Video Steganography Techniques: A Survey

In digital world, information security is the major issue in digital communication on a network from the third party hackers. Steganography techniques play an important role in information security. These are the secure techniques, used for concealing existence of secret information in any digital cover object viz. image, audio, video files. In last several decades, significant researches have been done on video and image steganography techniques because data embedding and data extraction is very simple. However, many researchers also take the audio file as a cover object where robustness and undetectability of information is very difficult task. The main objective of steganography is hiding the existence of the embedded data in any digital cover object. Steganography technique must be robust against the various image-processing attacks. Nowadays, video files are more accepted because of large size and memory requirements. This paper intends to provide a survey on video techniques and provide the fundamental concept of the steganography and their uses

Sensor Data Integrity Verification for Real-time and Resource Constrained Systems

Sensors are used in multiple applications that touch our lives and have become an integral part of modern life. They are used in building intelligent control systems in various industries like healthcare, transportation, consumer electronics, military, etc. Many mission-critical applications require sensor data to be secure and authentic. Sensor data security can be achieved using traditional solutions like cryptography and digital signatures, but these techniques are computationally intensive and cannot be easily applied to resource constrained systems. Low complexity data hiding techniques, on the contrary, are easy to implement and do not need substantial processing power or memory. In this applied research, we use and configure the established low complexity data hiding techniques from the multimedia forensics domain. These techniques are used to secure the sensor data transmissions in resource constrained and real-time environments such as an autonomous vehicle. We identify the areas in an autonomous vehicle that require sensor data integrity and propose suitable water-marking techniques to verify the integrity of the data and evaluate the performance of the proposed method against different attack vectors. In our proposed method, sensor data is embedded with application specific metadata and this process introduces some distortion. We analyze this embedding induced distortion and its impact on the overall sensor data quality to conclude that watermarking techniques, when properly configured, can solve sensor data integrity verification problems in an autonomous vehicle.Ph.D.College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttp://deepblue.lib.umich.edu/bitstream/2027.42/167387/3/Raghavendar Changalvala Final Dissertation.pdfDescription of Raghavendar Changalvala Final Dissertation.pdf : Dissertatio

A novel robust watermarking algorithm for encrypted medical image based on DTCWT-DCT and chaotic map

In order to solve the problem of patient information security protection in medical images, whilst also taking into consideration the unchangeable particularity of medical images to the lesion area and the need for medical images themselves to be protected, a novel robust watermarking algorithm for encrypted medical images based on dual-tree complex wavelet transform and discrete cosine transform (DTCWT-DCT) and chaotic map is proposed in this paper. First, DTCWT-DCT transformation was performed on medical images, and dot product was per-formed in relation to the transformation matrix and logistic map. Inverse transformation was undertaken to obtain encrypted medical images. Then, in the low-frequency part of the DTCWT-DCT transformation coefficient of the encrypted medical image, a set of 32 bits visual feature vectors that can effectively resist geometric attacks are found to be the feature vector of the encrypted medical image by using perceptual hashing. After that, different logistic initial values and growth parameters were set to encrypt the watermark, and zero-watermark technology was used to embed and extract the encrypted medical images by combining cryptography and third-party concepts. The proposed watermarking algorithm does not change the region of interest of medical images thus it does not affect the judgment of doctors. Additionally, the security of the algorithm is enhanced by using chaotic mapping, which is sensitive to the initial value in order to encrypt the medical image and the watermark. The simulation results show that the pro-posed algorithm has good homomorphism, which can not only protect the original medical image and the watermark information, but can also embed and extract the watermark directly in the encrypted image, eliminating the potential risk of decrypting the embedded watermark and extracting watermark. Compared with the recent related research, the proposed algorithm solves the contradiction between robustness and invisibility of the watermarking algorithm for encrypted medical images, and it has good results against both conventional attacks and geometric attacks. Under geometric attacks in particular, the proposed algorithm performs much better than existing algorithms

Oblivious data hiding : a practical approach

This dissertation presents an in-depth study of oblivious data hiding with the emphasis on quantization based schemes. Three main issues are specifically addressed: 1. Theoretical and practical aspects of embedder-detector design. 2. Performance evaluation, and analysis of performance vs. complexity tradeoffs. 3. Some application specific implementations. A communications framework based on channel adaptive encoding and channel independent decoding is proposed and interpreted in terms of oblivious data hiding problem. The duality between the suggested encoding-decoding scheme and practical embedding-detection schemes are examined. With this perspective, a formal treatment of the processing employed in quantization based hiding methods is presented. In accordance with these results, the key aspects of embedder-detector design problem for practical methods are laid out, and various embedding-detection schemes are compared in terms of probability of error, normalized correlation, and hiding rate performance merits assuming AWGN attack scenarios and using mean squared error distortion measure. The performance-complexity tradeoffs available for large and small embedding signal size (availability of high bandwidth and limitation of low bandwidth) cases are examined and some novel insights are offered. A new codeword generation scheme is proposed to enhance the performance of low-bandwidth applications. Embeddingdetection schemes are devised for watermarking application of data hiding, where robustness against the attacks is the main concern rather than the hiding rate or payload. In particular, cropping-resampling and lossy compression types of noninvertible attacks are considered in this dissertation work