FIELD OF INVENTION
[001] The present invention generally relates to data security and cryptography  and more particularly to a methods and systems for securing data from unauthorized access.

BACKGROUND OF INVENTION
[002] As data communication becomes more pervasive and complex with evermore wide spread use  data security becomes wider  more complex and more important problem. Since the digital data in communication channels and distributed storage devices is inherently exposed to public users through network connectivity  the storage and communication services are becoming more and more vulnerable to security threat. Securing and protecting valuable multimedia and non-multimedia data on-the-fly becomes increasingly more demanding for commercial and personal communication applications. Several cryptographic techniques are used to encrypt and decrypt the data but have to achieve a tradeoff between channel bandwidth  robustness  and complexity. The existing methods require data compression techniques to be applied before data encryption as uncompressed data requires large storage space  data is not cost effective and requires very high channel bandwidth for data transfer over a network.
[003] Existing methods employ two-stage approach of compressing data and then encrypting this compressed data. These methods have higher computational complexities and require more memory space. The computational complexity and memory requirements of the data security system heavily depend on requirements of both compression and cryptographic techniques. It is not possible to use the above techniques in cascade manner without considering the impact of one technique over another. The data security methods using scrambling techniques that are implemented in temporal  spatial and frequency domains are not effective and efficient for storing or transmitting signals as these approaches significantly change the characteristics of the original signal. Thus  compression of data is not much achieved and demanding high bandwidth for transmission and more memory space for data storage. Conventional scrambling data techniques in the spatial (or temporal or frequency) domain provide limited possibilities of scrambled data and allow easy attack on security of data. Moreover  existing security techniques are not fast enough to process multimedia data collected via sensors and monitoring systems to meet the real-time constraints.
[004] Due to above mentioned reasons  existing data security systems fail to provide sufficient data security with high compression efficiency for storage and transmission. Also  it does not provide an effective solution for reducing the computing resources  transmission channel bandwidth  power consumption and processing time.

OBJECT OF INVENTION
[005] The principal object of the embodiments herein is to achieve devices  methods and systems for joint data security and compression in compressive measurement domain.
[006] Another object of the invention is to provide multilevel dynamic data security without substantially increasing computing and bandwidth resources giving an energy-efficient system.

SUMMARY
[007] Accordingly the invention provides a method for multi-level dynamic joint data security and compression  the method includes receiving input signal from a sensor interface  performing encryption on compressive measurement encoded data on the input signal  transmitting the encrypted compressive measurement encoded data through a communication network  performing decryption on compressive measurement decoded data after receiving the encrypted compressed measurement encoded data from the communication network  and reproducing original signal from the decrypted compressive measurement decoded data.
[008] Accordingly the invention provides a compressive encoding system for encoding input signal  the compressive encoding system is configured for receiving the input signal from a sensor interface  generating secret keys by a random secret key generator  performing compressive measurement on the input signal by compressive sensing module  applying dynamic scrambling on the compressive measurement signal using the secret key by dynamic scrambling module  applying quantization on the scrambled compressive measurement by quantizer  applying encoding on the quantized compressive measurement by encoder  applying interleaving on the encoded compressive measurement using the secret key by dynamic interleaver  combining the interleaved encoded compressive measurement  and encrypting secret keys generated by a random secret key’s generator.
[009] Accordingly the invention provides a transmission system for transmitting encrypted compressive measurement encoded data  the transmission system is configured for receiving the encrypted compressive measurement encoded data from compressive encoding system and transmitting the encrypted compressive measurement encoded data to a receiving system.
[0010] Accordingly the invention provides a storage system for storing encrypted compressive measurement encoded data  the storing system is configured for storing the encrypted compressive measurement encoded data received from compressive encoding system.
[0011] Accordingly the invention provides a compressive decoding system for decoding encrypted compressive measurement encoded data from a communication network  the compressive decoding system is configured for receiving the compressed encoded encrypted measurement data with encrypted secret key from a receiving system  decrypting the received encrypted secret key by decryption module  applying deinterleaving on the received interleaved compressive measurement using the decrypted secret key by a dynamic deinterleaver  applying decoding on the deinterleaved compressive measurement by a decoder  applying dequantization on the decoded compressive measurement by a dequantizer  applying dynamic descrambling on the dequantized compressive measurement using the decrypted secret key by a dynamic descrambler  applying sparse recovery process on the descrambled compressive measurement by sparse signal reconstruction module and reproducing original form of the compressed encoded signal by a reconstruction rules module.
[0012] Accordingly the invention provides a device for multi-level dynamic joint data security and compression  the device configured with an integrated circuit further including processor  memory having a computer program code within the circuit  the memory and the computer program code configured to with the processor cause the device to receive input signal from a sensor interface  perform encryption on compressive measurement encoded data on the input signal  transmit the encrypted compressive measurement encoded data through a communication network  perform decryption on compressive measurement decoded data after receiving the encrypted compressed measurement encoded data from the communication network  and reproduce original signal from the decrypted compressive measurement decoded data.
[0013] These and other aspects of the embodiments herein will be better appreciated and understood when considered in conjunction with the following description and the accompanying drawings. It should be understood  however  that the following descriptions  while indicating preferred embodiments and numerous specific details thereof  are given by way of illustration and not of limitation. Many changes and modifications may be made within the scope of the embodiments herein without departing from the spirit thereof  and the embodiments herein include all such modifications.

BRIEF DESCRIPTION OF FIGURES
[0014] This invention is illustrated in the accompanying drawings  throughout which like reference letters indicate corresponding parts in the various figures. The embodiments herein will be better understood from the following description with reference to the drawings  in which:
[0015] FIG. 1 illustrates general block diagram of a data communication and storage system  in accordance with various embodiments of the present invention;
[0016] FIG. 2 illustrates a multilevel dynamic joint data security and coding system using compressive sensing and sparse recovery techniques  in accordance with various embodiments of the present invention;
[0017] FIG. 3 illustrates a multilevel dynamic joint data security and coding system using compressive sensing and sparse recovery techniques and storing encrypted data  in accordance with various embodiments of the present invention;
[0018] FIG. 4 illustrates a flow diagram explaining the process of compressive sensing encoding system  in accordance with various embodiments of the present invention;
[0019] FIG. 5 illustrates block diagrams explaining different scrambling operations  in accordance with various embodiments of the present invention;
[0020] FIG. 6 illustrates a flow diagram explaining the process of compressive decoding system  in accordance with various embodiments of the present invention; and
[0021] FIG. 7 illustrates the graph that shows the performance of the compressive sensing based secured data processing system  in accordance with various embodiments of the present invention.

DETAILED DESCRIPTION OF INVENTION
[0022] The embodiments herein and the various features and advantageous details thereof are explained more fully with reference to the non-limiting embodiments that are illustrated in the accompanying drawings and detailed in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein can be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly  the examples should not be construed as limiting the scope of the embodiments herein.
[0023] The embodiments herein achieve methods and systems to perform multilevel dynamic joint data compression and security  in the compressive measurement domain without substantially increasing computing and bandwidth resources. The system uses the concepts of compressive sensing and sparse signal representation techniques making it simpler and more energy efficient. The system provides a compressive encoder which can perform functions such as compressive sampling  dynamic scrambling  quantization  encoding and dynamic interleaving and so on. The input data uses random secret keys before storage or transmission. The system also provides a compressive decoder which can perform functions such as dynamic de-interleaving  decoding  de-quantization  dynamic descrambling  sparse signal reconstruction  and so on to reconstruct original signal from received data using the secret keys received from the encoder. The system uses any of the wired or wireless communication interface and application protocol for data transmission and reception. The above enhanced functions of system provide simultaneous data security and compression on-the-fly so as to be useful in real time signal processing.
[0024] The compressive sensing (CS) is a powerful advanced signal processing technique in data acquisition theory that aims to approximates signal using a few measurements in sparse representation matrix by exploiting its compressibility or sparsity when acquiring/sensing signals but this simple technique for encrypting the random seed used for generation of compressive sensing matrix may not provide better security of data since partial data can be retrieved when unauthorized users employ some other random seed. The method and system disclosed overcomes this drawback by using compressive sensing and sparse signal reconstruction techniques to provide joint compression and security (encryption and decryption) on the data. The theory of sparse recovery (or sparse signal representation) mentions that  most natural signal can be represented as a linear combination of a small number of elementary waveforms (or atoms) chosen from a prede?ned dictionary matrix with their corresponding weights as given in equation below
(1)Where is the transform sparse coefficients vector that is computed as . The theory of compressive sensing as introduced by Candes  Tao and Romberg and Donoho demonstrates that a K-sparse signal in sparse basis matrix can be reconstructed from a fixed set of linear measurements. Consider an M×N measurement/ sensing basis matrix   where the rows of measurement matrix are incoherent with the columns of sparse basis matrix . The compressive measurement system computes the measurements as given below
(2)
where y represents an M × 1 measurement/sampled vector and x is the input signal vector which can be represented as . Generally  the measurement system actually performs dimensionality reduction. These measurements are able to completely capture the useful content embedded in a sparse signal. The expression for compressive measurement system can be rewritten as follows
(3)
where is an M×N matrix. The method and system provides secure coding and transmission or storage of the measurement data vector y obtained from input signal x.
[0025] Throughout the description the term compressive sensing  compressive sampling  compressive measurement  compressed sensing  compressed sampling is used interchangeably.
[0026] Throughout the description the term data security and data encryption/decryption is used interchangeably.
[0027] Throughout the description the term data and signal is used interchangeably.
[0028] Referring now to the drawings  and more particularly to FIGS. 1 through 7  where similar reference characters denote corresponding features consistently throughout the figures  there are shown preferred embodiments.
[0029] FIG. 1 illustrates general block diagram of a data communication and storage system 100  in accordance with various embodiments of the present invention. FIG. 1 includes electronic devices 101a  101b  and 101c  a compression and encryption data module 102  content storage devices 103  distributed storage servers 104a  104b  and 104c  a network 105  a decompression and decryption data module 106. The data communication and storage system 100 provides joint data compression and encryption  joint data decompression and decryption techniques  used by data security system for protection of data against unauthorized access. The compression and encryption data module 102 receives data from the electronic devices 101a and 101b.
[0030] In an embodiment  electronic devices can be mobile phones  tablets  laptops  personal digital assistant (PDA)  desktop computers  notebooks  wearable devices  and so on. The compression and encryption data module 102  on receiving data from the electronic devices 101a and 101b  performs signal processing such as compression  encryption  and data integrity on the received data. The system 100 provides mechanism to simultaneously perform compression and encryption data module 102 enables fast signal processing of data collected through sensors. This system meets real time constraints without substantially increasing computing resources and bandwidth requirement.
[0031] The data from compressed and the encrypted data module 102 can securely be transmitted over a communication network. This compressed and encrypted data can be stored on the content storage devices 103 and then can be transmitted to the distributed storage server 104a or can directly be transmitted to be stored on the distributed storage server 104a. Further  the encrypted and compressed data can be transmitted to any of the desired electronic devices such as 101c through a secured wired or wireless communication network 105 and/or a distributed storage server 104b. The data can also be transmitted through network 105 to the another distributed storage server 104c in the network. In an embodiment  communication networks such as mobile cellular networks  cable television networks  wireless networks  internet  cognitive radio networks  wireless sensor networks  satellite networks  Wi-Fi  wireless local loop (WLL)  WLAN  Bluetooth  Zigbee  global positioning system (GPS)  cloud computing  and so on.
[0032] FIG. 2 illustrates a multilevel dynamic joint data security and coding system using compressive sensing and sparse recovery techniques  in accordance with various embodiments of the present invention. The FIG. 2 shows a sensor interface 201  a secure compressive encoding system 200 including a secure compressive sampling system 202  a dynamic measurement scrambler 203  a quantizer 204  an encoder 205  a dynamic interleaver 206  a dynamic sensing matrix generator 207  and a random secret key’s generator 208. Further  the multilevel dynamic joint data security and coding system includes an encryption module 209  a multiplexer (MUX) 210  a transmission system 211  a wired or wireless channel 212  a receiving system 213  and a demultiplexer (De-Mux) 214. A secure compressive decoding system 215 includes a decryption module 216  a dynamic deinterleaver 217  a decoder 218  a dequantizer 219  a dynamic measurement descrambler 220  a sparse signal reconstruction module 221  a dynamic sensing matrix generator 222  a composite dictionary matrices module 223  and a signal reconstruction module 224.
[0033] The compressive sensing encoding system 200 determines data compression efficiency and ensures multilevel data security. The devices and techniques integrated with the compressive sensing encoding system 200 convert the input signal x into measurements. The sensor interface 201 senses signals which need to be secured and compressed. The input signal x can be single or multidimensional signal and can be either an analog or a digital signal. The input signal x from the sensor interface 201 will be processed in the secure compressive sampling system 202 using the scrambled compressive sensing matrix Fs generated by the dynamic sensing matrix generator 207 for randomly selected random secret key ag generated by the random secret key’s generator 208. This random secret key ag used by the scrambled compressive sensing matrix Fs provides first level of security dynamically. The analog compressive sensing device or digital compressive sensing device is used depending on the type of input signal x.
[0034] In an embodiment  the input signal x may be divided into predetermined segments and each segment may be processed according to techniques of compressive sensing method.
[0035] In an embodiment  a method for generating compressive sensing matrix can be generated by using Gaussian  Bernoulli  Walsh-Hadamard  Fourier basis  random basis  polynomial matrices  or any pseudo noise sequence generator. The method determines the number of measurements to be taken for an input signal by using information about signal to be processed at the secure compressive sensing encoding system 200.
[0036] In an embodiment  the method may adaptively increase or decrease the number of measurements based on the acceptable reconstructed signal or data quality by the user. In an embodiment  user can request the secure compressive encoder 200 about number of measurements to be taken. Thus  the secure compressive sampling system 202 processes input signal x and outputs an encrypted compressive measurement sequence signal y to the dynamic measurement scrambler 203. The dynamic measurement scrambler 203 uses the dynamic scrambling operations and the secret key am generated by the random secret key’s generator 208 to determine second level of security. Then  the compressive measurement signal y will be scrambled using dynamically selected one or more scrambling operations  in order to increase level data security. The scrambling operational sequence is obtained based on secret key am.
[0037] The output y of the dynamic measurement scrambler 203 is provided to the quantizer 204 for rounding the continuous set of measurement values with a finite precision set of values of quantization levels. The quantizer 204 represents the original signal with minimum loss or distortion when the quantized compressive measurements are used in the reconstruction.
[0038] In an embodiment  quantization technique can be a scalar midtread quantizer  midrise quantizer  non-uniform quantizer  adaptive quantizer  deadzone quantizer  vector quantizer  and so on. The method determines the number of quantization levels or quantization step size based on the compression efficiency and acceptable level of distortion in the reconstructed signal. The quantized output qs is provided to the encoder 205 where the encoding process converts input decimal value of quantized output into binary value. This encoded data be is forwarded to dynamic interleaver 206 that performs dynamic interleaving process using the standard interleaving techniques. The interleaving block processes the encoded data using one or more interleaving techniques that are implemented using one or more programs. The dynamic interleaver 206 uses secret key ai generated by the random secret key’s generator 208 for interleaving the received data be. The interleaving method provides a solution for reducing errors caused by bit errors in communication systems and provides third level of security. The method provides the encryption module 209 for encrypting all the secret keys generated by the random secret key’s generator 208. In an embodiment  the encryption techniques can be permutation  modulo-2 operation  that are used to encrypt the secret keys ag  ai  am. The method mixes the interleaved data bi and encrypted secret keys bk using the multiplexing techniques at the MUX 210  and these encrypted keys may be shared with authorized users when it is required.
[0039] Accordingly  the multiplexed data bk+bi is transmitted using the transmission system 211 through a wired or wireless communication channel 212 to a receiving system 213. The receiving system 213 receives the data bk+bi sent by the transmission system 211 and performs demultiplexing of the data using De-Mux 214 where received data of encrypted secret keys combined with the interleaved data bk+bi is separated. The encrypted keys bk are provided to the secure compressive decoding system’s 215 decryption module 216 for decrypting the secret keys ai  am  ai while interleaved data bi is provided to the dynamic deinterleaver module 217 for de-interleaving by using reverse interleaving mapping techniques with received secret key ai. The dynamic deinterleaver module 217 collects the transmitted decrypted random key ai  and then processes the interleaved data bi to obtain the original deinterleaved data as it was at the input of the dynamic interleaver 206. The deinterleaver uses the reverse interleaving-mapping rules of the interleaver to restore the original sequence of data. The method can include one or more programs and devices to perform deinterleaving process.
[0040] Further  this deinterleaved data bdi is provided to the decoder 218  which converts binary data into decimal data bd and forwards this data bd to the dequantizer 219 for performing de-quantization process on the decoded data to give dequantized data qd using reverse de-quantization rules. The method includes one or more programs and devices for performing de-quantization process on the decoded measurement vector. The de-quantization process uses the specifications of the quantization process that are used at the secure compressive sensing encoding system 200. The de-quantized data qd goes to the dynamic measurement descrambler 220 for descrambling the de-quantized measurements by using reverse dynamic scrambling operations with a received secret key am. The method provides a dynamic sensing matrix generator 222 to generate scrambled compressive sensing matrix Fs using the received secret key ag. The matrix Fs is provided to the sparse signal reconstruction module 221 such as to perform sparse signal representations by using L1-norm minimization algorithm or greedy algorithm. Further  the sparse signal reconstruction module 221 can estimate sparse coefficients for the descrambled compressive measurements data and predetermined transform basis matrix ? (or representation matrix or sparse basis matrix). This transform basis matrix ? is generated by composite dictionary matrices module 223. The estimated coefficient vector along with transform basis matrix ? is used by the reconstruction rules module 224 to reconstruct the original input signal x from the estimated sparse coefficients and the transform basis matrix ?.
[0041] In an embodiment  sparse basis matrix (or transform matrix) which may be constructed using the elementary atoms from dirac  Heaviside  Fourier  short-time Fourier transform  discrete cosines  discrete sines  Haar  wavelets  wavelet packets  Gabor filters  curvelets  ridgelets  contourlets  bandelets  shearlets  directionlets  grouplets  chirplets  Walsh Hadamard  polynomials  and so on. The method can also use prior information about characteristics of an input signal or pattern of input signal to be processed at the encoding system side. By using prior information  the method may construct sparse basis matrix such that the complexity of the solving sparse recovery problem can be reduced.
[0042] In an embodiment  the input data x can be reconstructed from the descrambled measurements by solving the convex optimization problem with the sparse basis matrix and the scrambled sensing basis matrix Fs. The sparse basis matrix is selected such that it contains elementary atoms exhibiting strong similarities with the input signal to be transmitted or stored. The scrambled sensing basis matrix is obtained using the random matrix generator and the preferred dynamic scrambling operations listed in the scrambling operation sequence key shared at the decoding stage. The method processes the measurement vector and the matrix A= Fs? which is an M×N matrix  and produces estimated sparse transform coefficient vector .
[0043] In an embodiment  the method provides reconstructing the input signal x by using the estimated sparse transform coefficients and the sparse basis matrix ?. For example  for a given input measurement vector y and the dictionary matrix A  transform coefficients are computed by solving the following minimization problem [Candes  Romberg  Tao; Donoho]:

where and represent the L1-norm and L2-norm of the vector  respectively  and ? is a regularization parameter that controls the relative importance of the fidelity and sparseness terms. Then  the input signal is recovered or reconstructed as .
[0044] In some implementations  some functional operations are described as a method for de-mixer which is used to separate the bk+bi when the encrypted secret keys are shared along with the input data  where bk represents encrypted keys  and bi represents the encoded encrypted measurement data. The binary data bi is then transferred to the dynamic deinterleaving section and the secret key data bk is transferred to the decryption section.
[0045] Some functional operations used in the preferred compressive sensing encoding system of the present invention are described below:
y= compressive_measurement(x  scrambled sensing matrix ) %generate measurements
s=scrambling_operation_sequence(secret_key); %generates random scrambling operations
ys=dynamic_scrambler(y s) %scrambling compressive measurements
qs=quantizer(ys step_size) %quantizing scrambled compressive measurements
be= encoder (qs) %converts decimal to binary numbers bi= dynamic_interleaver (be  secret_key) %interleaves the input data.
[0046] FIG. 3 illustrates a multilevel dynamic joint data security and coding system using compressive sensing and sparse recovery techniques and storing encrypted data  in accordance with various embodiments of the present invention. FIG. 3 shows a sensor interface 201  a secure compressive encoding system 200 including a secure compressive sampling system 202  a dynamic measurement scrambler 203  a quantizer 204  an encoder 205  a dynamic interleaver 206  a dynamic sensing matrix generator 207 and a random secret key’s generator 208. Further  the multilevel dynamic joint data security and coding system includes an encryption module 209  a multiplexer (MUX) 210 and a storage medium 300.
[0047] The compressive sensing encoding system 200 determines data compression efficiency and ensures multilevel data security. The devices and techniques integrated with the compressive sensing encoding system 200 convert the input signal x into measurements. The input signal x can be for example  a multidimensional signal  an analog  or a digital signal. The input signal x received from the sensor interface 201 can be processed in the secure compressive sampling system 202 using the scrambled compressive sensing matrix Fs generated by the dynamic sensing matrix generator 207. The secure compressive sampling system 202 use the randomly selected random secret key ag generated by the random secret key’s generator 208. This random secret key ag used by the scrambled compressive sensing matrix Fs provides first level of security dynamically. The analog compressive sensing device or digital compressive sensing device is used depending on the type of input signal x.
[0048] In an embodiment  the method may adaptively increase or decrease the number of measurements based on the acceptable reconstructed signal or data quality by the user. In an embodiment  user can request the secure compressive encoder about number of measurements to be taken. Thus  the secure compressive sampling system 202 processes the input signal x and outputs an encrypted compressive measurement sequence signal y to the dynamic measurement scrambler 203 where the dynamic scrambling operations and the secret key am generated by the random secret key’s generator 208 will determine second level of security. Then  the compressive measurement signal y will be scrambled using dynamically selected one or more scrambling operations  in order to increase level data security. The scrambling operational sequence is obtained based on secret key am.
[0049] The output y of the dynamic measurement scrambler 203 is provided to the quantizer 204 for rounding the continuous set of measurement values with a finite precision set of values of quantization levels. The quantizer 204 represents the original signal with minimum loss or distortion when the quantized compressive measurements are used in the reconstruction.
[0050] The method determines the number of quantization levels or quantization step size based on the compression efficiency and acceptable level of distortion in the reconstructed signal. The quantized output qs is provided to the encoder 205 where the encoding process converts input decimal value of quantized output into binary value. This encoded data be is forwarded to dynamic interleaver 206 that performs dynamic interleaving process using the standard interleaving techniques. The interleaving block processes the encoded data using one or more interleaving techniques that are implemented using one or more programs. The dynamic interleaver 206 uses secret key ai generated by the random secret key’s generator 208 for interleaving the received data be. The interleaving method provides a solution for reducing errors caused by bit errors in communication systems and provides third level of security. The method provides the encryption module 209 for encrypting all the secret keys generated by the random key’s generator 208. In an embodiment  the encryption techniques can be permutation  modulo-2 operation  that are used to encrypt the secret keys ag  ai  am. The method mixes the interleaved data bi and encrypted secret keys bk using the multiplexing techniques at the MUX 210  and these encrypted keys may be shared with authorized users when it is required. This multiplexed data bk+bi from the MUX 210 which is a compressive encrypted encoded data is securely stored on a storage medium 300 and can be retrieved later. The storage medium 300 can be a content storage 103  distributed storage server 104a  and the like. In an embodiment  this stored compressive encrypted encoded data can be later transmitted to any destination such as an electronic device 101c  or a distributed storage server 104c in the extended network and so on. The original input signal can be recovered using the secure compressive decoding system 215.
[0051] FIG. 4 illustrates a flow diagram explaining the process of compressive sensing encoding system  in accordance with various embodiments of the present invention. As depicted in figure 400  the secure compressive encoding system 200 receives (401) single or multidimensional input signal from the sensor interface 201. In an embodiment  the sensor interface 201 can be attached with electronic devices such as 101a and 101b or from a storage database system  cloud computing system  and so on. The received input signal can be an analog or a digital signal. On receiving the input signal the secure compressive sampling system 202 performs (402) compressive measurement process using either analog compressive sensing device or digital compressive sensing based on type of input signal. The scrambled compressive sensing matrix is used in the sensing process which provides compressed and encrypted data. The output data at the secure compressive sampling system 202 is further provided to the dynamic measurement scrambler 203  which applies (403) dynamic scrambling operations on encrypted compressive measurements where one or more scrambling operations are used in random manner as specified in the secret key generated by the random secret key’s generator 208. The scrambled  compressive measurements data is further forwarded to the quantizer 204 which applies (404) preset quantization process on the scrambled compressive measurements to get finite precision of data measurement values. The quantized data is provided to the encoder 205 which applies (405) encoding process on quantized data received from quantizer 204. For example  the lossless coding may applied by the encoder 205 for further compression. This encoded data is provided to the dynamic interleaver 205  which applies (205) interleaving process on encoded data received using dynamically selected predefined interleaving technique by using the secret key provided the random secret key’s generator 208. Further  the encryption module 209 applies (407) encryption process on all the secret keys used in the compressive sensing encoding process. The encoded signal data along with the encrypted keys is forwarded to the MUX 210 which applies (408) combining process for combining all the data that may include header information  secret keys  interleaved data  and other information using one or more transmission or storage protocols. This combined data is further transmitted using the transmission system 211 to reach the desired destination such as the distributed storage 104  the content storage devices 103  or any other electronic devices such as electronic the devices 101c. The various actions in the method 400 may be performed in the order presented  in a different order or simultaneously. Further  in some embodiments  some actions listed in the FIG. 4 may be omitted.
[0052] FIG. 5a  5b  5c  5d illustrates block diagrams of different scrambling operations performed  in accordance with various embodiments of the present invention. Various scrambling operations  which can be performed on data by the dynamic measurement scrambler 203 module in the secure compressive encoding system 200 are depicted in the FIG. 5. The blocking module of the FIG. 5a present in the dynamic measurement scrambler 203 receives the measurement sequence data vector y from the secure compressive sampling system 202. This data vector y will be scrambled based on the randomly selected scrambling operations for secret key am generated from the random secret key’s generator 208. If y is the measurement vector of size Mx1 for an N-dimensional input signal vector x then the structure of measurement vector y is shown below:
(5)
The output of the measurement reversal operator is given below
(6)
The block shuffling first divides the measurement vector y into non-overlapping blocks with variable size in the blocking module. The output of the block shuffling process is given below
  (7)
where represents block  and represents the number of blocks.
[0053] The number of blocks and the sizes for the blocks will be randomly generated using secret key am. For a selected number of blocks  the secret key for shuffling of blocks will be generated that provide positions for reordering the blocks. For example  the number of blocks is 5 and the sizes of blocks are {5  10  14  2  8}. For this specification  the total number of measurements is 39. Assume the secret key for block shuffling process is {3  1  4  5  2}. The input scrambled output structures of the block shuffling process are given below:
The input format: (8)
is provided to the block shuffling/rotation module and
The output format: (9)
is obtained at the output which can further be provided to the quantizer 204.
[0054] In an embodiment  various other scrambling operations can be performed such as random sign changing operation as in the FIG. 5b  permutation operation as in the FIG. 5c  arithmetic modulo operation as in the FIG. 5d using the secret key generated by the random secret key’s generator 208.
[0055] FIG. 6 illustrates a flow diagram 600 explaining the process of compressive decoding system  in accordance with various embodiments of the present invention. As depicted in figure 600  the secure compressive decoding system 215 receives (601) signal from the receiving system 213 or distributed storage system such as distributed storage servers 104b. The De-Mux 214 applies (602) the de-combining process for separating the encrypted secret key information and encoded data and if required can use the header information provided  according to transmission or storage protocols. This separated information related with encrypted keys is provided to the decryption module 216  which applies (603) decryption process on the encrypted secret keys by using information provided to the authorized users. The decrypted secret keys can be communicated to the corresponding processing units in the compressive sensing decoding system such as the dynamic interleaver 217  the dynamic measurement descrambler 220  and the dynamic sensing matrix 222.
[0056] The data corresponding to compressive measurement which was separated at the De-Mux 214 is provided to the dynamic interleaver 217  which applies (604) de-interleaving process on the received interleaved data by using the reverse techniques adopted in the interleaving process by the secure compressive encoding system 200. Further  the decoder 218 applies (605) decoding process on de-interleaved data which is then processed by the dequantizer 219  which applies (606) de-quantization process on decoded data by using the reverse techniques of the quantization process adopted by the quantizer 204 to produce de-quantized measurement values. To this dequantized compressive measurement data the dynamic measurement descrambler 220 applies (607) dynamic de-scrambling process by using the reverse techniques of the scrambling operations used by the dynamic measurement scrambler 203.
[0057] The descrambled data is further provided to the sparse signal reconstruction module 221  which applies (608) sparse recovery algorithms for estimating sparse coefficients using compressive sensing matrix Fs generated by dynamic sensing matrix 222 using secret key ag received and transform dictionary matrix ? that produces transform coefficient vector. The processed data is provided to the reconstruction rules module 224 that applies (609) reconstruction process to reproduce original form of input signal x by using estimated coefficients and transform dictionary matrix ?. The reconstructed signal is obtained as: . The various actions in method 600 may be performed in the order presented  in a different order or simultaneously. Further  in some embodiments  some actions listed in the FIG. 6 may be omitted.
[0058] FIG. 7 illustrates the performance of the compressive sensing based secured data processing system  in accordance with various embodiments of the present invention. The FIG. 7 depicts graphical representation of the input signal at output various blocks. The first graphical plot represents original speech signal to be processed. The second graphical plot represents measurements obtained using the secret key and scrambling sequence. The third graphical plot represents quantized measurements at the output of quantizer. The fourth graphical plot represents the reconstructed signal using the compressive sensing decoding system with shared secret keys. The fifth graphical plot represents error signal obtained between the original and reconstructed signals. The input speech signal is processed using the scrambled sensing matrix and then quantized the scrambled measurements. At the receiver section  the reverse operations of the compressive sampling encoder are applied to get the original measurements by using the received secret keys. Then  the input signal is reconstructed using the L1-optimization as described in the present invention. The reconstructed and error signals are plotted for visual tests. In this experiment  the parameters are: number of measurements=500  quantization bit=3  regularization parameter=0.1  the dictionary matrix has cosine basis functions). The experiment shows that the system can recover the input signal by using the random measurements and the L1-optimization minimization algorithm. Experimental studies on various signals and images prove system to be advantageous over existing systems. The error value shown has a very small deviation about zero which indicates a faithful reproduction of original signal at the output of compressive sensing decoder. Experimentation for performance check of the proposed method is validated using the electrocardiogram signal and speech signal.
[0059] The embodiments disclosed herein can be implemented through at least one software program running on at least one hardware device and performing network management functions to control the elements. The elements shown in the FIGS. 1  2  3  and 5 include blocks which can be at least one of a hardware device  or a combination of hardware device and software module.
[0060] The foregoing description of the specific embodiments will so fully reveal the general nature of the embodiments herein that others can  by applying current knowledge  readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept  and  therefore  such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore  while the embodiments herein have been described in terms of preferred embodiments  those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the embodiments as described herein.

STATEMENT OF CLAIMS
What is claimed is:
1. A method for multi-level dynamic joint data security and compression  wherein said method comprises:
receiving input signal from a sensor interface;
performing encryption on compressive measurement encoded data on said input signal;
transmitting said encrypted compressive measurement encoded data through a communication network;
performing decryption on compressive measurement decoded data after receiving said encrypted compressed measurement encoded data from said communication network; and
reproducing original signal from said decrypted compressive measurement decoded data.
2. The method of claim 1  wherein said method receives input signal from sensor interface  wherein said sensor interface are attached to at least one of electronic devices  storage database system  cloud computing system.
3. The method of claim 1  wherein said method further comprises storing said encrypted compressive measurement encoded data in a storage device.
4. The method of claim 3  wherein said method further comprises decrypting said encrypted compressive measurement encoded data from said storage device.
5. The method of claim 1  wherein said method transmits said encrypted compressive measurement encoded data through a communication network  wherein said communication network comprises at least one of wired  wireless channels.
6. The method of claim 5  wherein said method further comprises transmitting said encrypted compressive measurement encoded data through a communication network after encrypting secret keys generated by a random secret key’s generator.
7. A compressive encoding system for encoding input signal  wherein said compressive encoding system is configured for:
receiving said input signal from a sensor interface;
generating at least one secret key by a random secret key generator;
performing compressive measurement on said input signal by compressive sensing module;
applying dynamic scrambling on said compressive measurement signal using said at least one secret key by dynamic scrambling module;
applying quantization on said scrambled compressive measurement by quantizer;
applying encoding on said quantized compressive measurement by encoder;
applying interleaving on said encoded compressive measurement using said at least one secret key by dynamic interleaver; and
combining said interleaved encoded compressive measurement and encrypting secret keys generated by a random secret key’s generator.
8. The compressive encoding system of claim 7  wherein said compressive encoding system is configured for receiving input signal in at least one of analog and digital form from said sensor interface  wherein said sensor interface are attached to at least one of electronic devices  storage database system  cloud computing system.
9. The compressive encoding system of claim 7  wherein said compressive encoding system is configured for performing compressive measurement further comprises generating scrambled compressive sensing matrix using said at least one secret key for producing encrypted compressive measurements.
10. The compressive encoding system of claim 9  wherein said compressive encoding system further comprises performing scrambling operations selected in a random manner on said encrypted compressive measurements.
11. The compressive encoding system of claim 9  wherein said compressive encoding system further comprises adaptively controlling number of said compressive measurements based on quality of the reproduced signal at the compressive decoding system.
12. A transmission system for transmitting encrypted compressive measurement encoded data  wherein said transmission system is configured for:
receiving said encrypted compressive measurement encoded data from compressive encoding system; and
transmitting said encrypted compressive measurement encoded data to a receiving system.
13. The transmission system of claim 12  wherein said transmission system is configured for transmitting said encrypted compressive measurement encoded data through at least one of wired  wireless communication networks.
14. A storage system for storing encrypted compressive measurement encoded data  wherein said storing system is configured for:
storing said encrypted compressive measurement encoded data received from compressive encoding system.
15. A compressive decoding system for decoding encrypted compressive measurement encoded data from a communication network  wherein said compressive decoding system is configured for:
receiving said compressed encoded encrypted measurement data with at least one encrypted secret key from a receiving system;
decrypting said received at least one of encrypted secret key by decryption module;
applying deinterleaving on the received interleaved compressive measurement using said at least one decrypted secret key by a dynamic deinterleaver;
applying decoding on said deinterleaved compressive measurement by a decoder;
applying dequantization on said decoded compressive measurement by a dequantizer;
applying dynamic descrambling on said dequantized compressive measurement using said at least one decrypted secret key by a dynamic descrambler;
applying sparse recovery process on said descrambled compressive measurement by sparse signal reconstruction module; and
reproducing original form of said compressed encoded signal by a reconstruction rules module.
16. The compressive decoding system of claim 15  wherein said compressive decoding system receives said compressed encoded signal with at least one encrypted secret key  wherein said key further comprises decombining said encrypted secret key and said encoded compressive measurement from said receiving system.
17. The compressive decoding system of claim 15  wherein said compressive decoding system applies sparse signal reconstruction process on said descrambled compressive measurement further comprises using at least one of: dynamic sensing matrix generator and dictionary matrices module.
18. The compressive decoding system of claim 15  wherein said dynamic sensing matrix generator obtains at least one decrypted secret key from said decryption module.
19. The compressive decoding system of claim 15  wherein said sparse recovery process uses sparse basis matrix that is adaptively constructed based on prior information of at least one of characteristics of said input signal or patterns of said input signal.
20. A device for multi-level dynamic joint data security and compression  wherein said device configured with:
an integrated circuit further comprising at least one processor;
at least one memory having a computer program code within said circuit;
said at least one memory and said computer program code configured to with said at least one processor cause the device to:
receive input signal from a sensor interface;
perform encryption on compressive measurement encoded data on said input signal;
transmit said encrypted compressive measurement encoded data through a communication network;
perform decryption on compressive measurement decoded data after receiving said encrypted compressed measurement encoded data from said communication network; and
reproduce original signal from said decrypted compressive measurement decoded data.
21. The device of claim 20  wherein said device is configured to receive input signal from said sensor interface  wherein said sensor interface is attached to at least one of electronic device  storage database system  cloud computing system.
22. The device of claim 20  wherein said device is configured to store said encrypted compressive measurement encoded data in a storage device.
23. The device of claim 22  wherein said device is configured to decrypt said encrypted compressive measurement encoded data from said storage device.
24. The device of claim 20  wherein said device is configured to transmit said encrypted compressive measurement encoded data through a communication network  wherein said communication network comprises at least one of wired  wireless communication networks.
25. The device of claim 24  wherein said device is configured to transmit said encrypted compressive measurement encoded data through a communication network after encrypting secret keys generated by a random secret key’s generator.

Dated: 6th day of September  2012 Signature:
Dr. Kalyan Chakravarthy.
Patent Agent

ABSTRACT
Device and method for multi-level dynamic joint data security and compression are disclosed. The method includes receiving input signal from a sensor interface  performing encryption on compressive measurement encoded data on the input signal  transmitting the encrypted compressive measurement encoded data through a communication network  performing decryption on compressive measurement decoded data after receiving the encrypted compressed measurement encoded data from the communication network  and reproducing original signal from the decrypted compressive measurement decoded data.
FIG. 2