Comprehensive Survey of Image Steganography: Techniques, Evaluations, and Trends in Future Research

Abstract Steganography is the science and art of covert communication. Conversely, steganalysis is the study of uncovering the steganographic process. The evolution of steganography has been paralleled by the development of steganalysis. In this game of hide and seek, the two player’s steganography and steganalysis always want to break the other down. Over the past three decades, research has produced a plethora of remarkable image steganography techniques (ISTs). The major challenge for most of these ISTs is to achieve a fair balance between the metrics such as high hiding capacity (HC), better imperceptibility, and improved security. This study aims to present an exhaustive scrutiny of various ISTs from the classical to recent developments in the spatial domain, with respect to various image steganographic metrics. Further, the current status, recent developments, open challenges, and promising directions in this field are also highlighted.

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Digital image steganography and steganalysis: A journey of the past three decades

The development of information technology has led to a significant increase in the share of multimedia traffic in data networks. This has necessitated to solve the following information security tasks in relation to multimedia data: protection against leakage of confidential information, as well as identifying the source of the leak; ensuring the impossibility of unauthorized changes; copyright protection for digital objects. To solve such kind of problems, methods of steganography and watermarking are designed that implement embedding in digital objects hidden information sequences for various purposes. In this paper, an overview of promising research in the specified area is provided. First of all, we provide basic information about this field of research and consider the main applications of its methods. Next, we review works demonstrating current trends in the development of methods and algorithms for data hiding in digital images. This review is not exhaustive; it focuses on contemporary works illustrating current research directions in the field of information embedding in digital images. This is the main feature of review, which distinguishes it from previously published reviews. The paper concludes with an analysis of identified problems in the field of digital steganography and digital watermarking.

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Digital steganography and watermarking for digital images: a review of current research directions

Cloud computing is one of the largest developments in the field of information technology during recent years. It is a service oriented computing which offers everything as a service via the internet by the pay-as-you-go model. It becomes more desirable for all organizations (such as education, banking, healthcare and manufacturing) and also for personal use as it provides a flexible, scalable, and reliable infrastructure and services. For the user, the most important issue is to store, retrieve and transmit the data over the cloud network and storage in a secure manner. Steganography and cryptography are some of the security techniques applied in the cloud to secure the user data transmitting. The objective of steganography is to hide the existence of communication from the unintended users; whereas cryptography encrypts the data to make it more secure. Steganography is considered as the most effective technique for securing the communication in the cloud. Digital images are most commonly used as a cover medium in steganography. In the literature, there exist several image steganography techniques for hiding information in images; which were developed and implemented in the time domain as well as in the frequency domain. Fundamentals of spatial domain and frequency domain techniques are reviewed in this paper with emphasis on the Least Significant Bit (LSB) and the Discrete Cosine Transform (DCT) techniques.

Data Security in Cloud Computing Using Steganography: A Review

Improved image steganography based on super-pixel and coefficient-plane-selection

Information security is one of the most important processes and methodologies which have to be considered when any information is communicated secretly between two parties. Cryptography and steganography are the two important practices used for this purpose. Cryptography changes the secret message into unintelligible text; however, it reveals the existence of the secret message. Steganography technique on the other hand hides the secret message such that no one can notice the presence of it. Current paper presents an image steganographic technique exploiting fuzzy logic edge detection and chaotic method. The fuzzy logic approach for image processing allows defining the degree to which a pixel belongs to an edge. Least significant bit substitution approach is used for data hiding in the carrier image. The combination of chaotic theory with steganography is emerging and gets attracted by researchers. Chaotic method is applied to the original message to generate the random sequence of binary equivalent secret message which prevents the secret message from attackers. The proposed method hides large amount of data with good quality of stage image of the human visual system and guarantees the confidentiality in the communication. The experimental results shows better peak signal-to-noise ratio, image quality index and payload for evaluating the stego image compared to the existing methods.

Image Steganography Using Fuzzy Logic and Chaotic for Large Payload and High Imperceptibility

Researchers all across the world have been working extensively for developing system in health care domain. Many people are struggling to clear their doubts about health issues by doctors or other medical personnel to confirm or clarify their diagnosis. The health management system is an end user support and online consultation system. The system is fed with counts of various pigments and chemicals present in an individual’s body which are necessary for determining liver health. Four algorithms have been implemented for this. This paper summarizes the predicted accuracy, precision and F-score of various machine learning algorithms and compares them to find the best suited algorithm to predict the impact of the liver diseases.

Analytical Comparison of Machine Learning Techniques for Liver Dataset

A Green city enables the perfect usage of resources and more dependable quality of services to the masses. To supply inspection and repairs such as air quality management, weather monitoring and automation of homes and edifices in a smart city, the basic parameters are humidity, water level temperature, gas level. This task delivers a customized blueprint of an Internet of Things (IoT) enabled environment monitoring system to monitor temperature, water point, humidity and gas level. In developed system, information is transmitted from the transmitter tx node to the receiver rx node using the Bluetooth sensor module. The data received at the receiver node is entered in a database and is monitored as logs into a personal data processor (PC) through an Arduino IDE. An Android application has also been broken through which information is transferred from Arduino IDE to a smartphone, for monitoring data remotely. The settlements and the carrying out of the proposed strategy is discussed.

Real Time Weather Monitoring using Internet of Things

In the era of technology, where for almost everything we are dependent on the internet, has been successful enough to dominate our social lives too. So, with excess usage of internet, creating huge log files containing hidden valuable information in it. Hence efforts have been made to overcome the shortcomings of log management and perform effective search to extract the real crux from pool of data which is needed for analysis. Further we require an efficient graphical visualizer which can completely express any shape of data. This paper demonstrates the working of open source tools i.e. elasticsearch, logstash, and kibana which has been clubbed together to have complete insight and visualization of data. Elastic search is used for searching and indexing, Logstash for slicing and dicing the raw data, maintaining and managing events whereas kibana is a graphical front end for data held in elasticsearch. By implementing these tools we are performing sentiment analysis of data taken from social networking blogging service like twitter.

C. Vanmathi

Papers

Image Steganography Using Fuzzy Logic and Chaotic for Large Payload and High Imperceptibility

Analytical Comparison of Machine Learning Techniques for Liver Dataset

Real Time Weather Monitoring using Internet of Things

Twitter Sentiment Analysis Using Elasticsearch, LOGSTASH And KIBANA

Optimization driven model and segmentation network for skin cancer detection