Print-Scan Resilient Text Image Watermarking Based on Stroke Direction Modulation for Chinese Document Authentication

Print-scan resilient watermarking has emerged as an attractive way for document security. This paper proposes an stroke direction modulation technique for watermarking in Chinese text images. The watermark produced by the idea offers robustness to print-photocopy-scan, yet provides relatively high embedding capacity without losing the transparency. During the embedding phase, the angle of rotatable strokes are quantized to embed the bits. This requires several stages of preprocessing, including stroke generation, junction searching, rotatable stroke decision and character partition. Moreover, shuffling is applied to equalize the uneven embedding capacity. For the data detection, denoising and deskewing mechanisms are used to compensate for the distortions induced by hardcopy. Experimental results show that our technique attains high detection accuracy against distortions resulting from print-scan operations, good quality photocopies and benign attacks in accord with the future goal of soft authentication

A Taxonomy of Hyperlink Hiding Techniques

Hidden links are designed solely for search engines rather than visitors. To get high search engine rankings, link hiding techniques are usually used for the profitability of black industries, such as illicit game servers, false medical services, illegal gambling, and less attractive high-profit industry, etc. This paper investigates hyperlink hiding techniques on the Web, and gives a detailed taxonomy. We believe the taxonomy can help develop appropriate countermeasures. Study on 5,583,451 Chinese sites' home pages indicate that link hidden techniques are very prevalent on the Web. We also tried to explore the attitude of Google towards link hiding spam by analyzing the PageRank values of relative links. The results show that more should be done to punish the hidden link spam.Comment: 12 pages, 2 figure

Coverless Information Hiding Based on Generative adversarial networks

Traditional image steganography modifies the content of the image more or less, it is hard to resist the detection of image steganalysis tools. To address this problem, a novel method named generative coverless information hiding method based on generative adversarial networks is proposed in this paper. The main idea of the method is that the class label of generative adversarial networks is replaced with the secret information as a driver to generate hidden image directly, and then extract the secret information from the hidden image through the discriminator. It's the first time that the coverless information hiding is achieved by generative adversarial networks. Compared with the traditional image steganography, this method does not modify the content of the original image. therefore, this method can resist image steganalysis tools effectively. In terms of steganographic capacity, anti-steganalysis, safety and reliability, the experimen shows that this hidden algorithm performs well.Comment: arXiv admin note: text overlap with arXiv:1703.05502 by other author

Spec-ResNet: A General Audio Steganalysis scheme based on Deep Residual Network of Spectrogram

The widespread application of audio and video communication technology make the compressed audio data flowing over the Internet, and make it become an important carrier for covert communication. There are many steganographic schemes emerged in the mainstream audio compression data, such as AAC and MP3, followed by many steganalysis schemes. However, these steganalysis schemes are only effective in the specific embedded domain. In this paper, a general steganalysis scheme Spec-ResNet (Deep Residual Network of Spectrogram) is proposed to detect the steganography schemes of different embedding domain for AAC and MP3. The basic idea is that the steganographic modification of different embedding domain will all introduce the change of the decoded audio signal. In this paper, the spectrogram, which is the visual representation of the spectrum of frequencies of audio signal, is adopted as the input of the feature network to extract the universal features introduced by steganography schemes; Deep Neural Network Spec-ResNet is well-designed to represent the steganalysis feature; and the features extracted from different spectrogram windows are combined to fully capture the steganalysis features. The experiment results show that the proposed scheme has good detection accuracy and generality. The proposed scheme has better detection accuracy for three different AAC steganographic schemes and MP3Stego than the state-of-arts steganalysis schemes which are based on traditional hand-crafted or CNN-based feature. To the best of our knowledge, the audio steganalysis scheme based on the spectrogram and deep residual network is first proposed in this paper. The method proposed in this paper can be extended to the audio steganalysis of other codec or audio forensics.Comment: 12 pages, 11 figures, 5 table

FontCode: Embedding Information in Text Documents using Glyph Perturbation

We introduce FontCode, an information embedding technique for text documents. Provided a text document with specific fonts, our method embeds user-specified information in the text by perturbing the glyphs of text characters while preserving the text content. We devise an algorithm to chooses unobtrusive yet machine-recognizable glyph perturbations, leveraging a recently developed generative model that alters the glyphs of each character continuously on a font manifold. We then introduce an algorithm that embeds a user-provided message in the text document and produces an encoded document whose appearance is minimally perturbed from the original document. We also present a glyph recognition method that recovers the embedded information from an encoded document stored as a vector graphic or pixel image, or even on a printed paper. In addition, we introduce a new error-correction coding scheme that rectifies a certain number of recognition errors. Lastly, we demonstrate that our technique enables a wide array of applications, using it as a text document metadata holder, an unobtrusive optical barcode, a cryptographic message embedding scheme, and a text document signature

Discrete Wavelet Transform and Gradient Difference based approach for text localization in videos

The text detection and localization is important for video analysis and understanding. The scene text in video contains semantic information and thus can contribute significantly to video retrieval and understanding. However, most of the approaches detect scene text in still images or single video frame. Videos differ from images in temporal redundancy. This paper proposes a novel hybrid method to robustly localize the texts in natural scene images and videos based on fusion of discrete wavelet transform and gradient difference. A set of rules and geometric properties have been devised to localize the actual text regions. Then, morphological operation is performed to generate the text regions and finally the connected component analysis is employed to localize the text in a video frame. The experimental results obtained on publicly available standard ICDAR 2003 and Hua dataset illustrate that the proposed method can accurately detect and localize texts of various sizes, fonts and colors. The experimentation on huge collection of video databases reveal the suitability of the proposed method to video databases.Comment: Fifth International Conference on Signals and Image Processing, IEEE, DOI 10.1109/ICSIP.2014.50, pp. 280-284, held at BNMIT, Bangalore in January 201

Lossless Secret Image Sharing Schemes

Secret image sharing deals with splitting confidential images into several shares and the original image can be reconstructed from the qualified subset of the shares. Secret sharing schemes are used in transmission and storage of private medical images and military secrets. Increased confidentiality and availability are the major achievements. We propose an efficient (2, 2) scheme and (2, 3) scheme for secret image sharing. The scheme is lossless and also the share size is same as the secret size. The sharing and revealing phase uses simple modular arithmetic which can be very easily implemented. Experimental results on Binary and Gray scale images show that the proposed scheme is secure and efficient.Comment: International Journal of Computational Intelligence and Information Security Vol. 4 April 2013, ISSN: 1837-782

Fast Steganalysis Method for VoIP Streams

In this letter, we present a novel and extremely fast steganalysis method of Voice over IP (VoIP) streams, driven by the need for a quick and accurate detection of possible steganography in VoIP streams. We firstly analyzed the correlations in carriers. To better exploit the correlation in code-words, we mapped vector quantization code-words into a semantic space. In order to achieve high detection efficiency, only one hidden layer is utilized to extract the correlations between these code-words. Finally, based on the extracted correlation features, we used the softmax classifier to categorize the input stream carriers. To boost the performance of this proposed model, we incorporate a simple knowledge distillation framework into the training process. Experimental results show that the proposed method achieves state-of-the-art performance both in detection accuracy and efficiency. In particular, the processing time of this method on average is only about 0.05\% when sample length is as short as 0.1s, attaching strong practical value to online serving of steganography monitor.Comment: 5 pages, 2 figure

Deep Learning in Information Security

Machine learning has a long tradition of helping to solve complex information security problems that are difficult to solve manually. Machine learning techniques learn models from data representations to solve a task. These data representations are hand-crafted by domain experts. Deep Learning is a sub-field of machine learning, which uses models that are composed of multiple layers. Consequently, representations that are used to solve a task are learned from the data instead of being manually designed. In this survey, we study the use of DL techniques within the domain of information security. We systematically reviewed 77 papers and presented them from a data-centric perspective. This data-centric perspective reflects one of the most crucial advantages of DL techniques -- domain independence. If DL-methods succeed to solve problems on a data type in one domain, they most likely will also succeed on similar data from another domain. Other advantages of DL methods are unrivaled scalability and efficiency, both regarding the number of examples that can be analyzed as well as with respect of dimensionality of the input data. DL methods generally are capable of achieving high-performance and generalize well. However, information security is a domain with unique requirements and challenges. Based on an analysis of our reviewed papers, we point out shortcomings of DL-methods to those requirements and discuss further research opportunities

Image in Image Steganography based on modified Advanced Encryption Standard and Lest Significant Bit Algorithms

الستيكانوغرافي هو فن لإخفاء المعلومات او البيانات أو تضمينها في وسائط رقمية مختلفة مثل الصور، الفيديو، الصوت والنصوص. وان هناك الكثير من التقنيات لتحقيق عملية الإخفاء. في هذا البحث قمنا بحماية البيانات أو أي معلومات بطريقتين: التشفير والإخفاء. الغرض الأساسي من البحث هي تقديم طريقة تشفير مطورة للرسالة أولا باستخدام خوارزمية (التشفير القياسي المتقدم)AES   هو تشفير مفتاح متماثل حيث ان لكل شفرة من الشفرات بحجم كتلة 128 بت، حيث ان الأحجام الرئيسية هي  من 128، 192، 256 بت. ثانيا نقوم بإخفاء تلك الرسالة المشفرة في الحدود الخارجية للصورة الملونة (الإطار الخارجي للصورة الغلاف) باستخدام دالة LSB (البت الأقل اهمية) في ملفات الصورة الغلاف التي تكون بامتداد (bmp) أو(Jpeg) علما ان الخوارزمية الأخيرة تتسم بالضعف تجاه الهجمات لذلك تم تطويرها وتدعيمها بخوارزمية AES لزيادة الأمن ضد اي هجوم محتمل اثناء ارسالها عبر شبكة الانترنيت من المرسل الى المستلم.Because the big grown of the digital market and the growing demand for protection to data and information which transmitted through the Internet. Steganography is the art of embedding, hiding information into different digital media, it was the main reason to increase its importance in the exponential development of the secret communication of computer and digital cloud users over the internet. There are a lot of techniques and different ways to achieve hiding data. Usually, the data embedding is obtained in communication such as image, text, voice or any multimedia content for copyright and also in military communication for authentication and many other different purposes. In this paper, we protected the information in two ways: Encryption and Steganography. The basic idea is to present a method that encrypted the message firstly by using The AES (Advanced Encryption Standard) it is a symmetric-key encryption each of these ciphers it has 128-bit the size to block, and size keys of 128, 192 and 256 bits.  Secondly, hide that encrypted message in color cover image in the Least Significant Bit (LSB) to image’s frame with (.bmp, .jpg) extensions. Our scheme is to enhance the ability of LSB algorithm to include the storage of information and images encoded and intangible sense of human vision. That two methods to increased together the security attend any attack