Low-Complexity Multiclass Encryption by Compressed Sensing

IEEE Transactions on Signal Processing

Volumn 63, Issue 9, 2015, Pages 2183-2195

  Cambareri, Valerio ^a   Mangia, Mauro ^a   Pareschi, Fabio ^b   Rovatti, Riccardo ^a   Setti, Gianluca ^b  

^a UNIVERSITY OF BOLOGNA   (Italy)

^b UNIVERSITY OF FERRARA   (Italy)

Author keywords

Compressed sensing; encryption; secure communications; security

Indexed keywords

ALGORITHMS; COMPRESSED SENSING; COST BENEFIT ANALYSIS; ENCODING (SYMBOLS); FEATURE EXTRACTION; MOBILE SECURITY; RECOVERY; SECURE COMMUNICATION; SIGNAL RECEIVERS; SIGNAL RECONSTRUCTION;

ENCODING PROCESS; FEATURE EXTRACTION ALGORITHMS; PERFORMANCE BOUNDS; PRIVATE-KEY ENCRYPTION; QUALITY DEGRADATION; SECURITY; SECURITY PROPERTIES; SENSITIVE INFORMATIONS;

CRYPTOGRAPHY;

EID: 84926430155     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSP.2015.2407315     Document Type: Article

References (48)

1. I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, "A survey on sensor networks," IEEE Commun. Mag., vol. 40, no. 8, pp. 102-114, 2002.
2. Y. Wang, G. Attebury, and B. Ramamurthy, "A survey of security issues in wireless sensor networks," IEEE Commun. Surveys Tuts., vol. 8, no. 2, pp. 2-23, 2006.
3. J. Daemen and V. Rijmen, The Design of Rijndael: AES - The Advanced Encryption Standard. New York, NY, USA: Springer, 2002.
4. D. L. Donoho, "Compressed sensing," IEEE Trans. Inf. Theory, vol. 52, no. 4, pp. 1289-1306, Apr. 2006.
5. E. J. Candès and M. B. Wakin, "An introduction to compressive sampling,"IEEE Signal Process. Mag., vol. 25, no. 2, pp. 21-30, Mar. 2008.
6. J. A. Tropp, J. N. Laska, M. F. Duarte, J. K. Romberg, and R. G. Baraniuk, "Beyond Nyquist: Efficient sampling of sparse bandlimited signals,"IEEE Trans. Inf. Theory, vol. 56, no. 1, pp. 520-544, 2010.
7. M. Mishali, Y. C. Eldar, and A. J. Elron, "Xampling: Signal acquisition and processing in union of subspaces," IEEE Trans. Signal Process., vol. 59, no. 10, pp. 4719-4734, 2011.
8. J. Haboba, M. Mangia, F. Pareschi, R. Rovatti, and G. Setti, "A pragmatic look at some compressive sensing architectures with saturation and quantization," IEEE J. Emerg. Sel. Topics Circuits Syst.,, vol. 2, no. 3, pp. 443-459, Sep..
9. M. F. Duarte, M. A. Davenport, D. Takhar, J. N. Laska, T. Sun, K. F. Kelly, and R. G. Baraniuk, "Single-pixel imaging via compressive sampling," IEEE Signal Process. Mag., vol. 25, no. 2, pp. 83-91, 2008.
10. F. Chen, A. Chandrakasan, and V. Stojanovic, "Design and analysis of a hardware-efficient compressed sensing architecture for data compression in wireless sensors," IEEE J. Solid-State Circuits, vol. 47, no. 3, pp. 744-756, 2012.
11. E. J. Candès and T. Tao, "Near-optimal signal recovery from random projections: Universal encoding strategies?," IEEE Trans. Inf. Theory, vol. 52, no. 12, pp. 5406-5425, 2006.
12. th Annu. Allerton Conf. Commun., Control, Comput., Sep. 2008, pp. 813-817.
13. M. Herman and T. Strohmer, "General deviants: An analysis of perturbations in compressed sensing," IEEE J. Sel. Topics Signal Process., vol. 4, no. 2, pp. 342-349, 2010.
14. A. Orsdemir, H. O. Altun, G. Sharma, and M. F. Bocko, "On the security and robustness of encryption via compressed sensing," in Proc. IEEE Military Commun. Conf. (MILCOM), 2008, pp. 1-7.
15. V. Cambareri, J. Haboba, F. Pareschi, R. Rovatti, G. Setti, and K. W. Wong, "A two-class information concealing system based on compressed sensing," in Proc. IEEE Int. Symp. Circuits Syst. (ISCAS), 2013, pp. 1356-1359.
16. th Int. Conf. Embedd. Syst. (VLSID), 2013, pp. 31-36.
17. B. Klartag and S. Sodin, "Variations on the Berry - Esseen theorem,"Theory Probabil. Its Appl., vol. 56, no. 3, pp. 403-419, 2012.
18. P.-L. Loh and M. J. Wainwright, "Corrupted and missing predictors: Minimax bounds for high-dimensional linear regression," in Proc. IEEE Int. Symp. Inf. Theory (ISIT), Jul. 2012, pp. 2601-2605.
19. P.-L. Loh and M. J. Wainwright, "High-dimensional regression with noisy and missing data: Provable guarantees with nonconvexity," Ann. Statist., vol. 40, no. 3, p. 1637, 2012.
20. E. J. Candès and T. Tao, "Decoding by linear programming," IEEE Trans. Inf. Theory, vol. 51, no. 12, pp. 4203-4215, Dec. 2005.
21. E. J. Candès, J. K. Romberg, and T. Tao, "Stable signal recovery from incomplete and inaccurate measurements," Commun. Pure Appl. Math., vol. 59, no. 8, pp. 1207-1223, Aug. 2006.
22. E. J. Candès, "The restricted isometry property and its implications for compressed sensing," Comptes Rendus Mathematique, vol. 346, no. 9, pp. 589-592, 2008.
23. P. Billingsley, Probability and Measure. New York, NY, USA: Wiley, 2008.
24. R. Vershynin, "Introduction to the non-asymptotic analysis of random matrices," in Compressed Sensing: Theory and Applications. Cambridge, U.K.: Cambridge Univ. Press, 2012, pp. 210-268.
25. Z. Yang, C. Zhang, and L. Xie, "Robustly stable signal recovery in compressed sensing with structured matrix perturbation," IEEE Trans. Signal Process., vol. 60, no. 9, pp. 4658-4671, 2012.
26. R. a. Lata, "Some estimates of norms of random matrices," Proc. Amer. Math. Soc., vol. 133, no. 5, pp. 1273-1282, 2005.
27. D. Donoho and J. Tanner, "Precise undersampling theorems," Proc. IEEE, vol. 98, no. 6, pp. 913-924, Jun. 2010.
28. C. E. Shannon, "Communication theory of secrecy systems," Bell Syst. Tech. J., vol. 28, no. 4, pp. 656-715, Oct. 1949.
29. L. C. Washington and W. Trappe, Introduction to Cryptography: With Coding Theory. Englewood Cliffs, NJ, USA: Prentice-Hall PTR, 2002.
30. A. C. Berry, "The accuracy of the Gaussian approximation to the sum of independent variates," Trans. Amer. Math. Soc., vol. 49, no. 1, pp. 122-136, 1941.
31. J. A. Tropp and S. J. Wright, "Computational methods for sparse solution of linear inverse problems," Proc. IEEE, vol. 98, no. 6, pp. 948-958, 2010.
32. E. van den Berg and M. P. Friedlander, "Sparse optimization with least-squares constraints," SIAM J. Optim., vol. 21, no. 4, pp. 1201-1229, 2011.
33. E. van den Berg and M. P. Friedlander, "SPGL1: A solver for large-scale sparse reconstruction," 2007 [Online]. Available: http://www.cs.ubc.ca/labs/scl/spgl1
34. D. Needell and J. A. Tropp, "COSAMP: Iterative signal recovery from incomplete and inaccurate samples," Appl. Comput. Harmon. Anal., vol. 26, no. 3, pp. 301-321, 2009.
35. S. Rangan, "Generalized approximate message passing for estimation with random linear mixing," in Proc. IEEE Int. Symp. Inf. Theory (ISIT), 2011, pp. 2168-2172.
36. th Asilomar Conf. Signals, Syst, Comput. (ASILOMAR), 2011, pp. 799-803.
37. D. L. Donoho, A. Maleki, and A. Montanari, "Message-passing algorithms for compressed sensing," Proc. Nat. Acad. Sci., vol. 106, no. 45, pp. 18 914-18 919, 2009.
38. th Asilomar Conf. Signals, Syst., Comput. (ASILOMAR), 2011, pp. 804-808.
39. H. Zhu, G. Leus, and G. B. Giannakis, "Sparsity-cognizant total least-squares for perturbed compressive sampling," IEEE Trans. Signal Process., vol. 59, no. 5, pp. 2002-2016, 2011.
40. G. Pirker, M. Wohlmayr, S. Petrik, and F. Pernkopf, "A pitch tracking corpus with evaluation on multipitch tracking scenario," in Proc. Interspeech, Florence, Italy, Aug. 27-31, 2011, pp. 1509-1512.
41. K. Karhunen, Über Lineare Methoden in der Wahrscheinlichkeitsrechnung. Helsinki, Finland: Universitat Helsinki, 1947, vol. 37.
42. G. Shires and H. Wennborg, Web Speech API Specification, 2012 [Online]. Available: http://dvcs.w3.org/hg/speech-api/raw-file/tip/speechapi.html
43. G. Hinton et al., "Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups," IEEE Signal Process. Mag., vol. 29, no. 6, pp. 82-97, 2012.
44. A. L. Goldberger, L. A. N. Amaral, L. Glass, J. M. Hausdorff, P. C. Ivanov, R. G. Mark, J. E. Mietus, G. B. Moody, C.-K. Peng, and H. E. Stanley, "PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals," Circulation, vol. 101, no. 23, pp. e215-e220, Jun. 2000.
45. S. Mallat, A Wavelet Tour of Signal Processing. New York, NY, USA: Access Online via Elsevier, 1999.
46. R. Jane, A. Blasi, J. García, and P. Laguna, "Evaluation of an automatic threshold based detector of waveform limits in holter ECG with the QT database," in Proc. Comput. Cardiol., 1997, pp. 295-298.
47. th Int. Conf. Document Anal. Recognit. (ICDAR), 2007, vol. 2, pp. 629-633.
48. S. Geman, "A limit theorem for the norm of random matrices," Ann. Probabil., vol. 8, no. 2, pp. 252-261, 1980.