ORIGINAL_ARTICLE
A survey on digital data hiding schemes: principals, algorithms, and applications
This paper investigates digital data hiding schemes. The concept of information hiding will be explained at first, and its traits, requirements, and applications will be described subsequently. In order to design a digital data hiding system, one should first become familiar with the concepts and criteria of information hiding. Having knowledge about the host signal, which may be audio, image, or video and the final receiver, which is Human Auditory System (HAS) or Human Visual System (HVS), is also beneficial. For the speech/audio case, HAS will be briefly reviewed to find out how to make the most of its weaknesses for embedding as much data as possible. The same discussion also holds for the image watermarking. Although several audio and image data hiding schemes have been proposed so far, they can be divided into a few categories. Hence, conventional schemes along with their recently published extensions are introduced. Besides, a general comparison is made among these methods leading researchers/designers to choose the appropriate schemes based on their applications. Regarding the old scenario of the prisoner-warden and the evil intention of the warden to eavesdrop and/or destroy the data that Alice sends to Bob, there are both intentional and unintentional attacks to digital information hiding systems, which have the same effect based on our definition. These attacks can also be considered for testing the performance or benchmarking, of the watermarking algorithm. They are also known as steganalysis methods which will be discussed at the end of the paper.
http://www.isecure-journal.com/article_39134_fa8d8264a6ef71d410a75af0365ec2fe.pdf
2013-01-01T11:23:20
2018-02-20T11:23:20
5
36
10.22042/isecure.2013.5.1.2
Data hiding
watermarking
capacity
Robustness
security
Steganalysis
M. A.
Akhaee
akhaee@ut.ac.ir
true
1
LEAD_AUTHOR
F.
Marvasti
marvasti@sharif.edu
true
2
AUTHOR
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ORIGINAL_ARTICLE
Design and formal verification of DZMBE+
In this paper, a new broadcast encryption scheme is presented based on threshold secret sharing and secure multiparty computation. This scheme is maintained to be dynamic in that a broadcaster can broadcast a message to any of the dynamic groups of users in the system and it is also fair in the sense that no cheater is able to gain an unfair advantage over other users. Another important feature of our scheme is collusion resistance. Using secure multiparty computation, a traitor needs k cooperators in order to create a decryption machine. The broadcaster can choose the value of k as he decides to make a trade-off between communication complexity and collusion resistance. Comparison with other Broadcast Encryption schemes indicates enhanced performance and complexity on the part of the proposed scheme (in terms of message encryption and decryption, key storage requirements, and ciphertext size) relative to similar schemes. In addition, the scheme is modeled using applied pi calculus and its security is verified by means of an automated verification tool, i.e., ProVerif.
http://www.isecure-journal.com/article_39135_a837619ce7b3e26f5d6110ab1d021d6d.pdf
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10.22042/isecure.2013.5.1.3
Broadcast Encryption
Secure Multiparty Computation
Threshold Secret Sharing
Formal Methods
Applied pi Calculus
M.
Soodkhah Mohammadi
xemailpro@yahoo.co.uk
true
1
LEAD_AUTHOR
A.
Ghaemi Bafghi
ghaemib@ferdowsi.um.ac.ir
true
2
AUTHOR
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ORIGINAL_ARTICLE
Provably secure and efficient identity-based key agreement protocol for independent PKGs using ECC
Key agreement protocols are essential for secure communications in open and distributed environments. Recently, identity-based key agreement protocols have been increasingly researched because of the simplicity of public key management. The basic idea behind an identity-based cryptosystem is that a public key is the identity (an arbitrary string) of a user, and the corresponding private key is generated by a trusted Private Key Generator (PKG). However, it is unrealistic to assume that a single PKG will be responsible for issuing private keys to members of different organizations or a large-scale nation. Hence, it is needed to consider multiple PKG environments with different system parameters. In this paper, we propose an identity-based key agreement protocol among users of different networks with independent PKGs, which makes use of elliptic curves. We prove the security of the proposed protocol in the random oracle model and show that all security attributes are satisfied. We also demonstrate a comparison between our protocol and some related protocols in terms of the communication costs and the execution time. The results show that the execution time of our protocol is less than 10%, and its communication costs are about 50% of the competitor protocols.
http://www.isecure-journal.com/article_39136_720abc23e66b24a1564536558e5d8afb.pdf
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10.22042/isecure.2013.5.1.4
Identity-Based Cryptography
Key Agreement Protocol
Elliptic Curve Cryptography
Random Oracle Model
M.
Sabzinejad Farash
sabzinejad@tmu.ac.ir
true
1
sabzinejad@tmu.ac.ir
sabzinejad@tmu.ac.ir
sabzinejad@tmu.ac.ir
LEAD_AUTHOR
M.
Ahmadian Attari
mahmoud@eetd.kntu.ac.ir
true
2
AUTHOR
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doi:10.1016/j.camwa.2012.01.041.
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[19] M.S. Farash, M.A. Attari, "A new improved and efficient authenticated multiple-key agreement protocol based on bilinear pairings," Computers & Electrical Engineering, 2012, http://dx.doi.
21
org/10.1016/j.compeleceng.2012.09.004.
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[22] P. Barreto, B. Lynn, M. Scott, "On the selection of pairing-friendly groups," Selected Areas in Cryptography (SAC 2003), LNCS, vol. 3006, 2003, pp. 17-25.
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28
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49
ORIGINAL_ARTICLE
DyVSoR: dynamic malware detection based on extracting patterns from value sets of registers
To control the exponential growth of malware files, security analysts pursue dynamic approaches that automatically identify and analyze malicious software samples. Obfuscation and polymorphism employed by malwares make it difficult for signature-based systems to detect sophisticated malware files. The dynamic analysis or run-time behavior provides a better technique to identify the threat. In this paper, a dynamic approach is proposed in order to extract features from binaries. The run-time behavior of the binary files were found and recorded using a homemade tool that provides a controlled environment. The approach based on DyVSoR assumes that the run-time behavior of each binary can be represented by the values of registers. A method to compute the similarity between two binaries based on the value sets of the registers is presented. Hence, the values are traced before and after invoked API calls in each binary and mapped to some vectors. To detect an unknown file, it is enough to compare it with dataset binaries by computing the distance between registers, content of this file and all binaries. This method could detect malicious samples with 96.1% accuracy and 4% false positive rate. The list of execution traces and the dataset are reachable at: http://home.shirazu.ac.ir/˷ sami/malware
http://www.isecure-journal.com/article_39137_2ec12eb8dddec2ad8da9da145ee933b7.pdf
2013-01-01T11:23:20
2018-02-20T11:23:20
71
82
10.22042/isecure.2013.5.1.5
Malware Detection
API Call
Dynamic analysis
CPU Register Values
x86 Registers Values
M.
Ghiasi
mhbbgh@gmail.com
true
1
AUTHOR
A.
Sami
asami@ieee.org
true
2
LEAD_AUTHOR
Z.
Salehi
zsalehi@cse.shirazu.ac.ir
true
3
AUTHOR
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[6] X. Hu, "Large-Scale Malware Analysis, Detection, and Signature Generation," A dissertation for the degree of Doctor of Philosophy, University of Michigan, Ann Arbor. Michigan. United States, 2011.
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[7] P. Wood, M. Nisbet, G. Egan, N. Johnston, K. Haley, B. Krishnappa, T. K. Tran, I. Asrar, O. Cox, S. Hittel, et al., "Symantec Internet Security Threat Report Trends for 2011," Vol. 17, Symantec Corporation, 2012.
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Proceeding of 16th CSI Symposium on Artificial Intelligence and Signal Processing (AISP 2012), Shiraz, Iran, 2012.
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62
ORIGINAL_ARTICLE
Robust multiplicative video watermarking using statistical modeling
The present paper is intended to present a robust multiplicative video watermarking scheme. In this regard, the video signal is segmented into 3-D blocks like cubes, and then, the 3-D wavelet transform is applied to each block. The low frequency components of the wavelet coefficients are then used for data embedding to make the process robust against both malicious and unintentional attacks. The hidden message is inserted through multiplying/dividing these coefficients by a constant parameter which controls the power of the watermark. The watermark extraction relies on a maximum likelihood-based procedure, observing the distribution of the watermarked coefficients. The performance of the proposed scheme has been verified via simulations and found to be superior to some of the well-known existing video watermarking methods.
http://www.isecure-journal.com/article_39138_dc5d300e700aa3d1ae93d99a61c1e51e.pdf
2013-01-01T11:23:20
2018-02-20T11:23:20
83
95
10.22042/isecure.2013.5.1.6
Multiplicative Video Watermarking
Maximum Likelihood Decoding
3D Wavelet Transform
A.
Diyanat
a.diyanat@ut.ac.ir
true
1
LEAD_AUTHOR
M. A.
Akhaee
akhaee@ut.ac.ir
true
2
AUTHOR
Sh.
Ghaemmaghami
ghaemmagh@sharif.edu
true
3
AUTHOR
[1] G. Döerr, “A Guide Tour of Video Watermarking,” Signal Processing: Image Communication, vol. 18, pp. 263-282, Apr. 2003.
1
[2] Y. Chen and H. Huang, “A New Shot-Based Video Watermarking,” in Computer Communication Control and Automation (3CA), International Symposium on, vol. 2, pp. 53-58, 2010.
2
[3] M. Belhaj, M. Mitrea, F. Preteux, and S. Duta, “MPEG-4 AVC robust video watermarking based on QIM and perceptual masking,” in Communications (COMM), 8th International Conference on, pp. 477-480,2010.
3
[4] D. Xu, R. Wang, and J. Wang, “Low complexity video watermarking algorithm by exploiting CAVLC in H. 264/AVC,” in Wireless Communications, Networking and Information Security (WCNIS), IEEE International Conference on, pp. 411-415, 2010.
4
[5] L. Zhang, Y. Zhu, and L. L.-M. Po, “A novel watermarking scheme with compensation in bit stream domain for H.264/AVC,” IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 1758-1761, Mar. 2010.
5
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8
[9] R. Lancini, F. Mapelli, and S. Tubaro, “A Robust Video Watermarking Technique In the Spatial Domain,” in Video/Image Processing and Multimedia Communications 4th EURASIP-IEEE Region 8 International Symposium on VIProm-Com, no. June, pp. 251-256, 2002
9
[10] P. Chan and M. Lyu, “A DWT-based digital video watermarking scheme with error correcting code,” in Proceedings of Fifth International Conference on Information and Communications Security, pp. 202-213, Springer, 2003.
10
[11] F. Deguillaume, G. Csurka, J. O’Ruanaidh, and T. Pun, “Robust 3D DFT Video Watermarking,” in Proceedings of IS & T/SPIE Electronic Imaging, vol. 3657, pp. 113-124, 1999.
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[14] B. Barakli and C. Vural, “A new reversible video watermarking method-based on motion compensated interpolation,” in 20th Signal Processing and Communications Applications Conference (SIU), pp. 1-4, IEEE, Apr. 2012.
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[15] B. Mobasseri, “Direct Sequence Watermarking of Digital Video Using M-Frames,” in Proceedings International Conference on Image Processing (ICIP-98), vol. 2, pp. 399-403, 1998.
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[17] S. a. M. Al-Taweel and P. Sumari, “Robust Video Watermarking Based On 3D-DWT Domain,” in TENCON , IEEE Region 10 Conference, pp. 1-6, Nov. 2010.
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[18] P. Campisi, “Video watermarking in the 3DDWT domain using perceptual masking,” in IEEE International Conference on Image Processing(ICIP), pp. 997-1000, 2005.
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[19] R. Reyes, C. Cruz, M. Nakano-Miyatake, and H. Perez-Meana, “Digital Video Watermarking in DWT Domain Using Chaotic Mixtures,” Latin America Transactions, IEEE (Revista IEEE America Latina), vol. 8, no. 3, pp. 304-310, 2010.
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[20] R. O. Preda, “Robust wavelet-based video watermarking scheme for copyright protection using the human visual system,” Journal of Electronic Imaging, vol. 20, p. 013022, Jan. 2011.
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[21] M. Swanson and A. Tewfik, “Multi resolution Scene-Based Video Watermarking Using Perceptual Models,” IEEE Journal on Selected Areasin Communications, vol. 16, pp. 540-550, May 2002.
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[22] J. Sun, N. Yang, J. Liu, X. Yang, X. Li, and L. Zhang, “Video watermarking scheme based on spatial relationship of DCT coefficients,” in Intelligent Control and Automation (WCICA), 8th World Congress on, pp. 56-59, 2010.
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[23] E. E. Abdallah, A. Ben Hamza, and P. Bhattacharya, “Video watermarking using wavelet transform and tensor algebra,” Signal, Image and Video Processing, vol. 4, pp. 233-245, Apr. 2009.
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27
[28] M. A. Akhaee, S. M. E. Sahraeian, B. Sankur, and F. Marvasti, “Robust Scaling-Based Image Watermarking Using Maximum- Likelihood Decoder With Optimum Strength Factor,” IEEE Transactions on Multimedia, vol. 11, pp. 822-833, Aug. 2009.
28
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ORIGINAL_ARTICLE
Image encryption based on chaotic tent map in time and frequency domains
The present paper is aimed at introducing a new algorithm for image encryption using chaotic tent maps and the desired key image. This algorithm consists of two parts, the first of which works in the frequency domain and the second, in the time domain. In the frequency domain, a desired key image is used, and a random number is generated, using the chaotic tent map, in order to change the phase of the plain image. This change in the frequency domain causes changes in the pixels value and shuffles the pixels location in the time domain. Finally, in the time domain, a pseudo random image is produced using a chaotic tent map, to be combined to the image generated through the first step, and thus the final encrypted image is created. A computer simulation is also utilized to evaluate the proposed algorithm and to compare its results to images encrypted by other methods. The criteria for these comparisons are chi-square test of histogram, correlation coefficients of pixels, NPCR (number of pixel change rate), UACI (unified average changing intensity), MSE (mean square error) and MAE (mean absolute error), key space, and sensitivity to initial condition. These comparisons reveal that the proposed chaotic image encryption method shows a higher performance, and is of more secure.
http://www.isecure-journal.com/article_39139_c5f1135db3f803d6cce0fb031b26b92c.pdf
2013-01-01T11:23:20
2018-02-20T11:23:20
97
110
10.22042/isecure.2013.5.1.7
Image Encryption
Chaotic Tent Map
Key Image
Frequency Domain
Time Domain
E.
Hassani
e.hasani@srbiau.ac.ir
true
1
LEAD_AUTHOR
M.
Eshghi
m-eshghi@sbu.ac.ir
true
2
AUTHOR
[1] E. Hasani, M. Eshghi, “Chaotic Image Encryption In Time and Frequency Domain”, 7th Iranian Machine Vision & Image Processing, IEEE conference, 2011.
1
[2] H. S. Kwok and W. K. S. Tang, “A Fast Image Encryption System Based on Chaotic Maps with Finite Precision Representation”, J. of Chaos, Solitons & Fractals, vol. 32, pp. 1518-1529, 2007.
2
[3] Y. Wang, K. W. Wong, X. Liao and G. Chen, “A New Chaos-based Fast Image Encryption Algorithm”, J. of Applied Soft Computing, Vol. 11, Issue 1, pp. 514-522, 2011.
3
[4] S. Sam, P. Devaraj and R. S. Bhuvaneswaran, “A Novel Image Cipher based on Mixed Transformed Logistic Maps”, J. of Multimedia Tools and Applications, Vol. 56, pp. 315-330, 2012.
4
[5] Kwok Sin Hung, “A Study On Efficient Chaotic Image Encryption Schemes”, Department of Electronic Engineering, CITY UNIVERSITY OF HUNG KONG, 2007.
5
[6] Sh. lian, “MultiMedia Content encryption”, Taylor & Francis Group, 2009.
6
[7] S. M. Seyedzadeh and S. Mirzakuchaki, “A Fast Color Image Encryption Algorithm based on Coupled Two-Dimensional Piecewise Chaotic Map”, J. of Signal Processing, Vol. 92, pp.1202- 1215, 2012.
7
[8] Y. Mao, G. Chen, and S. Lian, “A novel Fast Image Encryption Scheme Based on 3D Chaotic Baker Maps”, International Journal of Bifurcation and Chaos, vol.14, no.10, pp. 3613-3624, 2004.
8
[9] Q. Zhou, K-wo. Wong, X. Liao, T. Xiang and Y. Hu, “Parallel image encryption algorithm based on discretized chaotic map”, Chaos, Solitons & Fractals, vol. 38, pp. 1081-1092, 2008.
9
[10] X. Zhang, C. Wei-bin “A New Chaotic Algorithm for Image Encryption”, ICLIP2008, IEEE conference, 2008.
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[11] S.E. Borujeni and M. Eshghi, “Chaotic Image Encryption Design Using Tompkins-Paige Algorithm”, J. of Mathematical Problems in Engineering, 2009.
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[12] H. Khanzadi, M. Eshghi, “Image Encryption Using Random Bit Sequence Based on Chaotic Maps”, submitted to International Journal of Bifurcation and Chaos, 2012.
12
[13] Sh. Liu, J.Sun, Zhe. Xu, J. Liu, “Analysis on an Image Encryption Algorithm”, IEEE Computer society, 2008 International Workshop on Education Technology and Training & 2008 International Workshop on Geoscience and Remote Sensing.
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[14] Ch.Wei-bin, X. Zhang, “Image Encryption Algorithm Based on Henon Chaotic System”, IEEE, 2009.
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[15] K. T. Alligood, T. D. Sauer, J. A. Yorke, “CHAOS: An Introduction to Dynamical Systems”, Corrected third printing 2000, Springer-Verlag, New York, 1996.
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18
[19] H. Khanzadi, M. A. Omam, F. Lotfifar and M. Eshghi “Image Encryption Based on Gyrator Transform Using Chaotic Maps”, Signal Processing (ICSP) conference, China, 2010.
19
[20] Gonzalez and Wood, “Digital Image Processing”, 3rd edition, Prentice Hall, 2008.
20
[21] Y. Wang, K. W. Wong, X. Liao and G. Chen, “A New Chaos-based Fast Image Encryption Algorithm”, J. of Applied Soft Computing, Vol. 11, Issue 1, pp. 514-522, 2011.
21
[22] G. Zhang and Q. Liu, “A Novel Image Encryption Method based on Total Shuffling Scheme”, J. of Optics Communications, Vol. 284, pp. 2775-2780, 2011.
22
[23] X. Zhang and W. Chen, “A New Chaotic Algorithm for Image Encryption”, ICALIP, pp. 889-892, 2008.
23
[24] H. Gao, Y. Zhang, S. Liang and D. Li, “A new chaotic algorithm for image encryption”, J. of Chaos, Solitons & Fractals, vol. 29, pp. 393-399, 2006.
24
[25] Y. Wang, K. W. W, X. L and G. C, “A new chaos-based fast image encryption algorithm”, J. of Applied Soft Computing, vol. 11, pp. 514-522, 2009.
25
ORIGINAL_ARTICLE
Persian Abstract
http://www.isecure-journal.com/article_45223_be2605bb6b969d833bd157b02bffdd80.pdf
2013-01-25T11:23:20
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111
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10.22042/isecure.2013.5.1.8