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Technical seminar report

  1. 1. VISVESVARAYA TECHNOLOGICALUNIVERSITYJnanaSangama, Belgaum-590014A Technical Seminar ReportOn“An Adaptive LSB-OPAPbased Secret Data Hiding”Submitted in Partial fulfillment of the requirements for VIII semesterBachelor of EngineeringinElectronics & Communication EngineeringbyTEJAS.S(1AR09EC043)Under the Guidance ofProf. PADMAJA VIJAYKUMARDept. of ECE, AIeMSDEPARTMENT OF ELECTRONICS AND COMMUNICATIONENGINEERINGAMRUTA INSTITUTE OF ENGINEERING &MANAGEMENT SCIENCESNear bidadi industrial Area, Bengaluru-562109
  2. 2. B.V.V.Sangha’sAMRUTA INSTITUTE OF ENGINEERING ANDMANAGEMENT SCIENCESNear Bidadi Industrial Area, Bengaluru– 562109DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERINGCERTIFICATEThis is to Certify that the technical seminar entitled “An Adaptive LSB-OPAP basedSecret Data Hiding”has been carried out byTEJAS.S (1AR09EC043), a bonafidestudent of Amruta institute of engineering & management sciences, in the partialfulfillment of the requirements for the award of the degree in Bachelor of Engineering inElectronics & Communication Engineering under Visvesvaraya TechnologicalUniversity, Belgaum during the academic year 2012-2013. It is certified that allcorrections/suggestions indicated for Internal Assessment have been incorporated in thereport deposited in the department library.Prof. PADMAJA VIJAYKUMAR Prof. C.R RAJAGOPALDept of ECE, AIeMS HOD of ECE, AIeMSName of the Examiners: Signature and Date1.2.
  3. 3. ACKNOWLEDGEMENTThe satisfaction and euphoria that accompany the successful completion of any taskwould be incomplete without the mention of the people who made it possible, whose constantguidance and encouragement crowned my effort with success.I am grateful to our institution, Amruta Institute of Engineering &managementSciences (AIeMS) with its ideals and inspirations for having provided me with thefacilities, which made this, seminar a success.I earnestly thank Dr. A. PRABHAKAR, Principal, AIeMS, for facilitating academicexcellence in the college and providing me with congenial environment to work in, thathelped me in completing this seminar.I wish to extend my profound thanks to Prof. C.R.RAJAGOPAL, Head of theDepartment, Electronics & Communication Engineering, AIeMS for giving me theconsent to carry out this seminar.I would like to express my sincere thanks to our Internal Guide Prof. PADMAJAVIJAYKUMAR, Department of Electronics & Communication Engineering, AIeMS forher able guidance and valuable advice at every stage of my seminar, which helped me in thesuccessful completion of the seminar.I wish to express my solicit thanks to my friend Mr. RAGHU.K for his help andsupport to my seminar.I am thankful to all the faculty members and non-teaching staff of the department fortheir kind co-operation.I also wish to thank my friends for their useful guidance on various topics. Last butnot the least, I would like to thank my parents and almighty for the support.TEJAS.S(1AR09EC043)
  4. 4. ABSTRACTIn the present digital world, Steganography and cryptography are excellent means bywhich secret communication can be achieved significantly over the data network. Theclassical methods of steganography such as LSB substitution involve hiding the data in amultimedia carrier. The present research activities are focused on embedding the data andsimultaneously achieving good PSNR and efficient payload. An adaptive method for LSBsubstitution with private stego-key based on gray-level ranges is proposed. This newtechnique embeds binary secret data in 24-bits colour image or in 8-bits gray-scale image. Inthis method the cover image pixels are grouped into 4 ranges based on their intensity levels.Different ranks are allotted to each of the range so that the range having highest number ofpixel count gets the highest rank and the pixels under this range are embedded withmaximum of 4 bits of secret data. The pixel after embedding may or may not be within thesame range, hence this algorithm proposes an optimum pixel adjustment process (OPAP).The method also verifies that whether the attacker has tried to modify the secret datahidden inside the cover image. Besides, the embedded confidential information can beextracted from stego-images without the assistance of original image. This method provides acapacity of 3.5 bits/pixel and a PSNR of 52 dB on an average.
  5. 5. LIST OF FIGURESpageFig 1.1 Classification of Steganography 1Fig 2.1 Method for k- bits insertion 6Fig 3.1 LSB – OPAP 7Fig 4.1 Message embedding with signature 10Fig 4.2 Message extraction and integrity check 11Fig 6.1 Experimental result using Range1 for Baboon cover image 14Fig 6.2 Experimental result using Range2 for Lena cover image 15
  6. 6. TABLE OF CONTENTSPage1. Introduction to Steganography 12. An Adaptive LSB-OPAP employed pixel domain stegotechnique(ALOS) 42.1 Proposed Methodology2.2 Private stego-key generation2.3 Method to decide Bits insertion in each range2.4 LSB substitution3. Optimum Pixel Adjustment Process (OPAP) 74. Implementation of ALOS 94.1 Algorithms: Embedding4.2 Algorithms: Extracting5.Advantages& Applications of proposed system 125.1 Advantages5.2 Limitations5.3 Applications6. Experimental results and discussions 13References
  7. 7. CHAPTER 1INTRODUCTION TO STEGANOGRAPHYSteganography is derived from the Greek for covered writing and essentially means“to hide in plain sight”. Steganography is the art and science of communicating in such a waythat the presence of a message cannot be detected. Simple steganographic techniques havebeen in use for hundreds of years, but with the increasing use of files in an electronic formatnew techniques for information hiding have become possible.Figure1.1 shows how information hiding can be broken down into different areas.Steganography can be used to hide a message intended for later retrieval by a specificindividual or group. In this case the aim is to prevent the message being detected by any otherparty.Figure1.1 Classification of SteganographySteganography and encryption are both used to ensure data confidentiality. Howeverthe main difference between them is that with encryption anybody can see that both partiesare communicating in secret. Steganography hides the existence of a secret message and inthe best case nobody can see that both parties are communicating in secret. This makessteganography suitable for some a task for which encryption isn’t, such as copyright marking.
  8. 8. Adding encrypted copyright information to a file could be easy to remove butembedding it within the contents of the file itself can prevent it being easily identified andremoved.Steganography provides a means of secret communication which cannot be removedwithout significantly altering the data in which it is embedded. The embedded data will beconfidential unless an attacker can find a way to detect it.Steganography or Stego as it is often referred to in the IT community, literally means,"Covered writing" which is derived from the Greek language. Steganography is defined asfollows, "Steganography is the art and science of communicating in a way which hides theexistence of the communication. In contrast to Cryptography, where the enemy is allowed todetect, intercept and modify messages without being able to violate certain security premisesguaranteed by a cryptosystem, the goal of Steganography is to hide messages inside otherharmless messages in a way that does not allow any enemy to even detect that there is asecond message present".In a digital world, Steganography and Cryptography are both intended to protectinformation from unwanted parties. Both Steganography and Cryptography are excellentmeans by which to accomplish this but neither technology alone is perfect and both can bebroken. It is for this reason that most experts would suggest using both to add multiple layersof security.Steganography can be used in a large amount of data formats in the digital world oftoday. The most popular data formats used are .bmp, .doc, .gif, .jpeg, .mp3, .txt and .wav.Mainly because of their popularity on the Internet and the ease of use of the steganographictools that use these data formats. These formats are also popular because of the relative easeby which redundant or noisy data can be removed from them and replaced with a hiddenmessage. Steganographic technologies are a very important part of the future of Internetsecurity and privacy on open systems such as the Internet. Steganographic research isprimarily driven by the lack of strength in the cryptographic systems on their own and thedesire to have complete secrecy in an open-systems environment. Many governments havecreated laws that either limit the strength of cryptosystems or prohibit them completely. Civilliberties advocates fight this with the argument that “these limitations are an assault onprivacy”. This is where Steganography comes in. Steganography can be used to hide
  9. 9. important data inside another file so that only the parties intended to get the message evenknows a secret message exists. To add multiple layers of security and to help subside the"crypto versus law" problems previously mentioned, it is a good practice to use Cryptographyand Steganography together. As mentioned earlier, neither Cryptography nor Steganographyare considered "turnkey solutions" to open systems privacy, but using both technologiestogether can provide a very acceptable amount of privacy for anyone connecting to andcommunicating over these systems.CHAPTER 2
  10. 10. AN ADAPTIVE LSB-OPAP EMPLOYED PIXELDOMAIN STEGO TECHNIQUE (ALOS)To enhance the embedding capacity of image steganography and provideanimperceptible stego-image for human vision, a novel adaptive number of leastsignificantbits substitution method with private stego-key based on color imageranges are proposed inthis methodology. The new technique embeds binary bit streamin each 8 bit pixel value. Themethodalso verifies that whether the attacker has tried to modify the secret hidden (orstego-image also) information in the stego-image. The technique embeds thehidden information inthe spatial domain of the cover image and uses simple (Ex-OR operation based) digitalsignature using 140-bit key to verify the integrity fromthe stego-image. Besides, theembedded confidential information can beextracted from stego-images without the assistanceof original images.2.1 Proposed MethodologyThe proposed scheme works on the spatial domain of the cover image and employedan adaptivenumber of least significant bits substitution in pixels. Variable K-bits insertioninto least significantpart of the pixel gray value is dependent on the private stego-key K1.Private stego-key consistsof four gray-level ranges that are selected randomly in the range 0-255. The selected key showsthe four ranges of gray levels and each range substitute differentfixed number of bits into leastsignificant part of the 8-bit gray value of the pixels. Aftermaking a decision of bits insertion into different ranges, Pixel p(x, y) gray value “g” that fallwithin the range Ai-Bi is changed by embedding k-message bits of secret information intonew gray value “g’ ”. This new gray value “g’ ”of the pixel may go beyond the range Ai-Bithat makes problem to extract the correct information at the receiver. Specific gray valueadjustmentmethod is used that make the new gray value “g’ ” fall within the range Ai-Bi.Confidentiality isprovided by the private stego-key k1 and to provide integrity of theembedded secret information,140-bit another key K2 is used. Digital signature of the secretinformation with the key K2 wereobtained and appended with the information. The wholemessage plus signature is embeddedinto the cover image that provides some bit overheadsbut used to verify the integrity. At thereceiver key K1 is used to extract the message and keyK2 is used to verify the integrity of themessage.
  11. 11. 2.2 Private stego-key generationPrivate stego-key K1 play an important role in proposed methodology to providesecurity and deciding the adaptive K bits insertion into selected pixel. For a gray scale image8-bit is used to represent intensity of pixel, so there are only 256 different gray values anypixel may hold. Different pixels in image may hold different gray values. We may divide thepixels of images into different groups based on gray ranges. Based on this assumption let fourranges ofray levels are < A1-B1, A2-B2, A3-B3, A4-B4 > each range starting and endingvalue are in8-bits.2.3 Method to decide Bits insertion in each rangeLet the four gray ranges decided by the stego-key are <A1-B1, A2-B2, A3-B3, A4-B4> andnumber of pixel count from cover image in each range are < N1, N2, N3, N4 >.Range withmaximum pixel count will hold maximum bits insertion let four bits, secondmaximum count willhold three bits insertion and so on. In similar way we decide the bitsextraction from each range. ForExample assume key K1 is 0-64, 65-127, 128-191, 192-255and let pixel count in eachrange from any image are 34,13238,17116, 35148. Then range firstinsert one message bits in thepixel that comes within the range, range second insert twomessage bits in the pixel,range thirdinsert three bit in the pixel ,range four insert four bits inthe pixel. In this manner we decide the bits insertion into eachrange.2.4 LSB substitutionLeast significant substitution is an attractive and simple method to embed secretinformation intothe cover media and available several versions of it. We employ in proposescheme adaptive LSBsubstitution method in which adaptive K-bits of secret messagearesubstituted into leastsignificant part of pixel value. Fig.2 shows entire method for K-bitsinsertion.g original value K- zero bits K- msg bitsModify value g’
  12. 12. Fig 2: method for k- bits insertionTo decide arbitrary k-bits insertion into pixel, first we find the range of pixel value and thenfindthe number of bits insertion decided by method given in section 2.3 and insert K-messagebitsinto least significant part of pixel using LSB. After embedding the message bits thechanged grayvalue g’ of pixel may go beyond the range.CHAPTER 3Pixelvalue in8 - bitsAND ORValue in 8 -bitsK-LSB’s
  13. 13. THE LSB BASED OPTIMUM PIXEL ADJUSTMENTPROCESS (OPAP)The Least significant substitution is a simple method to embed secret information intothe cover media. We employ in propose scheme adaptive LSBsubstitution method in whichadaptive K-bits of secret message are substituted into leastsignificant part of pixel value. Todecide arbitrary k-bits insertion into pixel, first we find the range of pixel value and thenfindthe number of bits insertion decided by method given in section 2 and insert K-messagebitsinto least significant part of pixel using LSB.Figure 3.1 shows the whole process.Fig 3.1 LSB - OPAPAfter embedding the message bits the changed grayvalue g’ of pixel may go beyondthe range. To make value within the range, reason is thatreceiver side required to count pixelsto extract message, pixel value adjusting method is appliedto make changed value withinrange called as Optimum Pixel Adjustment Process.After embedding the K-message bits into the pixel gray value g new gray vale g’ maygo outside the range. For example let our range based on key is 0-32. Let the gray value g ofthe pixel is 00100000 in binary forms (32 in Decimal), decided K-bits insertion is 3-bits areK = K+1
  14. 14. 111. The pixel new gray value g’ will be 00100111 in binary forms after inserting three bits(39 in Decimal).Modified value is outside the range. To make within the range 0-32, K+1 bits of g’ ischanged from 0 to 1 or via- versa and checked again to fall within range if not K+2 bit ischanged and so on until gray value fall within range. For example: 00100111- 00101111-00111111- 00011111.
  15. 15. CHAPTER 4IMPLEMENTATION OF ALOS: FLOW DIAGRAMAND ALGORITHMThe algorithms used to implement Adaptive LSB-OPAP stego technique is describedas below:4.1 Algorithms: EmbeddingInput: Cover-image, secret message, keys K1, K2.Output: Stego-image.Step1: Read key K1 based on gray-Level ranges.Step2: Read cover imageStep3: Decide No. of bits insertion into each range described in section 2.3Step4: Read the secret message and Convert it into bit stream form.Step5: Read the key K2.Step6: Find the signature using K2 and append with the message bits.Step7: For each Pixel7.1: Find gray value g.7.2: Decide the K-bits insertion based on gray ranges.7.3: Find K-message bits and insert using method given in section 2.47.4: Decide and adjust new gray Value g’ using method described in Optimum pixeladjustment process.7.5: Go to step 7.Step 8: endThe secret message is first converted into binary bit stream and its digital signature iscalculated using xor structure with the help of key-2 (140 bits), this signature is thenappended into the message and then embedding is done based on LSB substitution method bykey-1, on a cover image in spatial domain. The stego image is then transmitted through thechannel to the authorized receiver side, where the secret data embedded can be extractedusing the shared key.Figure 4.1 and 4.2 shows the flow diagram for secret message embedding andextraction along with digital signature respectively.
  16. 16. Fig 4.1 Message embedding with signature
  17. 17. 4.2 Algorithm: ExtractingInput: Stego-image, keys K1, K2;Output: Secret information;Step1: Read key K1 based on gray-level ranges.Step2: Read the stego image.Step3: Decide No. of bits extraction into each range described in section 2.3.Step4: For each pixel, extract the K-bits and save into file.Step5: Read the key K2 and find the signature of bit streamStep6: Match the signature.Step7: EndFig 4.2 Message extractionand integrity check
  18. 18. CHAPTER 5ADVANTAGES & APPLICATIONS OF PROPOSEDSYSTEM5.1 Advantages High hiding capacity compared to LSB Substitution technique. Robust in nature, i.e., highly secure algorithm since two keys (key-1 and key-2) areused. We get good quality of the stegoimage. High water marking level. Provides maximum possible payload. Embedded data is imperceptible to the observer.5.2 Limitations High computational complexity. Requires a lot of overhead to hide a relatively bits of information.This can be overcome by using HIGH SPEED COMPUTERS.5.3 Applications In secret communication system. Military applications. Hiding and protecting of secret data in industry. Airlines.
  19. 19. CHAPTER 6EXPERIMENTAL RESULTS AND DISCUSSIONSIn this implementation, Lena and baboon 256 × 256 × 3 colourdigital images havebeen taken as coverimages and are tested for various ranges along with different size of secretmessages chosen. The effectiveness of thestego process has been studied by calculatingPSNR for the two digital images in RGB planesand tabulated. First analysis is used to selectthe Range for embedding data (in this analysis Range1 is 0-64, 65-127, 128-191, 192-255)and the results are tabulated in Table-12.3 for various Ranges. From the table we willunderstand that Range2 for cover image baboon provides high Payload and Range1 for coverimage baboon provides low payload.RangeCoverimageMax bits that can beembedded (payload)No of bits embeddedCapacity(bits/pixel)PSNRRange1Lena 65314951360 3.2016 44.94124768 3.141 55.5705115360 3.2268 40.8688Baboon 60952451360 3.2927 44.76684768 3.2 54.8287115360 3.0352 41.7503Range2Lena 69370051360 3.624 43.4944768 3.7338 53.4812115360 3.6078 40.3313Baboon 70008751360 3.6488 43.24794768 3.7192 53.6941115360 3.5019 40.2084Table 6.1 Tabulated result for ALOS technique for secret image
  20. 20. Figure 6.1 Experimental result using Range1 for Baboon cover imageThe above figure 6.1 shows the input cover image and output stego image and theirrespective histograms. The above results are obtained for using Range1. The maximumpayload obtained is 609524 bits, on an average of 3.0352 bits per pixel with the PSNR of41.7503.The input cover image0200400600The histogram of input cover image0 100 200The output stego image0200400600800The histogram of stego image0 100 200
  21. 21. Figure 6.2 Experimental result using Range2 for Lena cover imageThe above figure 6.2 shows the input cover image and output stego image and theirrespective histograms. The above results are obtained for using Range2. The maximumpayload obtained is 31975 bits, on an average of 3.6078 bits per pixel with the PSNR of40.3313.The input cover image0200400600800The histogram of input cover image0 100 200The output stego image05001000The histogram of stego image0 100 200
  22. 22. CONCLUSIONThis novel image steganographic model results in high-capacity embedding/extractingcharacteristic based on the Variable-Size LSB substitution. In the embedding part based onstego-key selected from the gray value range 0-255, it uses pixel value adjusting method tominimize the embedding error and adaptive 1-4 bits to embed in the pixel to maximizeaverage capacity per pixel. Using the proposed method, it can be shown that atleastfourmessage bits in each pixel can be emebbed, while maintaining the imperceptibility. For thesecurity requirement, two different ways are proposed to deal with the issue. The majorbenefit of supporting these two ways is that the sender can use different stego-keys indifferent sessions to increase difficultly of steganalysis on these stego images. Using only thestego-keys, which is used to count the number of pixel in each range and second 140-bit keyto verify the integrity of the message, the receiver can extract the embedded messagesexactly. Experimental resultsverify that the proposed model is effective and efficient.REFERENCES
  23. 23. 1. Yogendra Kumar Jain, R.R. Ahirwal, “ A Novel Image Steganography Method withAdaptive number of Least Significant Bits Modification Based on Private Stego-Keys”, IJCSS, vol. 4, Issue 1.2. F. A. P. Petitcolas, R. J. Anderson, M. G. Kuhn, “Information Hiding - A Survey”,Proceeding of the IEEE, vol. 87, issue 7, pp. 1062-1078, July 1999.3. S. Dumitrescu, W. X. Wu and N. Memon, “On steganalysis of random LSBembedding in continuous-tone images”, Proceeding of International conference onimage Processing,Rochester, NY, pp. 641-644, 2002.4. B. Mehboob and R. A. Faruqui, “A steganography Implementation”, IEEE –International symposium on biometrics & security technologies, ISBAST’08,Islamabad, April 2008.5. A. Cheddad, J. Condell, K. Curran and P. McKevitt, “Enhancing Steganography indigitalimages”, IEEE - 2008 Canadian conference on computer and Robot vision,pp. 326-332,2008.6. Ko-Chin Chang, Chien-Ping Chang, Ping S. Huang, and Te-mingTu, “A novelimage steganographic method using Tri-way pixel value Differencing”, Journal ofmultimedia,vol. 3, issue 2, June 2008.7. K. S. Babu, K. B. Raja, K. Kiran Kumar, T. H. Manjula Devi, K. R. Venugopal, L.M.Pataki, “Authentication of secret information in image steganography”, IEEERegion 10 Conference, TENCON-2008, pp. 1-6, Nov. 2008.8. S. K. Moon and R.S. Kawitkar, “Data Security using Data Hiding”, IEEEInternational conference on computational intelligence and multimedia applications,vol. 4, pp. 247251, Dec2007.

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