194âAS1213, 2007.
14
[10] “SSH,” [Online]. Available: http://www.rfcarchive.org/getrfc.php?rfc=4251.
15
[11] C. Chao, J. Zhang, Y. Xiang, W. Zhou and Y.Xiang, “Internet traffic classification by aggregating
16
correlated naive bayes predictions,” IEEE Transactions on Information Forensics and Security,vol. 8, no. 1, pp. 5-15, 2013.
17
[12] N. Williams, S. Zander and G. Armitage, “A Preliminary Performance Comparison of Five Machine Learning Algorithms for Practical IP Traffic Flow Classification,” SIGCOMM Comput.Commun. Rev., vol. 36, no. 5, pp. 5-16, 2006.
18
[13] H. Kim, K. Claffy, M. Fomenkov, D. Barman, M.Faloutsos and K. Lee, “Internet Traffic Classification
19
Demystified: Myths, Caveats, and the Best Practices,” in CoNEXT ’08, New York, 2008.
20
[14] M. Lotfollahi, R. S. Hossein Zade, M. Jafari Siavoshani and M. Saberian, “Deep Packet: A Novel Approach For Encrypted Traffic Classification Using Deep Learning,” eprint arXiv, vol.1709.02656, no. 2, 2017.
21
[15] S. Bagui, X. Fang, K. Ezhil, S. C. Bagui and J.Sheehan, “Comparison of machine-learning algorithms
22
for classification of VPN network using time-related features,” Journal of Cyber Security Technology, vol. 1, no. 2, pp. 108-126, 2017.
23
[16] A. McGregor, M. Hall, P. Lorier and J. Brunskill,“Flow Clustering Using Machine Learning Techniques,” in Passive and Active Network Measurement: 5th International Workshop, Berlin,Heidelberg, Springer Berlin Heidelberg, 2004, pp.205-214.
24
[17] L. Bernaille, R. Teixeira and K. Salamatian, “Early Application Identification,” in Proceedings of the 2006 ACM CoNEXT Conference, New York, NY, USA, 2006.
25
[18] Z. Jun, X. Yang, Z. Wanlei and W. Yu, “Unsupervised traffic classification using flow statistical properties and IP packet payload,” Journal of Computer and System Sciences, vol. 79, no. 5,pp. 573-585, 2013.
26
[19] A. Shrivastav and A. Tiwari, “Network traffic classification using semi-supervised approach,” in Machine Learning and Computing (ICMLC),Bangalore, 2010.
27
[20] Y. Wang, Y. Xiang, J. Zhang and S. Yu, “A novel semi-supervised approach for network traffic clustering,” in 5th International Conference on Network and System Security (NSS), Milan,2011.
28
[21] C. T. Zahn, “Graph-Theoretical Methods for Detecting and Describing Gestalt Clusters,” IEEE Transactions on Computers, Vols. C-20, no. 1,pp. 68-86, 1971.
29
[22] C. Zhong and et al., “A graph-theoretical clustering method based on two rounds of minimum spanning trees,” Pattern Recognition, vol. 43, pp.752-766, 2010.
30
[23] “NLANR,” [Online]. Available: http://pma.nlanr.net.
31
[24] “MAWI,” [Online]. Available: http://mawi.wide.ad.jp/mawi/.
32
[25] “DARPA 1999 intrusion detection evaluation data,” [Online]. Available: https://www.ll.mit.edu/ideval/data/. “BRASIL,” [Online]. Available:
33
[26] https://www.cl.cam.ac.uk/research/srg/netos/projects/brasil/.
34
ORIGINAL_ARTICLE
NETRU: A Non-commutative and Secure Variant of CTRU Cryptosystem
In this paper we present a new finite field-based public key cryptosystem(NETRU) which is a non-commutative variant of CTRU. The original CTRU is defined by the ring of polynomials in one variable over a finite field F2. This system works in the ring R = F2[x]=hxN 1i and is already broken by some attacks such as linear algebra attack. We extend this system over finite fields Zp, where p is a prime (or prime power) and it operates over the non-commutative ring M = Mk(Zp)[T; x]=hXn Ikki, where M is a matrix ring of k by k matrices of polynomials in R = Zp[T; x]=hxn 1i. In the proposed NETRU, the encryption and decryption computations are non-commutative and hence the system is secure against linear algebra attack as lattice-based attacks. NETRU is designed based on the CTRU core and exhibits high levels of security with two-sided matrix multiplication.
https://www.isecure-journal.com/article_54997_681d86e37a0a6f7fa6bbf26a47907972.pdf
2018-01-01
45
53
10.22042/isecure.2018.0.0.2
Lattice-based Cryptography
CTRU
Matrix Rings
Finite Fields
Reza
Ebrahimi Atani
rebrahimi@guilan.ac.ir
1
Department of Computer Engineering, University of Guilan, Rasht, Iran
LEAD_AUTHOR
Shahabaddin
Ebrahimi Atani
ebrahimiatani@gmail.com
2
University Campus 2, Department of Mathematics, University of Guilan, Rasht, Iran
AUTHOR
A.
Hassani Karbasi
karbasi@phd.guilan.ac.ir
3
University Campus 2, Department of Mathematics, University of Guilan, Rasht, Iran
AUTHOR
[1] W. Diffie, and M.E. Hellman, New directions in cryptography, In IEEE Trans. On Information Theory, (1976), Vol. 22, pages 644-654.
1
[2] N. Koblitz, and A.J. Menezes, A Survey of Public Key Cryptosystems, SIAM Review, (2004), Vol.46, No. 4, pages 599-634.
2
[3] R.J. McEliece, A public key cryptosystem based on algebraic coding theory, JPL DSN Progress Report, (1978), No. 42-44, pages 114-116.
3
[4] T. Matsumoto, and H. Imai, Public quadratic polynomial-tuples for efficient signatureverification and message-encryption, In Proceeding of Eurocrypt ’88, (1988), LNCS of vol. 330,Springer-Verlag, pages 419-453.
4
[5] J. Ding, A new variant of the Matsumoto-Imaicryptosystem through perturbation, In Proceeding of PKC ’04, (2004), LNCS of vol. 2947, Springer-Verlag, pages 305-318.
5
[6] O. Regev, Lattice-based cryptography, In Advances in cryptology-CRYPTO, (2006), pages131–141.
6
[7] O. Regev, On lattices, learning with errors, random linear codes, and cryptography, J. ACM,(2005), Vol. 56, No. 6, pages 1–40. Preliminary version in STOC 2005.
7
[8] C. Peikert, V. Vaikuntanathan, and B. Waters, A framework for efficient and composable oblivious transfer, In CRYPTO, (2008), pages 554–571.
8
[9] X. Boyen, Lattice mixing and vanishing trapdoors: A framework for fully secure short signatures and more, In Public Key Cryptography,(2010), pages 499–517.
9
[10] C. Gentry, C. Peikert, and V. Vaikuntanathan, Trapdoors for hard lattices and new cryptographic constructions, In STOC, (2008), pages 197–206.
10
[11] V. Lyubashevsky, Lattice signatures without trapdoors, In EUROCRYPT, (2012), pages 738–755.
11
[12] D. Cash, D. Hofheinz, E. Kiltz, and C. Peikert, Bonsai trees, or how to delegate a lattice basis, In EUROCRYPT, (2010), pages 523–552.
12
[13] S. Agrawal, D. Boneh, and X. Boyen, Lattice basis delegation in fixed dimension and shorter ciphertext hierarchical IBE, In CRYPTO, (2010), pages 98–115.
13
[14] Z. Brakerski and V. Vaikuntanathan, Efficient fully homomorphic encryption from (standard) LWE, In FOCS, (2011), pages 97–106.
14
[15] J. Hoffstein, J. Pipher, and J.H. Silverman, NTRU: A Ring-Based Public Key Cryptosystem, In Proceedings of the 3rd International Symposium on Algorithmic Number Theory (ANTS-III), (1998), pages 267-288.
15
[16] D. Coppersmith, and A. Shamir, Lattice attacks on NTRU, in EUROCRYPT, (1997), pages 52–61.
16
[17] C. Gentry, Key recovery and message attacks on NTRU-composite, Eurocrypt 01, (2001), Springer LNCS 2045, pages 182-194.
17
[18] Standard Specifications for Public Key Cryptographic Techniques Based on Hard Problems over Lattices. IEEE P1363, 2008. Available at http://grouper.ieee.org/groups/1363/.
18
[19] D. Han, J. Hong, J.W. Han, and D. Kwon, Key recovery attacks on NTRU without ciphertext validation routine, In Proceeding of ACISP ’03, (2003), LNCS of vol. 2727, Springer-Verlag, pages 274-284.
19
[20] M. Coglianese, and B. M. Go, MaTRU: A New NTRU-Based Cryptosystem, INDOCRYPT, Lecture Notes in Computer Science, (2005), No. 3797 pages 232-243.
20
[21] E. Malekian, A. Zakerolhosseini, and A.Mashatan, QTRU: Quaternionic Version of the NTRU Public Key Cryptosystems, The int’l Journal of information Security (ISeCure), (2011), Vol. 3, No. 1, pages 29-42.
21
[22] P. Gaborit, J. Ohler, and P. Sole, CTRU, a polynomial analogue of NTRU, Technical report, INRIA, (2002).
22
[23] R. Kouzmenko, Generalizations of the NTRU Cryptosystem, Master’s thesis, Polytechnique Montreal, Canada, (2006).
23
[24] M. O. Rabin, Probabilistic algorithms in finite fields, SIAM J. Comp., (1980), No. 9, pages 273-280.
24
[25] M. Butler, On the reducibility of polynomials over a finite field, Quart. J. Math. Oxford 5(1954), pages 102-107.
25
[26] J. von zur Gathen, and V. Shoup, Computing Frobenius maps and factoring polynomials, Comput complexity, (1992), No. 2, pages 187-224.
26
[27] V. Shoup, Fast construction of irreducible polynomials over finite fields, J. Symb. Comp., (1995), No. 17, pages 371-391.
27
[28] M. Ben-Or, Probabilistic algorithms in finite fields, In Proc. 22nd IEEE Symp. Foundations Computer Science, (1981), pages 394-398.
28
[29] N. Howgrave-Graham, J.H. Silverman, and W.Whyte, A Meet-In-The-Middle Attack on an NTRU Private Key, Technical report, Security Innovation Inc., Boston, MA, USA, (2002). Available at http://securityinnovation.com/ cryptolab/pdf/NTRUTech004v2.pdf.
29
[30] E. Jaulmes, and A. Joux, A Chosen Ciphertext Attack against NTRU, In Proceedings of the 20th Annual International Cryptology Conference on Advances in Cryptology-CRYPTO, (2000), pages 20-36.
30
[31] J. Hoffstein, and J. Silverman, Optimizations for NTRU, Technical Report 015, NTRU Cryptosystems, (2000). Available
31
at http://www.sisecure.com/cryptolab/pdf/ TECH_ARTICLE_OPT.pdf.
32
[32] P.Q. Nguyen, and D. Stehle, LLL on the Average, In Proceedings of the 7th International Symposium on Algorithmic Number Theory (ANTSVII), (2006), pages 238-256.
33
[33] P.Q. Nguyen, and D. Stehle, Low Dimensional Lattice Basis Reduction Revisited, ACM Transactions on Algorithms, (2009), Vol. 5, No. 4, pages 1-48.
34
[34] R.E. Atani, S.E. Atani, and A.H. Karbasi, EEH: A GGH-Like Public Key Cryptosystem Over The Eisenstein Integers Using Polynomial Representation, The ISC International Journal of Information Security, (2015), Vol. 7, No. 2, pages 115-126.
35
[35] A.H. Karbasi, and R.E. Atani, ILTRU: An NTRU-Like Public Key Cryptosystem Over Ideal Lattices, IACR Cryptology ePrint Archive 2015: 549, (2015).
36
[36] A.H. Karbasi, R.E. Atani, and S.E. Atani, A New Ring-Based SPHF and PAKE Protocol On Ideal Lattices, Submitted.
37
[37] S.E. Atani, R.E. Atani, and A.H.Karbasi, PairTRU: Pairwise Non-commutative Extension of The NTRU Public key Cryptosystem, Submitted
38
ORIGINAL_ARTICLE
BotRevealer: Behavioral Detection of Botnets based on Botnet Life-cycle
Nowadays, botnets are considered as essential tools for planning serious cyber attacks. Botnets are used to perform various malicious activities such as DDoS attacks and sending spam emails. Different approaches are presented to detect botnets; however most of them may be ineffective when there are only a few infected hosts in monitored network, as they rely on similarity in bots activities to detect the botnet. In this paper, we present a host-based method that can detect individual bot-infected hosts. This approach is based on botnet life-cycle, which includes common symptoms of almost all types of botnet despite their differences. We analyze network activities of each process running on the host and propose some heuristics to distinguish behavioral patterns of bot process from legitimate ones based on statistical features of packet sequences and evaluating an overall security risk for it. To show the effectiveness of the approach, a tool named BotRevealer has been implemented and evaluated using real botnets and several popular applications. The results show that in spite of diversity of botnets, BotRevealer can effectively detect the bot process among other active processes.
https://www.isecure-journal.com/article_51289_efe61281fbe90f209ed82bddfa1ae64d.pdf
2018-01-01
55
61
10.22042/isecure.2017.81520.374
Botnet Detection
Botnet Life-Cycle
Host-Based Intrusion Detection
Heuristic Algorithm
E.
Khoshhalpour
ehsan.khoshhalpour@chmail.ir
1
Department of Computer Engineering and Information Technology, Amirkabir University of Technology, Tehran, Iran
LEAD_AUTHOR
H. R.
Shahriari
shahriari@aut.ac.ir
2
Department of Computer Engineering and Information Technology, Amirkabir University of Technology, Tehran, Iran
AUTHOR
[1] W. Lee, C. Wang, and D. Dagon, Botnet detection: countering the largest security threat. Springer, 2008.
1
[2] J. Goebel and T. Holz, “Rishi: Identify Bot Contaminated Hosts by IRC Nickname Evaluation,” in First Workshop on Hot Topics in Understanding Botnets (HotBots’07), 2007.
2
[3] G. Gu, P. Porras, V. Yegneswaran, M. Fong, W. Lee, and M. Park, “BotHunter: Detecting Malware Infection Through IDS-Driven Dialog Correlation,” in Proceedings of the 16th USENIX Security Symposium (Security’07), 2007.
3
[4] G. Gu, R. Perdisci, J. Zhang, and W. Lee, “Bot-Miner: Clustering Analysis of Network Traffic for Protocol- and Structure-Independent Botnet Detection,” in Proceedings of the 17th USENIX Security Symposium (Security’08), 2008.
4
[5] M. Eslahi, M. Yousefi, M. V. Naseri, Y. Yussof, N. Tahir, and H. Hashim, “Cooperative Network Behaviour Analysis Model for Mobile Botnet Detection,” in IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE), 2016, pp.107–112.
5
[6] C. Dietz, A. Sperotto, G. Dreo, and A. Pras, “How to Achieve Early Botnet Detection at the Provider Level?,” in IFIP International Conference on Autonomous Infrastructure, Management and Security, 2016, pp. 142–146.
6
[7] R. Aryan, and H.R. Shahriari, “Botnet detection based on network behavioral and anomaly detection,” 18th National CSI Computer Conference, Iran (Islamic Republic of), 12-15 March 2013
7
[8] F. Giroire, J. Chandrashekar, N. Taft, E.Schooler, and D. Papagiannaki, “Exploiting Temporal Persistence to Detect Covert Botnet Channels,” in 12th International Symposium on Recent Advances in Intrusion Detection (RAID’09), Springer Berlin Heidelberg, 2009, pp. 326–345.
8
[9] G. Fedynyshyn, M. C. Chuah, and G. Tan, “Detection and Classification of Different Botnet C&C Channels,” in Autonomic and Trusted Computing, Springer Berlin Heidelberg, 2011, pp.228–242.
9
[10] L. Cavallaro, C. Kruegel, and G. Vigna, “Mining the Network Behavior of Bots,” Tech. Rep. 2009-12, Department of Computer Science, University of California at Santa Barbara (UCSB), CA, USA, 2009. .
10
[11] G. Kirubavathi and R. Anitha, “Botnet detection via mining of traffic flow characteristics,” Computers & Electrical Engineering, vol. 50, pp.91–101, 2016.
11
[12] R. A. Rodríguez-Gómez, G. Maciá-Fernández, and P. García-Teodoro, “Analysis of Botnets throuth Life-Cycle,” in Proceedings of International Conference on Security and Cryptography(SECRYPT), 2011, pp. 257–262.
12
[13] N. Hachem, Y. Ben Mustapha, G. G. Granadillo, and H. Debar, “Botnets: Lifecycle and Taxonomy,”in Conference on Network and Information Systems Security (SAR-SSI), IEEE, 2011,pp. 1–8.
13
[14] F. Naseem, U. Sabir, M. Shafqat, and A.Shahzad, “A Survey of Botnet Technology and Detection,” International Journal of Video & Image Processing and Network Security (IJVIPNSIJENS),vol. 10, no. 1, pp. 13–17, 2010.
14
[15] S. García, V. Uhlír, and M. Rehak, “Identifying and Modeling Botnet C & C Behaviors,” in In Proceedings of the 1st International Workshop on Agents and CyberSecurity, ACM, 2014.
15
[16] “CVUT Malware Capture Facility Project,” https://agents.fel.cvut.cz/malwarecapture-facility, [Accessed: 10- Oct-2016].
16
[17] R. S. Abdullah, M. F. Abdollah, Z. Azri, M.Noh, M. Zaki, and S. R. Selamat, “Revealing the Criterion on Botnet Detection Technique,” IJCSI International Journal of Computer Science, vol.10, no. 2, pp. 208–215, 2013.
17
ORIGINAL_ARTICLE
A Decentralized Online Sortition Protocol
We propose a new online sortition protocol which is decentralized. We argue that our protocol has safety, fairness, randomness, non-reputation and openness properties. Sortition is a process that makes random decision and it is used in competitions and lotteries to determine who is the winner. In the real world, sortition is simply done using a lottery machine and all the participant can be sure about the safety, fairness, randomness, non-reputation, and openness properties. But how we can do the sortition in virtual world such that it satisfies the desired properties? The idea is decentralization. Using cryptography notions, we provide a protocol where all agents participate in computing the winner of sortition. Our proposed protocol is novel and completely differs from other sortition protocols and also it is decentralized. It is simple and easily can be implemented and find the commercial use for those markets who want to give present to their customers in a fair and clear manner.
https://www.isecure-journal.com/article_57812_a0f5a541baba545e1c86b82bbb0ce77c.pdf
2018-01-01
63
69
10.22042/isecure.2018.113240.403
sortition
Protocols
Mechanism Design
R.
Ramezanian
ramezanian@sharif.ir
1
Ferdowsi University of Mashhad, Department of Mathematical Sciences, Mashhad, Iran
LEAD_AUTHOR
M.
Pourpouneh
mohsen.pourpoune@gmail.com
2
Sharif University of Technology, Department of Mathematical Sciences, Tehran, Iran
AUTHOR
[1] Atila Abdulkadiroglu and Tayfun Sönmez. Random serial dictatorship and the core from random endowments in house allocation problems. Econometrica, 66(3):689–701, 1998.
1
[2] Yeon-Koo Che and Fuhito Kojima. Asymptotic equivalence of probabilistic serial and random priority mechanisms. Econometrica, 78(5):1625–1672, 2010.
2
[3] Noam Nisan and Amir Ronen. Algorithmic mechanism design. In Proceedings of the thirty-first annual ACM symposium on Theory of computing, pages 129–140. ACM, 1999.
3
[4] Kenneth J Arrow, Amartya Sen, and Kotaro Suzumura. Handbook of social choice and welfare, volume 2. Elsevier, 2010.
4
[5] Felix Brandt, Vincent Conitzer, Ulle Endriss, Ariel D Procaccia, and Jérôme Lang. Handbook of computational social choice. Cambridge University Press, 2016.
5
[6] Atila Abdulkadiroglu and Tayfun Sönmez.School choice: A mechanism design approach. The American Economic Review, 93(3):729–747, 2003.
6
[7] Rafik Makhloufi, Grégory Bonnet, Guillaume Doyen, and Dominique Gaïti. Decentralized aggregation protocols in peer-to-peer networks: a survey. In IEEE International Workshop on Modelling Autonomic Communications Environments,
7
pages 111–116. Springer, 2009.
8
[8] JA Alvarez Bermejo, MA Lodroman, and JA Lopez-Ramos. A decentralized protocol for mobile control access. The Journal of Supercomputing,70(2):709–720, 2014.
9
[9] Airlie Chapman, Eric Schoof, and Mehran Mesbahi.Semi-autonomous networks: theory and decentralized protocols. In Robotics and Automation(ICRA), 2010 IEEE International Conference on, pages 1958–1963. IEEE, 2010.
10
[10] Manuel Blum. Coin flipping by telephone a protocol for solving impossible problems. ACM SIGACT News, 15(1):23–27, 1983.
11
[11] Tal Rabin and Michael Ben-Or. Verifiable secret sharing and multiparty protocols with honest majority. In Proceedings of the twenty-first annual ACM symposium on Theory of computing, pages 73–85. ACM, 1989.
12
[12] Richard Cleve. Limits on the security of coin flips when half the processors are faulty. In Proceedings of the eighteenth annual ACM symposium on Theory of computing, pages 364–369.ACM, 1986.
13
[13] Biao He and Yu Wei. Electronic sortition. In The 2009 International Symposium on Intelligent Information Systems and Applications (IISA 2009),page 203, 2009.
14
[14] Stéphane Grumbach and Robert Riemann. Distributed random process for a large-scale peer to peer lottery. In IFIP International Conference on Distributed Applications and Interoperable Systems, pages 34–48. Springer, 2017.
15
[15] Arjen K Lenstra and Benjamin Wesolowski. A random zoo: sloth, unicorn, and trx. IACR Cryptology ePrint Archive, - -:366, 2015.
16
[16] David M Goldschlag and Stuart G Stubblebine. Publicly verifiable lotteries: Applications of delaying functions. In International Conference on Financial Cryptography, pages 214–226. Springer,1998.
17
[17] Sherman SM Chow, Lucas CK Hui, Siu-Ming Yiu, and KP Chow. An e-lottery scheme using verifiable random function. In International Conference on Computational Science and its Applications, pages 651–660. Springer, 2005.
18
[18] Silvio Micali, Michael Rabin, and Salil Vadhan. Verifiable random functions. In Foundations of Computer Science, 1999. 40th Annual Symposium on, pages 120–130. IEEE, 1999.
19
ORIGINAL_ARTICLE
Persian Abstract
Persian Abstract of the online manuscripts
https://www.isecure-journal.com/article_73735_fb61d6c88c5b859616f3d613c5412c61.pdf
2018-01-01
71
76
10.22042/isecure.2018.10.1.8
There are no references for the Persian abstracts
1