Journal articles: 'Least significant bit matching'

1

Tseng, Hsien-Wen, and Hui-Shih Leng. "A reversible modified least significant bit (LSB) matching revisited method." Signal Processing: Image Communication 101 (February 2022): 116556. http://dx.doi.org/10.1016/j.image.2021.116556.

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Xia, Zhihua, Xinhui Wang, Xingming Sun, and Baowei Wang. "Steganalysis of least significant bit matching using multi-order differences." Security and Communication Networks 7, no. 8 (2013): 1283–91. http://dx.doi.org/10.1002/sec.864.

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Pristiwanto, Pristiwanto, and Abdul Halim Hasugian. "Steganography Formation by utilizing Enhanced Least Significant Bit Algorithm." Jurnal Info Sains : Informatika dan Sains 11, no. 1 (2021): 19–22. http://dx.doi.org/10.54209/infosains.v11i1.38.

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Steganography is the science and art of hiding secret messages in other messages so that the existence of those messages cannot be known. The letter sent does not attract attention with steganography, and the container media does not arouse suspicion. Steganography requires two properties, namely container media and secret messages. The LSB method (least significant bit)is the simplest and easiest steganography method to implement. An example of implementing this method is to use a digital image as a cover text. Each pixel in the image is 1 (one) to 3 (three) bytes in size. Pda bit arrangement in a byte ( 1 byte = 8 bits), there are the most significant bits ( MSB) and the least significant bits (LSB). For example, on 11010010 bytes, the first bit from the right is the MSB bit, and the last bit from the right is the LSB bit. The matching bit is replaced with the message bit is the LSB bit, because the modification only changes the byte value to one higher or one lower than the previous value

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Akhrameeva, K. A., and E. U. Gerling. "COMPARATIVE ANALYSIS OF STEGOSYSTEMS WITH EMBEDDING IN THE LEAST SIGNIFICANT BITS WITH MATCHING AND SUBSTITUTION." H&ES Research 12, no. 6 (2020): 38–47. http://dx.doi.org/10.36724/2409-5419-2020-12-6-38-47.

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The work presents the results of a comparative analysis of stegosystems with algorithms for embedding in the least significant bit with matching and substitution for differences in the procedure for embedding additional information in the covering object and the resistance of the obtained steganograms to various methods of steganalysis. When using stegosystems with embedding algorithms in the least significant bit with matching and substitution, samples of steganograms with different embedding fractions were obtained for a sample of 200 covering objects. The results of the steganogram analysis on the steganogram data were analyzed, the obtained steganogram samples were compared to the detection of the presence of an additional information attachment using three steganalysis methods: visual attack, first-order statistical attack (chi-square attack) and second-order statistical attack (pairwise selective analysis attack). The presented example of images before and after a visual attack, for samples steganograms with attachments in the least significant bit with substitution and matching, with an investment fraction of 10%, 50% and 100%, allows to demonstrate the performance of the visual method steganalysis. The graphical representation of the results for first-and second-order attacks allows us to evaluate the effectiveness of the studied methods of stegoanalysis for stegosystems with algorithms for embedding in the least significant bit with matching and substitution. It is shown that a stegosystem with an algorithm for embedding in the least significant bits with matching is more resistant to detection attacks using modern methods of stegoanalysis. Conclusions are made about the possibility of applying the considered methods of stegoanalysis to the presented methods of stegosystems

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Li, Wenxiang, Tao Zhang, Ran Wang, and Yan Zhang. "Quantitative steganalysis of least significant bit matching revisited for consecutive pixels." Journal of Electronic Imaging 23, no. 1 (2014): 013025. http://dx.doi.org/10.1117/1.jei.23.1.013025.

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Khalid, Kadhim Jabbar, Bahir Tuieb Munthir, and A. Thajeel Salam. "Digital watermarking by utilizing the properties of selforganization map based on least significant bit and most significant bit." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 6 (2022): 6545–58. https://doi.org/10.11591/ijece.v12i6.pp6545-6558.

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Information security is one of the most important branches concerned with maintaining the confidentiality and reliability of data and the medium for which it is transmitted. Digital watermarking is one of the common techniques in this field and it is developing greatly and rapidly due to the great importance it represents in the field of reliability and security. Most modern watermarking systems, however, use the self-organization map (SOM), which is safer than other algorithms because an unauthorized user cannot see the result of the SOM's training. Our method presents a semi-fragile watermark under spatial domain using least significant bit (LSB) and by relying on most significant bit (MSB) when the taken values equal to (2 or 4 bits) depending on the characteristics of SOM through developing the so-called best matching unit (BMU) which working to determine the best location for concealment. As a result, it shows us the ability of the proposed method to maintain the quality of the host with the ability to retrieve data, whether it is a binary image or a secret message.

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Xiong, Gang, Xi-jian Ping, Tao Zhang, and Bing Sun. "An Approach of Detecting Least Significant Bit Matching Based on Image Content." Journal of Electronics & Information Technology 34, no. 6 (2012): 1380–87. http://dx.doi.org/10.3724/sp.j.1146.2011.00932.

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Xia, Zhihua, Shufang Wang, Xingming Sun, and Baowei Wang. "Steganalysis of least significant bit matching based on image histogram and correlation." Journal of Electronic Imaging 22, no. 3 (2013): 033008. http://dx.doi.org/10.1117/1.jei.22.3.033008.

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Afrakhteh, Masoud, and Jeong-A. Lee. "Adaptive least significant bit matching revisited with the help of error images." Security and Communication Networks 8, no. 3 (2014): 510–15. http://dx.doi.org/10.1002/sec.998.

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Turkhamun Adi Kurniawan and Wahyudi Syahputra. "IMPLEMENTASI ALGORITMA LEAST SIGNIFICANT BIT MACHING UNTUK MENGAMANKAN DATA RAHASIA PERUSAHAAN." JURNAL LIMITS 18, no. 01 (2023): 1–7. http://dx.doi.org/10.59134/jlmt.v18i01.200.

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Keamanan data merupakan hal yang sangat penting,dimana dibutuhkan sebuah keamanan dalam transaksi data secara online terutama pada surat- surat penting perusahaan yang hanya diperuntukan untuk internalperusahaan, bukan untuk publik. Pertukaran data dapat dilakukan dengan mudah dan cepat sehingga menjadi sangat rentan terhadap penyalahgunaan dari pihak yang tidak berwenang, dengan ini maka dibutuhkan suatu solusi untuk mengamankan surat-surat penting perusahaan. Keamanan tersebut berupa aplikasi dengan Metodesteganografi menggunakan Least Significant Bit Matching (LSBM) sehingga dapat digunakan untuk mengamankan surat- surat penting perusahaan. Pengguna juga dapat meng encrypt dan decrypt

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Liu, Qingzhong, Andrew H. Sung, Bernardete Ribeiro, Mingzhen Wei, Zhongxue Chen, and Jianyun Xu. "Image complexity and feature mining for steganalysis of least significant bit matching steganography." Information Sciences 178, no. 1 (2008): 21–36. http://dx.doi.org/10.1016/j.ins.2007.08.007.

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Kadhim Jabbar, Khalid, Munthir Bahir Tuieb, and Salam A. Thajeel. "Digital watermarking by utilizing the properties of self-organization map based on least significant bit and most significant bit." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 6 (2022): 6545. http://dx.doi.org/10.11591/ijece.v12i6.pp6545-6558.

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Information security is one of the most important branches concerned with maintaining the confidentiality and reliability of data and the medium for which it is transmitted. Digital watermarking is one of the common techniques in this field and it is developing greatly and rapidly due to the great importance it represents in the field of reliability and security. Most modern watermarking systems, however, use the self-organization map (SOM), which is safer than other algorithms because an unauthorized user cannot see the result of the SOM's training. Our method presents a semi-fragile watermark under spatial domain using least significant bit (LSB) and by relying on most significant bit (MSB) when the taken values equal to (2 or 4 bits) depending on the characteristics of SOM through developing the so-called best matching unit (BMU) which working to determine the best location for concealment. As a result, it shows us the ability of the proposed method to maintain the quality of the host with the ability to retrieve data, whether it is a binary image or a secret message.

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13

Youssef, Taouil, and Bachir Ameur El. "Steganographic Scheme Based on Message-Cover matching." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 5 (2018): 3594–603. https://doi.org/10.11591/ijece.v8i5.pp3594-3603.

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Steganography is one of the techniques that enter into the field of information security, it is the art of dissimulating data into digital files in an imperceptible way that does not arise the suspicion. In this paper, a steganographic method based on the Faber-Schauder discrete wavelet transform is proposed. The embedding of the secret data is performed in Least Significant Bit (LSB) of the integer part of the wavelet coefficients. The secret message is decomposed into pairs of bits, then each pair is transformed into another based on a permutation that allows to obtain the most matches possible between the message and the LSB of the coefficients. To assess the performance of the proposed method, experiments were carried out on a large set of images, and a comparison to prior works is accomplished. Results show a good level of imperceptibility and a good trade-off imperceptibility-capacity compared to literature.

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Saravanan, D., N. Sivaprasad, and Dennis Joseph. "Information Trouncing Via Slightest Momentous Spot System Procedure." International Journal of Engineering & Technology 7, no. 3.27 (2018): 488. http://dx.doi.org/10.14419/ijet.v7i3.27.18002.

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The least-significant-bit based approach is a popular type of stenographic algorithms in the spatial domain. However, we find that in most existing approaches, the choice of embedding positions within a cover audio mainly depends on a pseudorandom number generator without considering the relationship between the audio content itself and the size of the secret message. In this paper, we expand the least significant bit matching revisited audio stegnography and propose an edge adaptive scheme which can select the embedding regions according to the size of secret message and the difference between two consecutive pixels in the cover audio. For lower embedding rates, only sharper edge regions are used while keeping the other smoother regions as they are. When the embedding rate increases, more edge regions can be released adaptively for data hiding by adjusting just a few parameters. New scheme can enhance the security significantly compared with typical least significant bit-based approaches as well as their edge adaptive ones, such as pixel-value-differencing-based approaches, while preserving higher visual quality of stegno audios at the same time.

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S.Azhagu, Senthil. "IMAGE STEGANOGRAPHY BASED ON LSB MATCHING TECHNIQUE USING SECRET SHARING METHOD." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES 6, no. 4 (2019): 312–15. https://doi.org/10.5281/zenodo.2653584.

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Least significant bit (LSB) method is a well-known steganographic algorithm in the spatial domain. LSB drops the visual quality of the image and leads to poor security. To overcome this issue the least significant bit matching revisited steganography was expanded and developed an edge adaptive image steganography. To provide more security for this scheme, this paper provides a combined scheme with (u, v) secret image sharing algorithm. With the additional facility of steganography with authentication and proposes a new algorithm in this paper, which is more secure compared to the previous scheme. This scheme provides four level of security.1) The message is hidden into an image using two keys rotation key (key 1) and the travelling order (key 2) of the algorithm. 2) The (u, v) – threshold function is applied for a batch of n members to share the secret image. Any u or more of v shares can only reconstruct the image consisting of the message. 3) Then the embedding scheme is used to embed each share into camouflage images. 4) The authentication is also provided by the proposed scheme. Thus the scheme is more appropriate for the application where high security and efficiency are mandatory and it can also handle color images with slight modifications.

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Raja, P. M. Siva, and E. Baburaj. "Secret Data Hiding Scheme with Least Significant Bit Matching Revisited Image Steganography based on Novel E-Coli Bacterial Foraging Optimization Model." Asian Journal of Research in Social Sciences and Humanities 6, no. 7 (2016): 807. http://dx.doi.org/10.5958/2249-7315.2016.00465.2.

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17

Taouil, Youssef, and El Bachir Ameur. "Steganographic Scheme based on Message-Cover matching." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 5 (2018): 3594. http://dx.doi.org/10.11591/ijece.v8i5.pp3594-3603.

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Steganography is one of the techniques that enter into the field of information security, it is the art of dissimulating data into digital files in an imperceptible way that does not arise the suspicion. In this paper, a steganographic method based on the Faber-Schauder discrete wavelet transform is proposed. The embedding of the secret data is performed in Least Significant Bit (LSB) of the integer part of the wavelet coefficients. The secret message is decomposed into pairs of bits, then each pair is transformed into another pair based on a permutation that allows to obtain the most matches possible between the message and the LSB of the coefficients. To assess the performance of the proposed method, experiments were carried out on a large set of images, and a comparison to prior works is accomplished. Results show a good level of imperceptibility and a good trade-off imperceptibility-capacity compared to literature.

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Wan, Peiyuan, Limei Su, Hongda Zhang, and Zhijie Chen. "A Power-Efficient Pipelined ADC with an Inherent Linear 1-Bit Flip-Around DAC." Electronics 9, no. 1 (2020): 199. http://dx.doi.org/10.3390/electronics9010199.

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An unity-gain 1-bit flip-around digital-to-analog converter (FADAC), without any capacitor matching issue, is proposed as the front-end input stage in a pipelined analog-to-digital converter (ADC), allowing an input signal voltage swing up to be doubled. This large input swing, coupled with the inherent large feedback factor (ideally β = 1) of the proposed FADAC, enables a power-efficient low-voltage high-resolution pipelined ADC design. The 1-bit FADAC is exploited in a SHA-less and opamp-sharing pipelined ADC, exhibiting 12-bit resolution with an input swing of 1.8 Vpp under a 1.1 V power supply. Fabricated in a 0.13-μm CMOS process, the prototype ADC achieves a measured signal-to-noise plus distortion ratio (SNDR) of 66.4 dB and a spurious-free dynamic range (SFDR) of 76.7 dB at 20 MS/s sampling rate. The ADC dissipates 5.2 mW of power and occupies an active area of 0.44 mm2. The measured differential nonlinearity (DNL) is +0.72/−0.52 least significant bit (LSB) and integral nonlinearity (INL) is +0.84/−0.75 LSB at a 3-MHz sinusoidal input.

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Lu, Tzu-Chuen, Ping-Chung Yang, and Biswapati Jana. "Improving the Reversible LSB Matching Scheme Based on the Likelihood Re-Encoding Strategy." Entropy 23, no. 5 (2021): 577. http://dx.doi.org/10.3390/e23050577.

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In 2018, Tseng et al. proposed a dual-image reversible embedding method based on the modified Least Significant Bit matching (LSB matching) method. This method improved on the dual-image LSB matching method proposed by Lu et al. In Lu et al.’s scheme, there are seven situations that cannot be restored and need to be modified. Furthermore, the scheme uses two pixels to conceal four secret bits. The maximum modification of each pixel, in Lu et al.’s scheme, is two. To decrease the modification, Tseng et al. use one pixel to embed two secret bits and allow the maximum modification to decrease from two to one such that the image quality can be improved. This study enhances Tseng et al.’s method by re-encoding the modified rule table based on the probability of each hiding combination. The scheme analyzes the frequency occurrence of each combination and sets the lowest modified codes to the highest frequency case to significantly reduce the amount of modification. Experimental results show that better image quality is obtained using our method under the same amount of hiding payload.

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Muatamed, Hajer, and Anbar Mohammed. "Identifying optimal message embedding location in audio steganography using generative adversarial networks." Eastern-European Journal of Enterprise Technologies 4, no. 9 (118) (2022): 59–68. https://doi.org/10.15587/1729-4061.2022.263695.

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Audio steganography (AS) uses the auditory redundancy of the human ear to conceal the hidden message inside the audio track. In recent studies, deep learning-based steganalysis has swiftly revealed AS by extracting high-dimensional stego acoustic features for categorization. There is still an opportunity for improvement in the current audio steganography required for managing communication confidentiality, access control and data protection. The main objective of this research is to improving the data protection by identifying the data embedding location in the audio. Generative Adversarial Network-based Audio Steganography Framework (GAN-ASF) is presented in this study, and it can automatically learn to provide better cover audio for message embedding. The suggested framework's training architecture comprises a generator, a discriminator, and a steganalyzer learned using deep learning. The Least Significant Bit Matching (LSBM) message embedding technique encrypts the secret message into the steganographic cover audio, which is then forwarded to a trained steganalyzer for misinterpretation as cover audio. After performing the training, stenographic cover audio has been generated for encoding the secret message. Here, Markov model of co-frequency sub images to generate the best cover frequency sub-image to locate an image's hidden payload. Steganographic cover audio created by GAN-ASF has been tested and found to be of excellent quality for embedding messages. The suggested method's detection accuracy is lower than that of the most current state-of-the-art deep learning-based steganalysis. This payload placement approach has considerably increased stego locations' accuracy in low frequencies. The test results GAN-ASF achieves a performance ratio of 94.5 %, accuracy ratio of 96.2 %, an error rate of 15.7 %, SNR 24.3 %, and an efficiency ratio of 94.8 % compared to other methods.

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Artiemjew, Piotr, and Aleksandra Kislak-Malinowska. "Indiscernibility Mask Key for Image Steganography." Computers 9, no. 2 (2020): 38. http://dx.doi.org/10.3390/computers9020038.

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Our concern in this paper is to explore the possibility of using rough inclusions for image steganography. We present our initial research using indiscernibility relation as a steganographic key for hiding information into the stego carrier by means of a fixed mask. The information can be embedded into the stego-carrier in a semi-random way, whereas the reconstruction is performed in a deterministic way. The information shall be placed in selected bytes, which are indiscernible with the mask to a fixed degree. The bits indiscernible with other ratios (smaller or greater) form random gaps that lead to somehow unpredictable hiding of information presence. We assume that in our technique it can modify bits, the change of which does not cause a visual modification detectable by human sight, so we do not limit ourselves to the least significant bit. The only assumption is that we do not use the position when the mask we define uses it. For simplicity’s sake, in this work we present its operation, features, using the Least Significant Bit (LSB) method. In the experimental part, we have implemented our method in the context of hiding image into the image. The LSB technique in its simplest form is not resistant to stegoanalisys, so we used the well-known LSB matching method to mask the presence of our steganographic key usage. To verify the resistance to stegoanalisys we have conducted and discussed Chi-square and LSB enhancement test. The positive features of our method include its simplicity and speed, to decode a message we need to hide, or pass to another channel, a several-bit mask, degree of indiscernibility and size of the hidden file. We hope that our method will find application in the art of creating steganographic keys.

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Darwis, Dedi, Akmal Junaidi, Dewi Asiah Shofiana, and Wamiliana. "A New Digital Image Steganography Based on Center Embedded Pixel Positioning." Cybernetics and Information Technologies 21, no. 2 (2021): 89–104. http://dx.doi.org/10.2478/cait-2021-0021.

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Abstract In this study we propose a new approach to tackle the cropping problem in steganography which is called Center Embedded Pixel Positioning (CEPP) which is based on Least Significant Bit (LSB) Matching by setting the secret image in the center of the cover image. The evaluation of the experiment indicated that the secret image can be retrieved by a maximum of total 40% sequential cropping on the left, right, up, and bottom of the cover image. The secret image also can be retrieved if the total asymmetric cropping area is 25% that covered two sides (either left-right, left-up or right-up). In addition, the secret image can also be retrieved if the total asymmetric cropping area is 70% if the bottom part is included. If asymmetric cropping area included three sides, then the algorithm fails to retrieve the secret image. For cropping in the botom the secret image can be extracted up to 70%.

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Jia, Hanbo, Xuan Guo, Xuqiang Zheng, et al. "A 4-bit 36 GS/s ADC with 18 GHz Analog Bandwidth in 40 nm CMOS Process." Electronics 9, no. 10 (2020): 1733. http://dx.doi.org/10.3390/electronics9101733.

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This paper presents a 4-bit 36 GS/s analog-to-digital converter (ADC) employing eight time-interleaved (TI) flash sub-ADCs in 40 nm complementary metal-oxide-semiconductor (CMOS) process. A wideband front-end matching circuit based on a peaking inductor is designed to increase the analog input bandwidth to 18 GHz. A novel offset calibration that can achieve quick detection and accurate correction without affecting the speed of the comparator is proposed, guaranteeing the high-speed operation of the ADC. A clock distribution circuit based on CMOS and current mode logic (CML) is implemented in the proposed ADC, which not only maintains the speed and quality of the high-speed clock, but also reduces the overall power consumption. A timing mismatch calibration is integrated into the chip to achieve fast timing mismatch detection of the input signal which is bandlimited to the Nyquist frequency for the complete ADC system. The experimental results show that the differential nonlinearity (DNL) and integral nonlinearity (INL) are −0.28/+0.22 least significant bit (LSB) and −0.19/+0.16 LSB, respectively. The signal-to-noise-and-distortion ratio (SNDR) is above 22.5 dB and the spurious free dynamic range (SFDR) is better than 35 dB at 1.2 GHz. An SFDR above 24.5 dB and an SNDR above 18.6 dB across the entire Nyquist frequency can be achieved. With a die size of 2.96 mm * 1.8 mm, the ADC consumes 780 mW from the 0.9/1.2/1.8 V power supply.

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Lara, Lara, Hadeel M. Saleh, Asraa Y. .., Lara Ahmad Ghasab Almashagba, and Fathiya Al Abri. "Biometric Data Securement Using Visual Information Encryption." Journal of Cybersecurity and Information Management 16, no. 1 (2025): 99–106. https://doi.org/10.54216/jcim.160108.

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Biometric data is becoming increasingly valuable because of its uniqueness, and digital watermarking techniques are used to protect it. This paper presents a new method of hiding Palmprint images using wavelet decomposition and Encrypting Visual Information (EVI). EVI is a technique for securing Palmprint print images that has been extensively studied in this report. By embedding the Palmprint image in the cover image, and then using wavelet transformation, this output image can be decomposed into four segments (Segment Low Low, Segment Low High, Segment High Low, and Segment High High). A compressor is placed at the sender site to compress these four segments. DWT is obtained at the receiver side and then the bit-matching procedure is applied to obtain the original palmprint image. Using data concealing and EVI implementations on biometrics, palmprints, and related textual information can be protected from identity fraud. The watermarked cover images and palmprints, which could be used for authentication, have been improved from the existing approach. By reducing the segment size, quality is achieved along with higher security and bandwidth reduction. In addition, the three least significant bits are successfully applied to increase the length of a secret message while retaining palmprint quality.

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Alia, Mohammad, and Khaled Suwais. "Improved Steganography Scheme based on Fractal Set." International Arab Journal of Information Technology 17, no. 1 (2019): 128–36. http://dx.doi.org/10.34028/iajit/17/1/15.

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Steganography is the art of hiding secret data inside digital multimedia such as image, audio, text and video. It plays a significant role in current trends for providing secure communication and guarantees accessibility of secret information by authorised parties only. The Least-Significant Bit (LSB) approach is one of the important schemes in steganography. The majority of LSB-based schemes suffer from several problems due to distortion in a limited payload capacity for stego-image. In this paper, we have presented an alternative steganographic scheme that does not rely on cover images as in existing schemes. Instead, the image which includes the secure hidden data is generated as an image of a curve. This curve is resulted from a series of computation that is carried out over the mathematical chaotic fractal sets. The new scheme aims at improving the data concealing capacity, since it achieves limitless concealing capacity and disposes of the likelihood of the attackers to realise any secret information from the resulted stego-image. From the security side, the proposed scheme enhances the level of security as the scheme depends on the exact matching between secret information and the generated fractal (Mandelbrot-Julia) values. Accordingly, a key stream is created based on these matches. The proposed scheme is evaluated and tested successfully from different perspectives

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Mahmood, Ahlam Fadhil, Nada Abdul Kanai, and Sana Sami Mohmmad. "An FPGA Implementation of Secured Steganography Communication System." Tikrit Journal of Engineering Sciences 19, no. 4 (2012): 14–23. http://dx.doi.org/10.25130/tjes.19.4.02.

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Steganography is the idea of hiding secret message in multimedia cover which will be transmitted through the Internet. The cover carriers can be image, video, sound or text data. This paper presents an implementation of color image steganographic system on Field Programmable Gate Array and the information hiding/extracting techniques in various images. The proposed algorithm is based on merge between the idea from the random pixel manipulation methods and the Least Significant Bit (LSB) matching of Steganography embedding and extracting method.In a proposed steganography hardware approach, Linear Feedback Shift Register (LFSR) method has been used in stego architecture to hide the information in the image. The LFSRs are utilized in this approach as address generators. Different LFSR arrangements using different connection unit have been implemented at the hardware level for hiding/extracting the secret data. Multilayer embedding is implemented in parallel manner with a three-stage pipeline on FPGA.This work showed attractive results especially in the high throughputs, better stego-image quality, requires little calculation and less utilization of FPGA area. The imperceptibility of the technique combined with high payload, robustness of embedded data and accurate data retrieval renders the proposed Steganography system is suitable for covert communication and secures data transmission applications.

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Li, Longlong, Yuliang Lu, Lintao Liu, Yuyuan Sun, and Jiayu Wang. "Practical Secret Image Sharing Based on the Chinese Remainder Theorem." Mathematics 10, no. 12 (2022): 1959. http://dx.doi.org/10.3390/math10121959.

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Compared with Shamir’s original secret image sharing (SIS), the Chinese-remainder-theorem-based SIS (CRTSIS) generally has the advantages of a lower computation complexity, lossless recovery and no auxiliary encryption. However, general CRTSIS is neither perfect nor ideal, resulting in a narrower range of share pixels than that of secret pixels. In this paper, we propose a practical and lossless CRTSIS based on Asmuth and Bloom’s threshold algorithm. To adapt the original scheme for grayscale images, our scheme shares the high seven bits of each pixel and utilizes the least significant bit (LSB) matching technique to embed the LSBs into the random integer that is generated in the sharing phase. The chosen moduli are all greater than 255 and the share pixels are in the range of [0, 255] by a screening operation. The generated share pixel values are evenly distributed in the range of [0, 255] and the selection of (k,n) threshold is much more flexible, which significantly improves the practicality of CRTSIS. Since color images in RGB mode are made up of three channels, it is easy to extend the scheme to color images. Theoretical analysis and experiments are given to validate the effectiveness of the proposed scheme.

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Kamal, A. H. M. "Steganography: Securing Message in wireless network." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 4, no. 3 (2013): 797–801. http://dx.doi.org/10.24297/ijct.v4i3.4200.

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Steganography is the process of hiding a secret message with in a cover medium. However eavesdropper may guess the embedding algorithm like least significant bit (LSB) replacement of Chan et al, 2004; Wang et al, 2001; Wu et al, 2005, LSB matching of Mielikainen, 2006, addition and/or subtraction of Andead wastfield, 2001; F. Huang et al in 2011, Exploiting Modification Direction by Zhang and Wang, 2006, Binary Space Partition by Tsai and Wang, 2007, modulus function of Chin et al, 2011 and thus can apply the respective extraction method to detect the secret message. So challenges lies in the methodologies of embedding message. Capacity, security and robustness are the services to be demanded by users. Again the true-positive rate of secret message detection by eavesdropper should be lessened by applying firm technique. Thirdly operating domain should be less sensitive to the noise, margin level of losses or alteration of data while communicating through unguided medium like wireless network, sensor network and cellular network. This paper will briefly discuss the steganographic methods and their experimental results explained in the survey paper of Niels Provos and Peter Honeyman to hide and seek message. Finally the proposed results and the directions for future works are addressed.

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Majeed, Nehayat Ezzaldeen, and Haval Mohammed Sidqi. "Robust Steganography Technique for Embedding Secret Images." Halabja University Journal 7, no. 4 (2022): 264–81. http://dx.doi.org/10.32410/huj-10443.

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Steganography is a technique used to disguise the existence of a secret communication. It is used in many fields to solve information security problems. Steganography is a technique to embed secret data in a carrier image and obtain a new image that can't actually be distinguished from the original image. This paper proposes steganography method based on least significant bit (LSB) replacement and integer wavelet transform IWT through lifting scheme to achieve high quality of stego image. we will do some pre-processing on the secret image before embedding process. IWT transforms the secret image from spatial domain to a frequency domain and will be divided it into a group of sub-bands, some of which we will use for their utmost importance and ignore some of them. We have embedded the secret image in a sequential LSB method and in a randomly LSB method and also by the method LSB matching. But after applying our proposed method to the secret image and then embedded it in each of the three above-mentioned methods, it was found that it had a higher degree of imperceptibly and obtained a higher rate of PSNR and the possibility of recovering the secret image without errors. By using the randomly and LSBM methods gives a higher security and resistance to extraction by attackers.

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Priya, Jain, Kumar Somesh, and Kumar Goel Raj. "A Survey on Enhancement of Text Security Using Steganography and Cryptographic Techniques." International Journal of Trend in Scientific Research and Development 2, no. 5 (2018): 20–24. https://doi.org/10.31142/ijtsrd15800.

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Increase in the number of attack recorded during electronic exchange of information between the source and intended destination has indeed called for a more robust method for securing data transfer. Cryptography and steganography are well known and widely used techniques that manipulate information in order to cipher or hide their existence. Many different carrier file format scan be used but digital images are the most popular because of their frequency on the internet. The digital images are the most popular because of their frequency on the Web among all different carrier file formats. Image steganography, achieves the secrecy by embedding data into cover image and generating a stego image. There are many types of steganography techniques each have their advantages and disadvantages. This paper discussed a technique used on the advanced LSB least significant bit and RSA algorithm. By matching data to an image, there is less chance of an attacker being able to use steganalysis to recover data. Before hiding the data in an image the application first encrypts it Priya Jain | Somesh Kumar | Raj Kumar Goel "A Survey on Enhancement of Text Security Using Steganography and Cryptographic Techniques" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-5 , August 2018, URL: https://www.ijtsrd.com/papers/ijtsrd15800.pdf

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Chen, Yuantao, Jiajun Tao, Qian Zhang, et al. "Saliency Detection via the Improved Hierarchical Principal Component Analysis Method." Wireless Communications and Mobile Computing 2020 (May 5, 2020): 1–12. http://dx.doi.org/10.1155/2020/8822777.

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Aiming at the problems of intensive background noise, low accuracy, and high computational complexity of the current significant object detection methods, the visual saliency detection algorithm based on Hierarchical Principal Component Analysis (HPCA) has been proposed in the paper. Firstly, the original RGB image has been converted to a grayscale image, and the original grayscale image has been divided into eight layers by the bit surface stratification technique. Each image layer contains significant object information matching the layer image features. Secondly, taking the color structure of the original image as the reference image, the grayscale image is reassigned by the grayscale color conversion method, so that the layered image not only reflects the original structural features but also effectively preserves the color feature of the original image. Thirdly, the Principal Component Analysis (PCA) has been performed on the layered image to obtain the structural difference characteristics and color difference characteristics of each layer of the image in the principal component direction. Fourthly, two features are integrated to get the saliency map with high robustness and to further refine our results; the known priors have been incorporated on image organization, which can place the subject of the photograph near the center of the image. Finally, the entropy calculation has been used to determine the optimal image from the layered saliency map; the optimal map has the least background information and most prominently saliency objects than others. The object detection results of the proposed model are closer to the ground truth and take advantages of performance parameters including precision rate (PRE), recall rate (REC), and F-measure (FME). The HPCA model’s conclusion can obviously reduce the interference of redundant information and effectively separate the saliency object from the background. At the same time, it had more improved detection accuracy than others.

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Chi, Sabrina S., and Devin M. Shanthikumar. "Local Bias in Google Search and the Market Response around Earnings Announcements." Accounting Review 92, no. 4 (2016): 115–43. http://dx.doi.org/10.2308/accr-51632.

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ABSTRACT We examine the impact of distance on internet search, and the effect of the “local bias” in search on the stock market response around earnings announcements. We find significant local bias in search behavior. Motivated by theories explaining local bias, local information advantage, and familiarity bias, we predict and find that firms with higher local bias in search experience higher bid-ask spreads, lower trading volumes, and lower earnings response coefficients at the time of earnings announcements, consistent with non-local investors relying more than locals on public information announcements. Consistent with local information advantage, we find that in the week prior to the announcement, firms with higher local bias have higher bid-ask spreads, higher trading volumes, and returns that are more predictive of the coming earnings surprise. Consistent with familiarity bias, firms with higher local bias in search experience stronger post-earnings announcement drift. We use unique predictions, propensity score matching, and two-stage least squares to identify the effects of local bias separately from the effects of overall visibility. Overall, we show there is significant local bias in search, and that this local bias has a significant impact on the market response around earnings announcements.

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Hajer, Muatamed, and Mohammed Anbar. "Identifying optimal message embedding location in audio steganography using generative adversarial networks." Eastern-European Journal of Enterprise Technologies 4, no. 9(118) (2022): 59–68. http://dx.doi.org/10.15587/1729-4061.2022.263695.

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Audio steganography (AS) uses the auditory redundancy of the human ear to conceal the hidden message inside the audio track. In recent studies, deep learning-based steganalysis has swiftly revealed AS by extracting high-dimensional stego acoustic features for categorization. There is still an opportunity for improvement in the current audio steganography required for managing communication confidentiality, access control and data protection. The main objective of this research is to improving the data protection by identifying the data embedding location in the audio. Generative Adversarial Network-based Audio Steganography Framework (GAN-ASF) is presented in this study, and it can automatically learn to provide better cover audio for message embedding. The suggested framework's training architecture comprises a generator, a discriminator, and a steganalyzer learned using deep learning. The Least Significant Bit Matching (LSBM) message embedding technique encrypts the secret message into the steganographic cover audio, which is then forwarded to a trained steganalyzer for misinterpretation as cover audio. After performing the training, stenographic cover audio has been generated for encoding the secret message. Here, Markov model of co-frequency sub images to generate the best cover frequency sub-image to locate an image's hidden payload. Steganographic cover audio created by GAN-ASF has been tested and found to be of excellent quality for embedding messages. The suggested method's detection accuracy is lower than that of the most current state-of-the-art deep learning-based steganalysis. This payload placement approach has considerably increased stego locations' accuracy in low frequencies. The test results GAN-ASF achieves a performance ratio of 94.5 %, accuracy ratio of 96.2 %, an error rate of 15.7 %, SNR 24.3 %, and an efficiency ratio of 94.8 % compared to other methods.

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Гуц, А. К., and Д. Э. Вильховский. "An algorithm for identifying steganographic inserts of the LSB-replacement type based on the hierarchy analysis." МОДЕЛИРОВАНИЕ, ОПТИМИЗАЦИЯ И ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИ 8, no. 2(29) (2020): 6–7. http://dx.doi.org/10.26102/2310-6018/2020.29.2.006.

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В статье предлагается алгоритм выявления стеганографических вставок, осуществляемых в виде замены наименее значащих битов. Предлагаемый алгоритм базируется на методе анализа иерархий. Рассматриваются слои младших битов синей компоненты. Области встраивания определяются при помощи алгоритма таксономии. Применяются алгоритм предварительной обработки для того чтобы повысить эффективности на участках, которые содержат градиентную заливку. Научная новизна заключается в разработке алгоритма стеганографического анализа метода LSB-замены при низком заполнении стегоконтейнера, основанного на сравнительном анализе нескольких слоев изображения с помощью метода анализа иерархий, отличающегося тем, что выделенные критерии принятия решения представляют возможность учитывать структуру исходного изображения-контейнера, которая хранится в более высоких битовых слоях и за счет этого представляется возможным сформировать карту подозрительных пикселей, повышающую эффективность обнаружения встроенного сообщения.Был выполнен эксперимент на ЭВМ. Для искусственных изображений с градиентной и равномерной заливкой предлагаемый алгоритм дает возможность определять в среднем 91% подмененных битов, тогда как ложные срабатывания составляют не больше 1%. Положение встроенных битов может быть определено на основе сопоставления матрицы решений с начальным изображением.Предлагаемый алгоритм эффективен при малых размерах встроенного сообщения в отличие от созданных ранее алгоритмов. The article proposes an algorithm for identifying steganographic inserts implemented as a replacement of the least significant bits. The proposed algorithm is based on the hierarchy analysis method. The layers of the least significant bits of the blue component are considered. The embedding areas are determined using the taxonomy algorithm. A preprocessing algorithm is applied in order to increase efficiency in areas that contain gradient fill. The scientific novelty lies in the development of an algorithm for steganographic analysis of the LSB replacement method with low filling of the container, based on a comparative analysis of several image layers using the hierarchy analysis method, characterized in that the selected decision criteria provide the opportunity to take into account the structure of the original container image that is stored in higher bit layers and due to this it is possible to form a map of suspicious pixels, increasing efficiency embedded messages.A computer experiment was performed. For artificial images with gradient and uniform fill, the proposed algorithm makes it possible to determine on average 91% of the replaced bits, while false positives are no more than 1%. The position of the embedded bits can be determined by matching the decision matrix with the initial image.The proposed algorithm is effective for the small size of the embedded message, in contrast to the previously created algorithms. Keywords:identification of stego inserts, analysis of images with inserts, analysis of stegocontainer, search for LSB inserts, embedding LSB.

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Izvolsky, A. A. "Matrix model parametric identification of antenna tuning units." Vestnik IzhGTU imeni M.T. Kalashnikova 26, no. 1 (2023): 71–83. http://dx.doi.org/10.22213/2413-1172-2023-1-71-83.

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HF radiocommunication modern development trends provide for improved handling and increased speed of antenna tuning units (ATU) functioning. The need to control the tuning process using a microcontroller based on the measurement results of antenna input impedance in the “on-line” mode requires an increase in the accuracy of modeling the transformative properties of these devices and subsequent calculations for the development of control commands by discrete tuning bodies. The more reliable the data in the memory of the microcontroller will characterize the real properties of the device's tuning bodies, the better their regulation will be. Based on the results of a full-scale experiment, the issues of parametric identification of the previously proposed conceptual matrix model of discreet power circuit are considered. Due to the complexity of technological modeling of circuits transformative properties, the task is to increase the accuracy of its numerical results for each device. With the found set of solutions for the model with the selected structure and a significant number of unknown parameters, its identification by the objective function extremum is not possible. Accordingly, the analysis of a priori identifiability (theoretical, with unambiguous definition of parameters) is carried out on the basis of a qualitative study of the structure of the model and the scheme of the “ideal” experiment (with determinism of all unmistakably measured values). The identifiability of the proposed power circuit model has been confirmed. The variants of the experiment, the algorithm for processing its results, as well as ways to obtain their guaranteed quality with the help of a vector circuits analyzer for a certain time at a given cost are described. The criterion for assessing the conformity of the model to a real power circuit is a measure of the number of its errors after measuring complex coefficients on a set of frequencies. Processing the results using the least squares method with interpolation for the entire frequency band reduces the errors and complexity of the experiment. Modeling of a 9-bit matching inductive body confirmed the correctness and effectiveness of the matrix description of the transforming properties of the wide band ATU and other solutions presented, as well as the possibility of full automation of this experiment.

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Al-Obaidi, Fatin E. M., and Ali Jassim Mohamed Ali. "Which Bit Is Better in Least Significant Bit?" Journal of Information Security 06, no. 03 (2015): 161–65. http://dx.doi.org/10.4236/jis.2015.63017.

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Praveenkum, Padmapriya, P. Rajalakshm, G. U. Priyanga, K. Thenmozhi, John Bosco Balaguru Rayappan, and Rengarajan Amirtharaj. "Least Significant Bit but Quantum Bit: A Quasi Stego." Information Technology Journal 13, no. 16 (2014): 2544–51. http://dx.doi.org/10.3923/itj.2014.2544.2551.

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Olbrich, Rainer, and Carsten D. Schultz. "Multichannel advertising: does print advertising affect search engine advertising?" European Journal of Marketing 48, no. 9/10 (2014): 1731–56. http://dx.doi.org/10.1108/ejm-10-2012-0569.

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Purpose – The study contributes to our understanding of search engine advertising in two main ways. Firstly, we analyze the comparative effectiveness of its campaign parameters. Secondly, we examine the effect of print advertising on search engine advertising Design/methodology/approach – Based on advertising data for a three-year period, we test the hypotheses by means of a path model with the aid of partial least squares. Findings – The advertising budget and the degree of keyword matching yield the greatest effect on the number of signed contracts. The click-through rate and the bid amount contribute, to a lesser extent, to explaining this financial target variance. The number of keywords had no significant effect. The study did not yield significant evidence of print advertising, directly affecting the number of search engine advertisement impressions, but showed an indirect effect of print advertising on the number of conversions, induced directly by search engine advertising. Research limitations/implications – The multichannel relationship of print and search engine advertising, including its campaign parameters, provides a starting point for future research to provide a coherent methodology for capturing the necessary data, processing the underlying information and evaluating the advertising effects. Practical implications – The multichannel effect needs to be quantified and taken into account when evaluating print advertising and search advertising campaigns and the future advertising mix is planned. Originality/value – The study extends the field of search engine advertising in the direction of multichannel effects. In comparison to previous research, empirical evidence on the multichannel usage of print advertising and search engine advertising, related to an overall economic target, is provided.

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Shreelekshmi, R., M. Wilscy, and C. E. Veni Madhavan. "Undetectable least significant bit replacement steganography." Multimedia Tools and Applications 78, no. 8 (2018): 10565–82. http://dx.doi.org/10.1007/s11042-018-6541-0.

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Aditya, Sonar, Malve Ved, Kandekar Shashikant, Kardile Samadhan, and Ms Adke Shilpa. "Image Steganography Using Least Significant Bit." International Journal of Research Publication and Reviews 5, no. 4 (2024): 2505–8. http://dx.doi.org/10.55248/gengpi.5.0424.0966.

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Lubis, R. R. A., S. M. Hardi, M. Zarlis, I. Jaya, and J. T. Tarigan. "Analysis on Combination of Watermarking Algorithm: Modified Least Significant Bit Algorithm with Least Significant Bit+1." Journal of Physics: Conference Series 1235 (June 2019): 012081. http://dx.doi.org/10.1088/1742-6596/1235/1/012081.

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Amin, M. Miftakul. "IMAGE STEGANOGRAPHY DENGAN METODE LEAST SIGNIFICANT BIT (LSB)." CSRID (Computer Science Research and Its Development Journal) 6, no. 1 (2015): 53. http://dx.doi.org/10.22303/csrid.6.1.2014.53-64.

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ABSTRAK Keamanan dalam menyampaikan pesan rahasia merupakan faktor penting dalam penyebaran informasi di dunia maya. Melindungi supaya pesan yang akan dikirimkan sampai kepada pihak yang berhak, perlu dibuat sebuah mekanisme penyembunyian pesan. Tujuan dari penelitian ini adalah menyembunyikan pesan berupa teks rahasia ke dalam citra digital true colour 24 bit dalam format RGB. Metode yang digunakan untuk menyisipkan pesan rahasia menggunakan metode LSB (Least Significant Bit) dengan mengganti bit terakhir atau bit ke-8 dalam setiap komponen warna RGB. Pilihan jenis file citra RGB dengan pertimbangan kapasitas pesan yang dapat disisipkan lebih besar dibandingkan jika menggunakan citra grayscale, hal ini dikarenakan dalam 1 pixel dapat disisipkan 3 buah bit pesan. Ujicoba yang dilakukan memberikan hasil bahwa pesan yang disembunyikan ke dalam citra digital tidak mengurangi kualitas citra digital secara signifikan, dan pesan yang telah disembunyikan dapat diekstrak kembali, sehingga pesan yang dikirimkan dapat sampai dengan aman kepada penerima.

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Zhong, Hua. "New least-significant-bit-based steganographic model." Optical Engineering 42, no. 7 (2003): 2082. http://dx.doi.org/10.1117/1.1577351.

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Darmawan, Yudhi, Nico Fahrul Marinza, and Yohanes Dwi Cahyono. "OPTIMASI STEGANOGRAFI BERBASIS LEAST SIGNIFICANT BIT (LSB) METODE OPERASI PERGESERAN BIST." JATI (Jurnal Mahasiswa Teknik Informatika) 8, no. 5 (2024): 11055–59. http://dx.doi.org/10.36040/jati.v8i5.11825.

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Penelitian ini membahas optimasi metode steganografi berbasis Least Significant Bit (LSB) dengan menggunakan operasi pergeseran bit untuk meningkatkan kapasitas penyembunyian pesan dalam gambar digital. Metode ini memodifikasi 8 bit per piksel yang melibatkan warna merah, hijau, biru, dan alpha untuk meningkatkan jumlah karakter yang dapat disisipkan dibandingkan dengan metode sebelumnya yang hanya memodifikasi 3 bit per piksel. Implementasi melibatkan dua tahap utama: operasi masker bit dan injeksi bit dengan logika AND dan OR. Penelitian ini mengevaluasi kualitas gambar steganografi dengan membandingkan nilai Peak Signal-to-Noise Ratio (PSNR) dan Mean Squared Error (MSE) antara gambar penutup dan gambar steganografi. Hasil menunjukkan bahwa meskipun kapasitas penyisipan meningkat, kualitas gambar sedikit menurun dibandingkan metode sebelumnya. Namun, metode yang diusulkan tetap memberikan peningkatan signifikan dalam kapasitas penyembunyian pesan tanpa merusak gambar secara drastis

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Kwan, Chiman, and David Gribben. "Target Detection and Classification Improvements using Contrast Enhanced 16-bit Infrared Videos." Signal & Image Processing : An International Journal 12, no. 1 (2021): 23–38. http://dx.doi.org/10.5121/sipij.2021.12103.

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In our earlier target detection and classification papers, we used 8-bit infrared videos in the Defense Systems Information Analysis Center(DSIAC) video dataset. In this paper, we focus on how we can improve the target detection and classification results using 16-bit videos. One problem with the 16-bit videos is that some image frames have very low contrast. Two methods were explored to improve upon previous detection and classification results. The first method used to improve contrast was effectively the same as the baseline 8-bit video data but using the 16-bit raw data rather than the 8-bit data taken from the avi files. The second method used was a second order histogram matching algorithm that preserves the 16-bit nature of the videos while providing normalization and contrast enhancement. Results showed the second order histogram matching algorithm improved the target detection using You Only Look Once (YOLO) and classificationusing Residual Network (ResNet) performance. The average precision (AP) metric in YOLO was improved by 8%. This is quite significant. The overall accuracy (OA) of ResNet has been improved by 12%. This is also very significant.

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Wiranata, Ade Davy, and Rima Tamara Aldisa. "Aplikasi Steganografi Menggunakan Least Significant Bit (LSB) dengan Enkripsi Caesar Chipper dan Rivest Code 4 (RC4) Menggunakan Bahasa Pemrograman JAVA." Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) 5, no. 3 (2021): 277. http://dx.doi.org/10.35870/jtik.v5i3.219.

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The research objective is to hide messages through images using the LSB (Least Significant Bit) method and Caesar Chipper and Rivest Code 4 encryption. The LSB (Least Significant Bit) method is used as a message hiding technique in steganography where hiding hidden messages is done by changing a few bits in the segment. image with a secret message. The results of this study resulted in an implementation using the Least Significant Bit (LSB) to be applied to institutions with an interest in maintaining the confidentiality of encrypted image output, changing the image file size and sound (audio) file size.Keywords:Steganography, Least Significant Bit (LSB), Caesar Chiper and RC4.

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Nur’aini, Siti. "Steganografi Pada Digital Image Menggunakan Metode Least Significant Bit Insertion." Walisongo Journal of Information Technology 1, no. 1 (2019): 73. http://dx.doi.org/10.21580/wjit.2019.1.1.4025.

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Steganography is a way to hide messages or confidential data in a medium called a carrier file. Embedding is done by the Least Significant Bit Insertion method, which is to replace the lowest bit of Red Green Blue (RGB) each pixel with the data bit you want to insert. With this method the difference between pixels that have not been pasted by messages and pixels that have been pasted by messages cannot be distinguished by human eye sight. Because the LSB insertion method is used, it is necessary to consider the type of digital image format used, this is necessary to avoid the loss of messages when extracting. And the best digital image format used is the 24-bit BMP because the BMP format is lossless compression

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Pradita, Ranida, and Ida Nurhaida. "Implementasi Steganografi Video dengan Menggunakan Metode Egypt, Least Significant Bit (LSB) dan Least Significant Bit (LSB) Fibonacci Edge Pixel." Jurnal Telekomunikasi dan Komputer 10, no. 1 (2020): 25. http://dx.doi.org/10.22441/incomtech.v10i1.7282.

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Seiring dengan perkembangan teknologi 5G, penyebaran dengan menggunakan video semakin besar dan mudah. Penyebaran informasi baik yang tersembunyi atau tidak semakin mudah disebarluaskan dengan menggunakan internet. Steganografi adalah cara menyembunyikan informasi dalam image atau video. Steganografi berbentuk digital image, text, audio, video, 3D model, dan lain-lain. Media digital yang popularitasnya paling tinggi dalam penelitian algoritma steganografi dengan menggunakan media digital image. Tulisan ini menggunakan media digital video karna media penelitian sebelumnya menggunakan media digital image. Pada tulisan ini akan diulas dan dianalis tentang video steganografi dengan menggunakan metode Egypt, Least Significant Bit (LSB), dan Least Significant Bit (LSB) Fibonacci Edge Pixel. Analisis video steganografi ini bertujuan untuk mendeteksi video yang mengandung unsur pesan rahasia yang kemungkinan untuk pengintaian. Hasil Peak Signal-to-Noise Ratio (PSNR) yang didapat dari penelitian ini rata-rata 40.46 dB dan menghasilkan rata-rata presentase similarity 30.67 %. Rata-rata Mean Square Error (MSE) pada penelitian ini adalah sebesar 0.50657. Untuk metode yang paling optimal yang digunakan dalam video steganografi adalah dengan menggunakan Metode Egypt.

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Wang, Jun Jie, Qian Mo, Dong Xia Mei, and Su Li. "Research for Robust Watermarking Algorithm Using Least Significant Bit." Advanced Materials Research 268-270 (July 2011): 1697–700. http://dx.doi.org/10.4028/www.scientific.net/amr.268-270.1697.

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An image watermarking algorithm using Least Significant Bit is presented. Firstly, Logistic chaotic map is utilized to generate embedding bits for the watermark. Then, the discrete cosine transform is performed on the host image, and the hiding bit is embedded in the coefficient of discrete cosine transform by replacing Least Significant Bit, which causes minimal distortion of the host image.The original host image is not required when extracting the watermark . Experimental results show that the watermarked image almost has no difference from the original host image, and the quality of the extracted image is satisfying, the capacity of this algorithm is high. This algorithm is robust to many attacks, such as noise attack, JPEG Compression attack. Introduction

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Julianto, Yohanes, and Kristoforus Jawa Bendi. "SISTEM STEGANOGRAFI DENGAN METODE LEAST SIGNIFICANT BIT (LSB) TERACAK." Jurnal Ilmiah Flash 2, no. 2 (2016): 116. http://dx.doi.org/10.32511/jiflash.v2i2.32.

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Information security has become important today. Steganography is one of the ways tomake any information secure. It hides information by inserting it in a media or cover. LSB (LeastSignificant Bit)steganographic technique has become popular because of its simplicity. LSB(Least Significant Bit) is one algorithm from steganography. The weakness of LSB is bits ofembedded are inserted sequentially. It can be easily tracked. Our research using text as embeddedmessage and WAV audio format as cover-object. We combine LSB and LCG (Linear CongruetialGenerator) to determinant the random position of replacement bit. Outcome of this research is asoftware that was develop by waterfall model and coded in Visual Basic. The result shows thatembedded message can be encode dan decode

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Journal articles on the topic 'Least significant bit matching'

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