The document provides an introduction to image encryption using AES key expansion. It discusses how traditional encryption techniques are not well-suited for encrypting large multimedia files like images due to their size and characteristics. The objective of the study is to develop an image encryption system that is computationally secure, fast enough for real-time use, and widely acceptable. It reviews related works in image encryption and discusses limitations of only using a 128-bit AES key. The document is organized into chapters covering cryptography fundamentals, image cryptosystems, AES algorithm details, an example of AES key expansion, and experimental analysis.
This is a project dealing with securing images over a network.
Image is a delicate piece of information shared between clients across the world.Cryptography plays a huge role during secure connections.Applying simple Gaussian elimination to achieve highly secured image encryption decryption technique is a interesting challenge.
This is a project dealing with securing images over a network.
Image is a delicate piece of information shared between clients across the world.Cryptography plays a huge role during secure connections.Applying simple Gaussian elimination to achieve highly secured image encryption decryption technique is a interesting challenge.
This is a Presentation On use of AES Algorithm To Encrypt Or Decrypt a Text File. This Algorithm is the latest and better than DES. It is a Networking Presentation. Thank You.
Steganography is the art and science of sending covert messages such that the existence and nature of such a message is only known by the sender and intended recipient.
Steganography has been practised for thousands of years, but in the last two decades steganography has been introduced to digital media. Digital steganography techniques typically focus on hiding messages inside image and audio files; in comparison, the amount of research into other digital media formats (such as video) is substantially limited.
In this talk we will discuss the history of steganography and the categories of steganographic technique before briefly discussing image and audio steganography and how to build such tools. The main body of our talk will focus on how video files are coded and the steganographic techniques that can be used to hide messages inside video files.
The principles discussed in this talk will be illustrated with live demos.
Project consists of individual modules of encryption and decryption units. Standard T-DES algorithm is implemented. Presently working on to integrate DES with AES to develop stronger crypto algorithm and test the same against Side Channel Attacks and compare different algorithms.
Steganography is the practice of concealing a file, message, image, or video within another file, message, image, or video. The word steganography combines the Greek words steganos meaning "covered, concealed, or protected", and graphein meaning "writing".
The first recorded use of the term was in 1499 by Johannes Trithemius in his Steganographia, a treatise on cryptography and steganography, disguised as a book on magic. Generally, the hidden messages appear to be (or be part of) something else: images, articles, shopping lists, or some other cover text. For example, the hidden message may be in invisible ink between the visible lines of a private letter. Some implementations of steganography that lack a shared secret are forms of security through obscurity, whereas key-dependent steganographic schemes adhere to Kerckhoffs's principle.
The advantage of steganography over cryptography alone is that the intended secret message does not attract attention to itself as an object of scrutiny. Plainly visible encrypted messages—no matter how unbreakable—arouse interest, and may in themselves be incriminating in countries where encryption is illegal.Thus, whereas cryptography is the practice of protecting the contents of a message alone, steganography is concerned with concealing the fact that a secret message is being sent, as well as concealing the contents of the message.
Steganography includes the concealment of information within computer files. In digital steganography, electronic communications may include steganographic coding inside of a transport layer, such as a document file, image file, program or protocol. Media files are ideal for steganographic transmission because of their large size. For example, a sender might start with an innocuous image file and adjust the color of every 100th pixel to correspond to a letter in the alphabet, a change so subtle that someone not specifically looking for it is unlikely to notice it.
Using this software any 50 sec audio message can be decrypted into image file and then original message can again be recovered from image file. This project is coded in Matlab and gui is also built in Matlab.
This is a Presentation On use of AES Algorithm To Encrypt Or Decrypt a Text File. This Algorithm is the latest and better than DES. It is a Networking Presentation. Thank You.
Steganography is the art and science of sending covert messages such that the existence and nature of such a message is only known by the sender and intended recipient.
Steganography has been practised for thousands of years, but in the last two decades steganography has been introduced to digital media. Digital steganography techniques typically focus on hiding messages inside image and audio files; in comparison, the amount of research into other digital media formats (such as video) is substantially limited.
In this talk we will discuss the history of steganography and the categories of steganographic technique before briefly discussing image and audio steganography and how to build such tools. The main body of our talk will focus on how video files are coded and the steganographic techniques that can be used to hide messages inside video files.
The principles discussed in this talk will be illustrated with live demos.
Project consists of individual modules of encryption and decryption units. Standard T-DES algorithm is implemented. Presently working on to integrate DES with AES to develop stronger crypto algorithm and test the same against Side Channel Attacks and compare different algorithms.
Steganography is the practice of concealing a file, message, image, or video within another file, message, image, or video. The word steganography combines the Greek words steganos meaning "covered, concealed, or protected", and graphein meaning "writing".
The first recorded use of the term was in 1499 by Johannes Trithemius in his Steganographia, a treatise on cryptography and steganography, disguised as a book on magic. Generally, the hidden messages appear to be (or be part of) something else: images, articles, shopping lists, or some other cover text. For example, the hidden message may be in invisible ink between the visible lines of a private letter. Some implementations of steganography that lack a shared secret are forms of security through obscurity, whereas key-dependent steganographic schemes adhere to Kerckhoffs's principle.
The advantage of steganography over cryptography alone is that the intended secret message does not attract attention to itself as an object of scrutiny. Plainly visible encrypted messages—no matter how unbreakable—arouse interest, and may in themselves be incriminating in countries where encryption is illegal.Thus, whereas cryptography is the practice of protecting the contents of a message alone, steganography is concerned with concealing the fact that a secret message is being sent, as well as concealing the contents of the message.
Steganography includes the concealment of information within computer files. In digital steganography, electronic communications may include steganographic coding inside of a transport layer, such as a document file, image file, program or protocol. Media files are ideal for steganographic transmission because of their large size. For example, a sender might start with an innocuous image file and adjust the color of every 100th pixel to correspond to a letter in the alphabet, a change so subtle that someone not specifically looking for it is unlikely to notice it.
Using this software any 50 sec audio message can be decrypted into image file and then original message can again be recovered from image file. This project is coded in Matlab and gui is also built in Matlab.
This PPT explains about the term "Cryptography - Encryption & Decryption". This PPT is for beginners and for intermediate developers who want to learn about Cryptography. I have also explained about the various classes which .Net provides for encryption and decryption and some other terms like "AES" and "DES".
This design involves the implementation AES 128. Inside top module, enc, dec and key_generation modules are available. Both enc and dec are controlled via respective resets. When enc executes, key_generation runs and further fills the key memory. dec unit on its execution extracts key from the same memory. Working on to test the design with Side Channel Attacks.
Abstract Security in transmission of digital images has its importance in today’s image communications, due to the increasing use of images in industrial process, it is essential to protect the confidential image data from unauthorized access, Image security has become a critical issue. The difficulties in ensuring individuals privacy become increasingly challenging. Various methods have been investigated and developed to protect data and personal privacy. Encryption is probably the most obvious one. In order to protect valuable information from undesirable readers, image encryption is essential. This paper presents an application of AES (Advanced Encryption Standard) operations in image encryption and decryption. The encrypted cipher images always display the uniformly distributed RGB pixels. Index Terms: Security, Image Processing, AES, Encryption and Decryption
Unified Approach With Neural Network for Authentication, Security and Compres...CSCJournals
The Present demands of scientific and social life forced image processing based applications to have a tremendous growth. This growth at the same time has given numbers of challenges to researcher to meet the desired objectives of either users or from solution perspectives. Among the various challenges, the most dominating areas are: reduction in required memory spaces for storage or taken transmission time from one location to other, protection of image contents to maintain the privacy and to facilitate the mechanism to identify the malicious modification if there is any either in storage or in transmission channel. Even though there are number of methods proposed by various researchers and are existed as solutions, questions are remain open in terms of quality, cost and complexity. In this paper we have proposed the concept based on neural network to achieve the quality of compression, protection and authentication all together using the ability of universal approximation by learning, one way property and one to one mapping characteristics correspondingly. With the proposed methods not only we can authenticate the image but also positions of malicious activity given in the image can be located with high precision. Proposed methods are very efficient in performance as well as carry the features of simplicity and cost effectiveness.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
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International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
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Survey on Different Image Encryption Techniques with Tabular Formijsrd.com
Rapid growth of digital communication and multimedia application increases the need of security and it becomes an important issue of communication and storage of multimedia. Image Encryption is one of the techniques that are used to ensure high security. Various fields such as medical science military in which image encryption can be used. Recent cryptography provides necessary techniques for securing information and protective multimedia data. In last some years, encryption technology has been developed quickly and many image encryption methods have been used to protect confidential image data from illegal way in. Within this paper survey of different image encryption techniques have been discussed from which researchers can get an idea for efficient techniques to be used.
SELECTIVE ENCRYPTION OF IMAGE BY NUMBER MAZE TECHNIQUEijcisjournal
Due to enormous increase in the usage of computers and mobiles, today’s world is currently flooded with huge volumes of data. This paper is primarily focused on multimedia data and how it can be protected from unwanted attacks. Sharing of multimedia data is easy and very efficient, it has been a customary practice to share multimedia data but there is no proper encryption technique to encrypt multimedia data. Sharing of multimedia data over unprotected networks using DCT algorithm and then applying selective encryption-based algorithm has never been adequately studied. This paper introduces a new selective encryption-based security system which will transfer data with protection even in unauthenticated network. Selective encryption-based security system will also minimize time during encryption process which there by achieves efficiency. The data in the image is transmitted over a network is discriminated using DCT transform and then it will be selectively encrypted using Number Puzzle technique, and thus provides security from unauthorized access. This paper discusses about numeric puzzle-based encryption technique
and how it can achieve security and integrity for multimedia data over traditional encryption technique.
Design and Implementation of Data Hiding Technique by Using MPEG Video with C...Editor IJMTER
This paper proposes a technique on data hiding approaches using compressed MPEG video files.
This approach hides the message bits by modulating the quantization scale of constant bit rate MPEG
videos. Payload is calculated for each macroblock and proposes to achieve one message bit per
macroblock. Macroblock level feature variables are calculated.To find the association between
macroblock level feature variables and value of a hidden message bit, a Second Order Multivariate
regression model is used. To achieve the very high prediction accuracy, the regression model is used by
the decoder. To decode the message, a feature variable of MBs from the encoded bit stream are computed
by the decoder and expands them to the second order and uses the model weights to predict the message
bits. This solution provides very high precision accuracy in predicting the message bits . The proposed
technique is analyzed in term of quality distortion, excessive bit rate, message pay load and message
extraction accuracy. The proposed solution is better in terms of message payload while causing the less
distortion and reduced compression overheads compare to the previous works.
PERFORMANCE ANALYSIS OF TEXT AND IMAGE STEGANOGRAPHY WITH RSA ALGORITHM IN CL...ijseajournal
Cloud computing provides a lot of shareable resources payable on demand to the users. The drawback with
cloud computing is the security challenges since the data in the cloud are managed by third party. Steganography and cryptography are some of the security measures applied in the cloud to secure user data. The objective of steganography is to hide the existence of communication from the unintended users whereas cryptography does provide security to user data to be transferred in the cloud. Since users pay for
the services utilize in the cloud, the need to evaluate the performance of the algorithms used in the cloud to
secure user data in order to know the resource consumed by such algorithms such as storage memory, network bandwidth, computing power, encryption and decryption time becomes imperative. In this work, we implemented and evaluated the performance of Text steganography and RSA algorithm and Image steganography and RSA as Digital signature considering four test cases. The simulation results show that, image steganography with RSA as digital signature performs better than text steganography and RSA algorithm. The performance differences between the two algorithms are 10.76, 9.93, 10.53 and 10.53 seconds for encryption time, 60.68, 40.94, 40.9, and 41.85 seconds for decryption time, 8.1, 10.92, 15.2 and 5.17 mb for memory used when hiding data, 5.3, 1.95 and 17.18 mb for memory used when extracting data, 0.93, 1.04, 1.36 and 3.76 mb for bandwidth used, 75.75, 36.2, 36.9 and 37.45 kwh for processing power used when hiding and extracting data respectively. Except in test case2 where Text steganography and RSA algorithm perform better than Image Steganography and RSA as Digital Signature in terms of memory used when extracting data with performance difference of -5.09 mb because of the bit size of the image data when extracted. This research work recommend the use of image steganography and RSA as digital signature to cloud service providers and users since it can secure major data types such as text, image, audio and video used in the cloud and consume less system resources.
Hybrid information security system via combination of compression, cryptogra...IJECEIAES
Today, the world is experiencing a new paradigm characterized by dynamism and rapid change due to revolutions that have gone through information and digital communication technologies, this raised many security and capacity concerns about information security transmitted via the Internet network. Cryptography and steganography are two of the most extensively that are used to ensure information security. Those techniques alone are not suitable for high security of information, so in this paper, we proposed a new system was proposed of hiding information within the image to optimize security and capacity. This system provides a sequence of steps by compressing the secret image using discrete wavelet transform (DWT) algorithm, then using the advanced encryption standard (AES) algorithm for encryption compressed data. The least significant bit (LSB) technique has been applied to hide the encrypted data. The results show that the proposed system is able to optimize the stego-image quality (PSNR value of 47.8 dB) and structural similarity index (SSIM value of 0.92). In addition, the results of the experiment proved that the combination of techniques maintains stego-image quality by 68%, improves system performance by 44%, and increases the size of secret data compared to using each technique alone. This study may contribute to solving the problem of the security and capacity of information when sent over the internet.
A novel chaotic system for Video Cryptography using 2D logistics Sine-Cosine ...IJERA Editor
The astonishing developments have been occurring in the field of network communications for a long time and
these advancement lead to a genuine and conspicuous need of image transfer and getting safely through the web.
The web is not secure for the exchange of dependable data, for example, content, picture and video.
Cryptographic procedures are vital to be improved to exchange data through web safely. Routine cryptography,
for example, AES, DES, IDEA and RSA includes simply rearranging of pixels and henceforth will prompt
decreased security for information protection. With a specific end goal to enhance the security, it is important to
expand the intricacy in encryption. As an answer for this it is proposed to utilize confused maps in encryption
methods which expand the multifaceted nature. As intricacy builds, data security increments. Thus, chaos-based
encryption has its own significance in providing security for secret information i.e. data confidentiality than
conventional.
Similar to Image encryption using aes key expansion (20)
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
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• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
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https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
DevOps and Testing slides at DASA ConnectKari Kakkonen
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JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
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State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
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Cyberattack types and targets
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In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
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UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
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The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
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1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
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Execution from the test manager
Orchestrator execution result
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SAP heatmap example with demo
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Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
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We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
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Your campaign sent to target colleagues for approval
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Image encryption using aes key expansion
1. Image Encryption using AES Key Expansion Seminar Report 2013
Department of Telecommunication Engineering,
PACE, Mangalore. Page 1
CHAPTER 1
Introduction
This chapter gives a brief introduction to Image Encryption and its advantages. The topics
covered are: Introduction to Image Encryption, Problem statement, Objective and scope
of Study, Literature Review and the need for proposed algorithm. Finally, limitations of
the study and organisation of chapters in this report are given.
1.1 General Introduction
A major issue for computer networks is to prevent important information from
being disclosed to illegal users. For this reason, encryption techniques were introduced.
Most encryption techniques have an easy implementation and are widely used in the field
of information security.
During the last decade, the use of computer networks has grown spectacularly,
and this growth continues unabated. New networks are being installed and connected to
global internet. The internet is commonly seen as the first incarnation of an information
superhighway. Today, the information transmitted over internet is not only text, but also
contains multimedia like image, audio etc. Mostly images are used. However, the more
extensively the images are used, the more important their security will be. For example, it
is important to protect military image databases, ensure confidential video conferencing,
and protect personal online photograph albums.
However, with the growth of computer processor processing power and storage,
illegal access has become easier. As a result image security has become an important
topic in the current computer world.
Most traditional or modern cryptosystems have been designed to protect textual
data. The original plain-text is converted into cipher-text (hidden form of message) which
is stored or transmitted over network. Upon reception, the cipher-text can be transformed
back into the original plain-text by using a decryption algorithm.
2. Image Encryption using AES Key Expansion Seminar Report 2013
Department of Telecommunication Engineering,
PACE, Mangalore. Page 2
However images are different from text. Although the traditional cryptosystems,
such as RSA and DES-like cryptosystems may be used, to encrypt images directly, it is
not a good idea for two reasons.
One is that the image size is always much greater than that of text. Therefore,
the traditional cryptosystems need much time to directly encrypt the image
data.
The second is that, the decrypted text must be equal to that of original text.
However, this requirement is not necessary for image data. This is due to the
characteristics of human perception; a decrypted image containing small
distortion is usually acceptable.
A digital image is defined as a two dimensional (2D) rectangle array. The
elements of this array are denoted as pixels. Each pixel has an intensity value (digital
number) and a location address (row, column).
An image can be encrypted by combining MATLAB with the encoder. Each pixel
in an image is represented by 8 bits, i.e., 1 byte. Using MATLAB the pixel values can be
converted into bytes. These byte values are then used as input to the encoder. The 128 bit
encoder then convert this byte into corresponding encoded byte. The encoded bit values
are then converted into decimal values for pixels. This operation is then repeated for each
pixel to generate a 2D text array corresponding to the pixel value.
For protecting the stored 2D data, they must be converted to one dimensional (1D)
arrays before using various traditional encryption techniques. The raster sequence of
image data can be encrypted into blocks by using block cipher or a stream cipher. A
product cipher can also be used to encrypt a file of image data. However, it is more
efficient to encrypt an image after employing some compression techniques. This will
reduce the computational requirement and also the increases the speed of processing
(which is of high importance in real time scenario).
1.2Problem Statement
The two main problems that arise in image encryption process are with respect to
the time it takes for its computation and its security level. For real time image encryption
only those ciphers are preferable which takes lesser amount of computational time
3. Image Encryption using AES Key Expansion Seminar Report 2013
Department of Telecommunication Engineering,
PACE, Mangalore. Page 3
without compromising security. An encryption scheme which runs very slowly, even
though may have higher degree of security features would be of little practical use for real
time processes. Hence a trade off has to be made.
Many encryption methods have been proposed in literature, and the most common
way to protect large multimedia files is by using conventional encryption techniques.
Private Key bulk encryption algorithms, such as Triple DES or Blowfish, are not suitable
for transmission of large amounts of data (such as images). Due to the complexity of their
internal structure, they are not particularly fast in terms of execution speed and cannot be
applied for images in the real time scenario. Also traditional cryptographic techniques
such as DES cannot be applied to images due to the intrinsic properties of images such as
bulk data capacity, redundancy and high correlation among pixels. Image encryption
algorithms can become an integral part of the image delivery process if they aim towards
efficiency and at the same time preserve the security level.
1.3 Objective of the Study
The three basic characteristics in the information security field: privacy (an
unauthorized user cannot disclose a message), integrity (an unauthorized user cannot
modify or corrupt a message) and availability (messages are made available to authorized
users faithfully).
A perfect image cryptosystem is not only flexible in the security mechanism, but
also has high overall performance.
The objective of this study is to realise an image cryptosystem that, besides the
above mentioned characteristics, also posses the following characteristics:
i. System should be computationally secure i.e., it should have an extremely long
computation time to break. In other words unauthorized users must not be able to
read privileged images.
ii. Encryption and decryption should be fast enough not to degrade system
performance. i.e., the algorithm should be simple enough to be done by users with
a personal computer.
iii. The security mechanism should be widely acceptable to design a cryptosystem
like a commercial product; and should be flexible.
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1.4 Related Works
Due to the differences between images and text, a wide variety of cryptographic
algorithms have been proposed for image security.
In the paper [2], Kuo proposed an image encryption method - image distortion, which
obtains the encrypted image by adding the phase spectra of the plain image with those of
the key image. This method is safe but the image is not compressed, thus encryption &
decryption is inefficient.
In the paper [3], Bourbakis and Alexopoulos developed a new method which performs
both lossless compression and encryption of binary and gray-scale images. The
compression and encryption schemes are based on SCAN patterns generated by the
SCAN technique. SCAN is a formal language-based two-dimensional spatial- access
methodology which can efficiently specify and generate a wide range of scanning paths
or space filling curves. Here again security is high but no image compression is
considered.
In the paper [4], Chin-Chen Chang, Min-Shian Hwang, and Tung-Shou Chen used one of
the popular image compression techniques, vector quantization, to design an efficient
cryptosystem for images. The scheme is based on vector quantization (VQ),
cryptography, and other number theorems. In VQ, the images are first decomposed into
vectors and then sequentially encoded vector by vector. Major advantage- simple
hardware structure; required bit-rate for VQ is also small.
In the paper [5], Fridrich demonstrated the construction of a symmetric block encryption
technique based on 2D standard chaotic map. In this paper to encrypt large data files
private-key symmetric block encryption schemes are used because public key encryption
schemes are not suitable for encrypting of large amounts of data and archival due to their
relatively slow performance. Also, the security of public key cryptographic schemes lies
in the computational complexity of certain problems, such as factorization of large
numbers or computing of the discrete logarithm problem. Advances in algorithmic
techniques, number theory force us to re-encrypt large databases and archives with a
longer key to maintain a sufficient degree of security. Here a chaotic map is first
generalized by introducing parameters and is then discretized to a finite square lattice of
points (image) which represent data items (pixel). The discretized map is further extended
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to three dimensions and composed with a simple diffusion mechanism to obtain a block
product encryption scheme. The main features of the encryption scheme studied in this
paper are a variable key length, a relatively large block size (several kB or more), and a
high encryption rate. However, the drawback here is the choices for the ciphering key
depend on the block size. Files with size smaller than 10kB would have to be padded to
guarantee sufficiently many encryption keys which will increase the size of the data to be
transmitted.
In the paper [6], Mitra had used a random combination of bit, pixel, and block
permutations. The permutation of bits decreases the perceptual information, whereas the
permutation of pixels and blocks produce high level security.
1.5 Limitation of the study
The algorithm for Image Encryption used here is based on 128-bit AES Key
Expansion. To increase the key space 192-bit/256-bit AES Algorithm may be used
in future.
Also the S-box used here provides only 70% non linearity to algorithm. Sbox with
better non linearity may be designed in future to increase the avalanche effect of
encrypted Image.
1.6 Chapter Organisation
The first 2 Chapters of this report, discusses the theoretical concepts required to
understand the image encryption and its importance. The next 4 chapters deal with
introduction to image cryptosystems and the proposed method to overcome the problems
faced in real time implementation of image cryptosystems. Last chapter deals with
Experimental analysis of proposed method and comparative results. The list of chapters
and brief description of their contents is given below.
Chapter 1: Gives the brief idea of image encryption requirements. It explains the
scope, literature survey, methodology and overall general view of this study.
Chapter 2: Gives a brief background to cryptography and some of the common
terms used in cryptography. It also discusses about the different types of cryptographies
and the types cryptanalysis attacks possible on images.
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Chapter 3: Gives a brief overview of some of the image cryptosystem
implemented so far, its efficiency and drawback in regard to real time application.
Chapter 4, 5 ,6 & 7 : In these chapters, AES standard, mathematical preliminaries
required to understand AES Algorithm, AES algorithm with the transformations used and
Key expansion schedule ,An example for AES Key Expansion and modification to AES
Key Expansion to suite Image Cryptosystems in real time application have been
explained. The chapter 7 gives Experimental analysis and results of proposed method.
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CHAPTER 2
Basics of Cryptography
This chapter just gives a basic idea about cryptography and its types, so that the concepts
in image cryptosystems can be understood better. The topics covered are: Definition of
cryptography and cryptanalysis, types of cryptography, types of cryptanalysis attacks for
evaluating the security of image cryptosystems.
2.1 Terms Used in Cryptography
―Cryptography‖ is the science of using mathematics to encrypt and decrypt data. It
enables us to store sensitive information or transmit it across insecure networks (like the
Internet) so that it cannot be read by anyone except the intended recipient.
While cryptography is the science of securing data, ―cryptanalysis‖ is the science
of analyzing and breaking secure communication. Classical cryptanalysis involves an
interesting combination of analytical reasoning, application of mathematical tools, pattern
finding, patience, determination, and luck. Cryptanalysts are also called as attackers.
Cryptology embraces both cryptography and cryptanalysis.
Cryptography can be strong or weak; its strength is measured in the time and
resources it would require to recover the plain-text. The result of strong cryptography is
cipher-text that is very difficult to decipher without possession of the appropriate
decoding tool.
A cryptographic algorithm, is a mathematical function used in the encryption and
decryption process. it works in combination with a key—a word, number, or phrase—to
encrypt the plain-text. The same plain-text encrypts to different cipher-text with different
keys. The security of encrypted data is thus entirely dependent on two things: the strength
of the cryptographic algorithm and the secrecy of the key.
A cryptographic algorithm, plus all possible keys and all the protocols that make it
work comprise a ―cryptosystem‖.
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2.2 Types of cryptography
Cryptography is usually of two types based the type of key used. They are: Secret
key & Public key Cryptography.
2.2.1 Secret key Cryptography
It is also known as Conventional or Symmetric Cryptography.
Here same key is used for encryption & decryption as shown in figure 2.2.1(a).
Example: DES (Data Encryption Standard).
Figure 2.1 Conventional encryption/decryption.
Advantages of conventional cryptography are,
i. It is very fast.
ii. It is especially useful for encrypting data that is to be stored securely and
not transmitted.
Main problem in conventional or secret key cryptography is ―Key Distribution‖.
For a sender and recipient to communicate securely using conventional
encryption, they must agree upon a key and keep it secret between themselves. If
they are in different physical locations, they must use some secure communication
medium to prevent the disclosure of the secret key during transmission else a third
party intercepting the key in transit can later read, modify or forge all information
encrypted.
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2.2.2 Public Key Cryptography
The problems of key distribution are solved by public key cryptography.
It is an asymmetric scheme which uses a pair of keys for encryption: ―public key‖,
which encrypts the data and a corresponding ―private key‖ or ―secret key‖, which
decrypts the data.
Here the public key is published to the world but private key is kept a secret i.e.,
anyone with the copy of public key can encrypt information whereas decryption
can only be done with the knowledge of private key.
It is computationally infeasible to deduce the private key from the public key.
Anyone who has a public key can encrypt information but cannot decrypt it. Only
the person who has the corresponding private key can decrypt the information.
Example: RSA (named after its inventors, Ron Rivest, Adi Shamir, and Leonard
Adleman)
Figure 2.2 Public key Encryption/Decryption
Advantages of Public Key Cryptography are,
i. The primary benefit of public key cryptography is that it allows people
who have no pre-existing security arrangement to exchange messages
securely.
ii. The need for sender and receiver to share secret keys via some secure
channel is eliminated; all communications involve only public keys, and
no private key is ever transmitted or shared.
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2.3 Types of Cryptanalysis Attacks for Evaluating the
Security of Image Cryptosystems
The following five attacks are used for evaluating the security of image
cryptosystems. Each of them assumes that the cryptanalyst has the complete knowledge
of the encryption algorithm used.
The first attack is called the cipher-image-only or brute force attack. In this attack,
an illegal user is assumed to obtain the cipher-image from networks, but does not have the
private key. In other words, a cryptanalyst must determine the private key solely from an
intercepted cipher-image.
The second attack is called the known-plain-image-only attack. The illegal users
are assumed to have obtained several plain-image and cipher-image pairs in this attack. A
cryptanalyst must deduce the private key used to encrypt the plain images or the
algorithm to decrypt any new cipher image encrypted with same private key.
The third attack is called the chosen plain-image attack. In this attack, the illegal
users are able to select the plain-images and obtain the corresponding cipher-images this
is more powerful than the known-plain-image-only attack, because cryptanalysts can
choose some specific pain-images to encrypt, and this yields more information about the
private key. The cryptanalysts uses this information to deduce the private key used to
encrypt the plain images.
The fourth attack is called jigsaw puzzle attack. In this attack, the illegal users first
divide a cipher-image into many small areas. The cryptanalysts then breaks these areas
one by one. Since each area is much smaller than the entire cipher-image, the
computational load for breaking each area is much less than that for breaking the entire
cipher-image. The jigsaw puzzle attack is therefore more efficient than other attacks.
The fifth attack is called the neighbour attack. In this attack, the illegal users are
assumed to know a part of the plain-image. The changes across the boundaries of the
areas are smooth in most images. Therefore, the cryptanalysts use this attribute to speed
up the selections for the boundaries of the neighbouring areas; and can derive the
neighbouring pixels for the known part of plain image and break the whole cipher
efficiently.[3]
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CHAPTER 3
Efficiency and Security of Some Image Cryptosystems
This chapter gives brief explanation about the techniques previously applied to solve
problems related to real time image encryption. This chapter covers the topics: Image
Encryption Using SCAN Patterns, Image Encryption Using Combinational Permutation
Techniques, and the need for AES based method.
3.1 Image Encryption Using SCAN Patterns
Due to the differences between images and text, a wide variety of cryptographic
algorithms have been proposed for image security.
In the paper [3], Bourbakis and Alexopoulos developed a new method which
performs encryption of binary and gray-scale images. The encryption schemes are based
on SCAN patterns generated by the SCAN technique. This method converts 2D image
patterns into 1D list & employs a SCAN language to describe the converted result. SCAN
is a formal language based 2D spatial accessing methodology which can efficiently
specify and generate a wide range of scanning paths. In this language there are several
SCAN letters & each letter represents a scan order. The four basic SCAN patterns used by
SCAN language are: Continuous raster (C), Continuous diagonal (D), Continuous
orthogonal (O) and Spiral (S).These four patterns are shown in figure 3.1.
Figure 3.1 Basic SCAN patterns [3]
Different combinations of SCAN letters generate different kind of secret images.
Once the combination of SCAN letters is determined, the scheme generates a SCAN
string which defines the SCAN order of the original image. The algorithm then scans the
image and encrypts the SCAN string using commercial cryptosystems. Since illegal users
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cannot obtain correct SCAN string, the original image is therefore secure. Figure 3.2
shows an example of SCAN key patterns.
Figure 3.2 Example of SCAN key pattern—B5(s2Z0(c5b0o0s5)c4d1) [3]
Drawbacks of Image Encryption using SCAN patterns are,
This method does not consider the advantages of image compression. As a result,
the size of the image is very large and is inefficient to encrypt or decrypt images
directly for real time applications.
Also, due to large image size encryption/decryption process is consumes lot of
time and hence is slow.
Although it provides fair enough security it is not preferred for real time
application because the time taken by this method to produce cipher image is not
acceptable for real time scenerio.
3.2 Image Encryption Using Combinational Permutation
Techniques
In the paper [6] Mitra presents an approach using a combinational permutation
techniques for image encryption. This technique uses a random combination of bit, pixel,
and block permutations. The permutation of bits decreases the perceptual information,
whereas the permutation of pixels and blocks produce high level security. It is observed
that the permutation of bits is effective in significantly reducing the correlation thereby
decreasing the perceptual information, whereas the permutation of pixels and blocks are
good at producing higher level security compared to bit permutation. A random
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combination method employing all the three techniques thus is observed to be useful for
tactical security applications, where protection is needed only against a casual observer.
The security of images used in electronic communication may be needed against
two types of attackers; casual listeners/observers or professional unauthorized recipients,
termed as cryptanalysts. In the former case, the security is needed only in terms of hours
while in the later it may be in terms of years. The duration roughly indicates the amount
of time that is needed to analyze the information available in unintelligible form in the
insecure channel without the knowledge of keys to derive the underlying information.
The scenario where security is needed against casual listener/observer, the
cryptographic structure should be as simple as possible in order to reduce the cost. The
present work focuses on development of improved private key cryptographic methods for
providing security against such casual observers in the context of image communications.
In designing private key cryptographic techniques, permutation methods and
pseudo random sequence generators play important roles due to their simple yet effective
information coding performances. This method uses many good keys, selected using
pseudo random index generators (PRIG), for different permutation operations. Since a
large number of keys are used, the security level offered is comparatively high. Further,
the amount of redundant information available in the encrypted image is kept as low as
possible, thereby providing fairly high security level against casual observers. In image
communication, the image is represented as a group of bits, pixels and blocks and
therefore, the encryption is done by permuting the respective groups. Further, to make it
more robust against casual attacks, a random combinational image encryption approach
with bit, pixel and block permutations is used. It is also shown that if the random
combinational sequence of permutations is not known to the observer, it will not be
possible for him/her to retrieve the original information, even if the permutation private
keys are known to that person.
The Pseudo random index generator (PRIG) for permutation purpose is usually
constructed using the linear feedback shift registers (LFSR). A PRIG contains ‗n‘ shift
registers and is initiated with a starting seed, which is usually transmitted through a
secured channel for intended users only. The outputs of the shift registers are multiplied
with the coefficients (Cn−1,Cn−2,...,C1,C0) of a primitive polynomial with respect to mod-2
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operation. The resultant output obtained by the modulo operation is then fed back to the
first shift register. The shift register output values are converted into decimal index using
binary to decimal converter. The general structure of such a PRIG is shown in Fig. 3.3.
Note that the periodicity of such a random index generator is 2n−1
.
Figure 3.3 Structure of a general pseudo random index generator [6]
In the context of images, three basic permutation techniques, they are,
1) Bit permutation: The image can be seen as an array of pixels, each with eight bits for
256 gray levels. In the bit permutation technique, the bits in each pixel taken from the
image are permuted with a key chosen from the set of keys by using the PRIG. The entire
array of these permuted pixels forms the encrypted image. The encrypted image obtained
from the bit permutation technique is transmitted to the receiver through the insecure
channel. At the receiver the encrypted image is decrypted using the same set of keys and
same pseudo random index generator. As the number of bits in each pixel is eight, the key
length is also taken equal to eight. The number of permutations obtained with eight
elements is 8! (=40320) but the number of good keys formed by such eight elements is
only 121. Therefore, to get 127 keys using a PRIG of maximal length 127, other 6 keys
are taken randomly from these 121 good permutation keys to form the complete set.
2) Pixel permutation: In this scheme each group of pixels is taken from the image. The
pixels in the group are permuted using the key selected from the set of keys. The
encryption and decryption procedure is same as the bit permutation technique. The size of
the pixel group is same as the length of the keys, and all the keys are of same length. If
the length of the keys is more than the size of pixel group, the perceptual information
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reduces. In this work the group of pixels is taken along the row without the loss of
generality, i.e., the column wise procedure would yield same kind of results.
3) Block permutation: In this technique, the image can be decomposed into blocks. A
group of blocks is taken from the image and these blocks are permuted same as bit and
pixel permutations. For better encryption the block size should be lower. If the blocks are
very small then the objects and its edges do not appear clearly. In this block permutation
the blocks are permuted horizontally in the image. The permutation of blocks along
vertical side is also similar to horizontal side block permutation. At the receiver the
original image can be obtained by the inverse permutation of the blocks.
Figure 3.4 Block diagram of Combinational Permutation technique [6]
The main idea behind this method is that an image can be viewed as an
arrangement of bits, pixels and blocks. The intelligible information present in an image is
due to the correlations among the bits, pixels and blocks in a given arrangement. This
perceivable information can be reduced by decreasing the correlation among the bits,
pixels and blocks using certain random permutation techniques. The advantage offered by
this scheme is that even if the private key is known to the attacker somehow and the
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random combination key is unknown, then the person will not be able to extract/tamper
the image. Also, due the combination of three permutation approaches the redundancy,
visual intelligence reduces.
To get back the original image at the receiver, the order of the permutation
processes should be exactly reverse to the order at the transmitter; otherwise the output
will produce no visible information. Figure 3.4 shows the block diagram of this method.
However the drawback in this approach is that it provides security only against
casual observers and not against professional hackers; hence is not preferred for real time
application because it is not possible to predict the type of attackers posing danger to the
integrity of image data.
3.3 Need for AES Key Expansion Based Method
The above discussed two Cryptosystem were mainly developed for single
application scenario and hence had its own limitation when considering a general Image
security application. Also these methods were not suitable for Real Time Applications
because the algorithm either had very high security but was slow in processing or it was
very fast at the prize of security.
Hence there is need for an algorithm that in general is applicable for all Image
security applications in Real Time. Thus a method that is based on AES Key Expansion
which overcomes the limitations of above mentioned algorithm is preferred.
Here the encryption process is a Bitwise Exclusive OR operation of a set of image
pixels along with a 128 bit key which changes for every set of pixels. The cipher keys are
generated independently at the sender and receiver side based on AES Key Expansion
process, hence the initial key alone is shared and not the whole set of keys. The algorithm
has been experimented with standard bench mark images proposed in USC-SIPI database
and the result shows that it offers good resistance against brute force attack, key
sensitivity tests and statistical crypt analysis.
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CHAPTER 4
Advanced Encryption Standard
This chapter contains a brief introduction to AES. The topics covered are: Introduction to
AES, Mathematical foundation for AES – Galios Field.
4.1 Introduction to AES
In January, 1997 NIST began its effort to develop the AES, a symmetric key
encryption algorithm, and made a worldwide public call for the algorithm to succeed
DES. Initially 15 algorithms were selected, which was then reduced down to 4
algorithms, RC6, Rijndael, Serpent and Two-fish, all of which were iterated block
ciphers. The four finalists were all determined to be qualified as the AES.
The final evaluation, which also solicited worldwide public input was based on three
characteristics [see table 4.1]
1) Security: It encompassed resistance to known attacks, mathematical soundness,
randomness of output and security compared to other algorithms.
2) Cost: encompassed encryption speed, required memory, and no licensing agreements
i.e. the algorithm had to be available worldwide royalty free.
3) Algorithm and implementation characteristics: The algorithm had to be suitable
across a wide range of hardware and software systems. The algorithm had to be relatively
simple as well. After extensive review the Rijndael algorithm was chosen to be the AES
algorithm.
Algorithm Security
Speed Memory
Encryption/Decryption Key RAM ROM
RC6 Adequate High end Average Average Average
Rijndael Adequate High end High end High end High end
Serpent High Low end Average Average Average
Two Fish High Average High end High end Average
Table 4.1 Some evaluation criteria and results for AES finalists
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AES was designed to have the following characteristics:
Resistance against all known attacks.
Speed and code compactness on a wide range of platforms.
Design simplicity.
The AES Algorithm is a symmetric-key cipher, in which both the sender and the
receiver use a single key for encryption and decryption. The data block length is fixed to
be 128 bits, while the length can be 128, 192 or 256 bits. In addition, the AES is an
iterative algorithm; each iteration being called a round. The total number of rounds Nr is
dependent on Key length Nk, where Nr and Nk are specified in words. The 128 bit data
block is divided into 16 bytes. These bytes are mapped to a 4x4 array called the State, and
all the internal operations of the AES algorithm are performed on the State. The
parameters for AES algorithm are shown in Table 4.2
Algorithm Key length, Nk Block size, Nb No of rounds, Nr= Nk+ 6
AES-128 4 4 10
AES-192 6 4 12
AES-256 8 4 14
Table 4.2 AES Parameters.
Most of the operations in the AES algorithm take place on bytes of data or on words
of data 4 bytes long, which are represented in the field GF(28
), called the Galois Field.
These bytes are represented by the polynomial equation,
b7x7
+ b6x6
+ b5x5
+ b4x4
+ b3x3
+ b2x2
+ b1x + b0 = ∑ bixi
- - - - equation (4.1)
Where, bi {0,1} and i = 0,1,2,...7. There are 256 elements in GF(28
).
For example, 0x11(00010001) identifies the specific finite field x4
+1.
4.2 Mathematical Preliminaries
In abstract algebra, a finite field or Galois field is a field that contains a finite
number of elements. Finite fields are important in number theory, algebraic geometry,
Galois theory, cryptography, coding theory and quantum error correction. The finite fields
are classified by size; there is exactly one finite field up to isomorphism of size pk
for
each prime p and positive integer k. This is represented as GF(pk
). Finite field elements
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can be added and multiplied, but these operations are different from those used in normal
algebra. [7]
4.2.1 Addition in Finite Field Algebra
The addition of two elements in GF(28
) is achieved by ―adding‖ the coefficients for
the corresponding powers in the polynomials for the two elements. The addition is
performed with the XOR operation (denoted by ) - i.e., modulo 2 addition.
i.e., (0 0) = 0; (0 1) = 1; (1 0) = 1; (1 1) = 0.
Consequently, subtraction of polynomials is identical to addition of polynomials. [7]
Example: (0x57 + 0x83) = (x6
+x4
+x2
+x+1) + ( x7
+x+1) = x7
+ x6
+x4
+x2
= 0xD4.
4.2.2 Multiplication in Finite Field Algebra
In the polynomial representation, multiplication in GF(28
) (denoted by •) corresponds
with the multiplication of polynomials modulo an irreducible polynomial m(x) of degree
8. A polynomial is irreducible if its only divisors are one and itself. For the AES
algorithm, this irreducible polynomial is, m(x)=x8
+x4
+x3
+x+1, or {01}{1b} in
hexadecimal notation. [7]
Example: {0x57} • {0x83} = {0xC1}.
i.e.., let A = (x6
+x4
+x2
+x+1) • ( x7
+x+1)
= x13
+x11
+x9
+x8
+x7
+x7
+x5
+x3
+x2
+x+ x6
+x4
+x2
+x+1
= x13
+x11
+x9
+x8
+ x6
+ x5
+ x4
+ x3
+1.
Result of multiplication = A mod (x8
+x4
+x3
+x+1) = x7
+x6
+1= 11000001 = 0xC1.
The modular reduction by m(x) ensures that the result will be a binary polynomial of
degree less than 8, and thus can be represented by a byte. Unlike addition, there is no
simple operation at the byte level that corresponds to this multiplication. There are three
rules which can help in multiplying polynomials in GF(28
). They are,
1) 0x01 is the identity in GF(28
). Thus anything multiplied by 0x01 remains unchanged.
2) Multiplying by two is the same as decimal arithmetic, provided the result does not
exceed the field size of 255 or 0xFF. Also multiplying by 2 in binary is the same as
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shifting left by 1. If the result exceeds 0xFF then the result must be XORed with 0x1B.
This will prevent any overflow errors if working with bytes thus keeping the results
within range.
3) Multiplying by three is the same as multiplying by (1 + 2). Thus,
a • 0x03 = a • (0x02 + 0x01) = (a • 0x02) (a • 0x01).
4.2.3 Multiplicative Inverse in Finite Field Algebra
The multiplication defined above is associative, and the element {01} is the
multiplicative identity. For any non-zero binary polynomial b(x), the multiplicative
inverse of b(x) modulo m(x), denoted by b-1
(x) ,can be found using Extended Euclidean
Algorithm if degree of b(x) is less than that of m(x) and also if GCD[b(x),m(x)]=1. [7]
i.e.., if b(x) • b-1
(x) = 1 ( mod m(x) ), then b-1
(x) is the multiplicative inverse of b(x) in
modulo m(x).
=> [ b(x)*b-1
(x) ] – [ i*m(x) ] = 1, - - - - - - - - - - - - - - - - - - - - - - - -equation (4.2)
where i is the integer quotient of division [ b(x)*b-1
(x) ] ÷ m(x).
=> [ 1 + {i*m(x) ] ÷ b(x) = b-1
(x) - - - - - - - - - - - - - - - - - - - - - - - -equation (4.3)
Equation (4.3) represents the Euclidean Approach to find multiplicative inverse.
The basics of Galois field discussed in section 4.2, is required to understand AES
Algorithm better.
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CHAPTER 5
AES Algorithm
This chapter gives detailed explanation about the steps involved in AES algorithm. The
topics covered includes: AES encryption/decryption, Transformations used in AES and
Key expansion Schedule.
5.1 AES Encryption/Decryption
For each round of AES, 128 bit input data and 128 bit key is required, i.e.., it needs 4
words of key in one round. Thus the input key must be expanded to the required number
of words depending upon the number of rounds. The output of each round serves as input
to the next stage. In AES system, same secret key is used for both encryption and
decryption; thus simplifies the design. The block diagram for AES Encryption and
Decryption is as shown in Figure 5.1
Figure 5.1 AES Encryption and Decryption.
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For both its Cipher and Inverse Cipher, the AES algorithm uses a round function that
is composed of four different byte-oriented transformations: 1) byte substitution using a
substitution table (S-box), 2) shifting rows of the State array by different offsets, 3)
mixing the data within each column of the State array, and 4) adding a Round Key to the
State. The above 4 transformation are looped Nr-1 times. In the last round (i.e.., Nr
th
round) Mixcolumn is not performed.
The AddRoundKey is performed at the beginning and at the end of the cipher in
order to provide initial and final randomness to the algorithm. Without this, the first or
last portion of the cipher could be easily deduced, and therefore would be irrelevant to the
security of the cipher. The last round in the cipher is different from the other rounds in
order to make the encryption and decryption routines more similar, allowing the
complexity to be reduced in hardware and software implementations.
5.2 AES Transformations
The four transformations used in AES Encryption are : ByteSub, ShiftRows,
MixColumns, AddRoundKey. The inverse of these operations are performed for
decryption.
5.2.1 Byte Substitution
The ByteSub transformation is a non-linear byte substitution that operates
independently on each byte of the State using a substitution table (S-box) as shown in
figure 5.2
Figure 5.2 ByteSub transformation
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The S-box, which is invertible, is constructed by composing two transformations,
i. Take the multiplicative inverse in the finite field GF(28
); the element {00} is
mapped to itself.
ii. Apply the following affine transformation (over GF(2) ) which is defined as,
bi‘= bi b(i+4)mod8 b(i+5)mod8 b(i+6)mod8 b(i+7)mod8 Ci - - - - - -equation (5.1)
Where, 0 ≤ i ≤ 8 and bi is the ith
bit of byte and Ci is the ith
bit of byte C whose
value is 0x63 or (01100011).
In matrix form, the affine transformation element of the S-box can be expressed
as;
The S-box for ByteSub is as shown in Figure 5.3
The Inverse ByteSub is used to reverse this operation in decryption process. The
affine transformation for Inverse ByteSub is as shown below;
The S-1
box for inv ByteSub operation is shown in Figure 5.4
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Figure 5.3 look up table for ByteSub transformation.
Figure 5.4 look up table for Inv ByteSub operation.
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5.2.2 Shift Rows
Shift-Rows operates on individual rows of the state. It provides diffusion throughout
the AES algorithm. This operation will not change the values of byte in the row, but will
just change their order. It performs left circular shift on each row as follows;
Row 0 Shift 0; Row 1 Shift 1; Row 2 Shift 2; Row 3 Shift 3;
This is illustrated in Figure 5.5 below. For decryption this Shift operation is reversed.
Figure 5.5 Illustration of Shift Row transformation.
5.2.3 Mix Columns
The MixColumns transformation operates on the State column-by-column, treating
each column as a four-term polynomial. The columns are considered as polynomials over
GF(28
) and are multiplied modulo (x4
+1) with a mixing polynomial a(x) given by,
a(x)=(0x03) • x3
+ (0x01) • x2
+ (0x01) • x + (0x02).
This can represented by matrix equation as,
02010103
03020101
01030201
01010302
02010103
03020101
01030201
01010302
a3
a2
a1
a0
a3
a2
a1
a0
a’
3
a’
2
a’
1
a’
0
a’
3
a’
2
a’
1
a’
0
=
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Figure 5.6 illustrates the mix column transformation.
Figure 5.6 Illustration of MixColumn transformation.
InvMixColumns performs the reverse operation for decryption and can be described by
the matrix equation is,
5.2.4 Add Round Key
It is the step that incorporates the round key, a portion of the expanded key, into the
plaintext. This routine performs bitwise XOR of each byte of the state with the
corresponding byte of the round key.
If Add Round Key operates on a variable twice, the variable itself is returned. This
property is used in decryption. Figure 5.7 illustrates this transformation.
0e090d0b
0b0e090d
0d0b0e09
090d0b0e
0e090d0b
0b0e090d
0d0b0e09
090d0b0e
a3
a2
a1
a0
a3
a2
a1
a0
a’
3
a’
2
a’
1
a’
0
a’
3
a’
2
a’
1
a’
0
=
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Figure 5.7 Add round key Transformation
The above 4 transformation are looped Nr-1 times. In the last round (i.e.., Nr
th
round) Mixcolumn is not performed.
The AddRoundKey is performed at the beginning and at the end of the cipher in
order to provide initial and final randomness to the algorithm. Without this, the first or
last portion of the cipher could be easily deduced, and therefore would be irrelevant to the
security of the cipher. The last round in the cipher is different from the other rounds in
order to make the encryption and decryption routines more similar, allowing the
complexity to be reduced in hardware and software implementations.
5.3 Key Expansion schedule
Pseudo code for AES Key Expansion is given in Figure 5.9. The key-expansion
routine creates round keys word by word, where a word is an array of four bytes. The
routine creates 4x(Nr+1) words. For Nk=4words, Nr=10; this routine creates 44 words.
The process is as follows :
First 4 words of round key are made from initial cipher key. The key is considered
as an array of 16 bytes k[0:15]. The first four bytes (k0 to k3) become w0, the next
four bytes (k4 to k7) become w1, and so on.
The rest of the words (wi for i=4 to 43) are derived as follows:
if (i mod 4)!=0 then, wi = wi-1 wi-4 ;
else if(i mod 4)=0 then wi=t wi-4. Here ‗t‘ is a temporary word result of
applying SubByte transformation and rotate word on wi-1 and XORing the result
with a round constant.
Figure 5.8 shows the pictorial representation of AES key expansion.
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Figure 5.8 AES Key Expansion
Figure 5.9 pseudo code for AES key expansion.
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Steps to find wi when ( i mod 4) = 0
i. RotWord: performs one byte circular left shift on wi-1.
ii. SubWord: performs a byte substitution on each byte of its input word, using
the S-box.
iii. The result of step (i) and (ii) is XORed with a round constant Rcon[j] whichis
given by, Rcon[j]={RC[j],0,0,0},where RC[j]=2*RC[j-1], with multiplication
over GF(28
).
J 1 2 3 4 5 6 7 8 9 10
RC[j] 01 02 04 08 10 20 40 80 1B 36
Table 5.1 RC[j] values in hex.
5.3.1 Example for AES Key Expansion
Consider the 16 byte key to be, K = 2b7e151628aed2a6abf7158809cf4f3c.
Key length, Nk = 4 words. => expanded key has 44 words or 11 sets of 4 word keys( one
set used in each round).
AES key expansion steps to obtain the expanded key:
Step 1: Enter the K into key array byte by byte column wise.
2b 28 ab 09
7e ae f7 cf
15 d2 15 4f
16 a6 88 3c
W[0] W[1] W[2] W[3]
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W[0:3] forms the cipher key.
Step 2: calculate the first set of 16byte key to be used for 1nd
round, i.e., w[4:7]
Step 2a: to find w[4] , follow the steps discussed in section 5.3.
Now, W[i-1] = W[3] = [ 09 cf 4f 3c ].
After shift row operation, W[3] = [ cf 4f 3c 09 ].
After SubByte transform, W[3]* = [ 8a 84 eb 01 ].
Now, W[i-4] = W[0] = [ 2b 7e 15 16 ] and Rcon[1] = [ 01 00 00 00].
W[4] = W[3]* W[0] Rcon[1]
W[4] = [ 8a 84 eb 01 ] [ 2b 7e 15 16 ] [ 01 00 00 00].
W[4] = [a0 fa fe 17].
Step 2b: To find W[5], W[i-1] =W[4] = [a0 fa fe 17] and W[i-4]= W[1] = [ 28 ae d2 a6 ].
W[5] = W[4] W[1].
W[5] = [a0 fa fe 17] [ 28 ae d2 a6 ].
W[5] = [ 88 54 2c b1 ].
Step 2c: Find W[6] and W[7] using the same procedure as 2b.
Thus W[6] = [ 23 a3 39 39 ]. And W[7] = [ 2a 6c 76 05 ].
Therefore, the 2nd
round key is,
A0 88 23 2a
Fa 54 A3 6c
Fe 2c 39 76
17 B1 39 05
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Step 3: Similarly find rest of the 9 round keys using the step 2.
2nd
round key :
F2 79 59 73
C2 96 35 59
95 B9 80 F6
F2 43 7a 7f
3rd
round key:
3d 47 1e 6d
80 16 23 7a
47 fe 7e 88
7d 3e 44 3b
4th
round key:
Ef A8 B6 Db
44 52 71 0b
A5 5b 25 0d
41 7f 3b 00
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5th
round key:
D4 7c Ca 11
D1 83 F2 F9
C6 9d B8 15
F8 87 bc Bc
6th
round key:
6d 11 Db Ca
88 0b F9 00
A3 3e 86 93
7a Fd 41 Fd
7th
round key:
4e 5f 84 4e
54 5f A6 A6
F7 C9 4f Dc
0e F3 B2 4f
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8th
round key:
Ea B4 31 7f
D2 8d 2b 8d
73 Da F5 29
21 D2 60 2f
9th
round key:
Ac 19 28 57
77 Fa D1 5c
65 Dc 29 00
F3 21 41 6e
10th
round key:
D0 C9 E1 B6
14 Ee 3f 63
F9 25 0c 0c
A8 89 C8 A6
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CHAPTER 6
Modified AES Key Expansion
This chapter gives the detailed description of the proposed method for Real Time Image
Cryptosystems-Modified AES Key Expansion Based Method. The topics covered
include: Changes in AES Key Expansion Schedule to suite Image Cryptosystems, Steps
involved in Image Encryption/Decryption and Experimental Results & Analysis.
6.1 Changes in AES Key Expansion Schedule to Suite Image
Cryptosystems
Certain changes made to the AES key expansion process (discussed in the section 5.3)
improves the encryption quality, and also increases the avalanche effect in the resulting
cipher image. The changes are,
The initial key is expanded based on the number of pixels in the image.
The Rcon value is not constant instead it is being formed from the initial key
itself.
Both the s-box and Inverse s-box are also used for the modified Key Expansion
process because it improves non-linearity in the expanded key and also improves
the encryption quality. The S-box and Inverse S-box are however not directly used
in this algorithm; instead some circular shifts are performed on the boxes based on
the initial key.
The above changes in the algorithm can be represented as discussed in the sections below.
6.1.1 Key Expansion for the image
Consider a plain gray-level image of size mxn. In this method, a set of 16 pixels (128
bits) is encrypted using 2 round keys.
∴ No of keys to Encrypt the whole image N=2*{(m*n)/16}.
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6.1.2 Formation of Rcon values
Rcon[j] is formed from the initial cipher key as follows:
Rcon[0]=key[12:15]; Rcon[1]=key[4:7];
Rcon [2]=key[0 : 3]; Rcon [3]=key[8:11];
6.1.3 Using Inverse S-Box for key expansion
The ‗temp‘ value used in the algorithm is formed as follows,
temp = SubWord(RotWord(temp)) + InvSubWord(Rcon[i/4]);
here the Rcon values are not used directly, instead each byte of Rcon is substituted by its
corresponding InvSubByte value from S-1
box. This improves the non-linearity of the
expanded key.
6.1.4 Shifting of S-box and Inverse S-box
The offset for shifting S-box and S-1
box is obtained using following equation,
Sbox_offset = sum(key[0:15])mod256;
Inv_Sbox_offset = (sum(key[0:15])*mean(key[0:15]))mod256;
6.2 Steps Involved in Image Encryption/Decryption Using
Modified AES Key Expansion
The steps involved in Image Encryption/Decryption using Modified AES Key
Expansion include: Key selection, Generation of multiple keys, Encryption and
Decryption. Each of these steps are explained briefly below.
6.2.1 Key selection
The sender and receiver agree upon a 128 bit key. This key is used for encryption
and decryption of images. It is a symmetric key encryption technique, so they must share
this key in a secure manner.
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The key is represented as blocks k[0],k[1]...k[15]. Where each block is 8bits long
(8*16=128 bits).
6.2.2 Generation of Multiple keys
The sender and receiver can now independently generate the keys required for the
process using the above explained Modified AES Key Expansion technique. This is a one
time process; these expanded keys can be used for future communications any number of
times till they change their initial key value.
6.2.3 Encryption
Encryption is done in spans, where 16 pixels are processed in each span. This
Algorithm performs two XOR operations and a SubBytes Transformation for each set of
pixels. Since two XOR operations are performed using the expanded key for every set of
pixels it is impossible to get the key from plain image and cipher image, and to improve
the non linearity the s-box values used in AES may also be used. This is shown in figure
6.1.
6.2.4 Decryption
The decryption process shown in figure 6.1 is similar as encryption, but here Inverse
SubByte Transformation is used and also the order of XOR operation using the expanded
key is reversed.
Figure 6.1 Encryption/Decryption process for image encryption using modified aes key expansion
37. Image Encryption using AES Key Expansion Seminar Report 2013
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CHAPTER 7
Experimental Analysis
The algorithm has been implemented in Mat Lab 6.0 in windows environment with a
system configuration of PIV processor with 1 GB RAM. The proposed algorithm has
been tested with various images in USC-SIPI repository which is a collection of digitized
images primarily to support image processing, image analysis and machine vision.
7.1Key Space Analysis
The strength of any cryptographic algorithm depends upon key space which should
be sufficiently large enough to make brute force attack infeasible. The proposed
algorithm has a huge key space which is 2^128 possible keys. If an opponent tries for
brute force attack, since the key sensitivity of this algorithm is very high he would have to
try all combinations of keys for the image which is computationally infeasible.
7.2Histogram Analysis
To prevent the leakage of information to an opponent, it is also advantageous if the
cipher image bears little or no statistical similarity to the plain image. An image
histogram illustrates how pixels in an image are distributed by graphing the number of
pixels at each colour intensity level. The histogram of the encrypted image is expected to
be fairly uniform and significantly different from the respective histograms of the original
image.
Figure 7.1 and figure 7.2 shows the histogram analysis of plain image and cipher
image. The histogram analysis shows that the histogram of the cipher image is fairly
uniform and is significantly different from the original image. The encryption algorithm
has covered up all the characters of the plain image and has complicated the statistical
relationship between the plain image and its ciphered version.
Figure 7.1 shows the analysis for grey scale image whereas figure 7.2 shows the
analysis for color image.
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Figure 7.1 Histogram analysis of Grey Scale 1024X1024 Lena Image
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Figure 7.2 Histogram Analysis of Colour 640X480 Mountain Image
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7.3 Key Sensitivity Analysis
High key sensitivity is required by secure image cryptosystems, which means that
the cipher image cannot be decrypted correctly even if there is only a slight difference
between encryption or decryption keys. The proposed algorithm is experimented for
various key values whose difference is negligibly small. This is similar to avalanche
effect in text encryption where a small bit difference in the key could produce a
significant difference in the cipher text produced. The strength of the algorithm is that
even for a single bit change in the key value the image is not decrypted. Figure 7.3
illustrates the key sensitivity of the proposed algorithm.
Figure 7.3 Key Sensitivity Analysis of Proposed Algorithm
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7.4 Execution Time
Another important factor that evaluates the efficiency of algorithms is measuring the
amount of time required to encrypt an image. In this investigation, actual time in CPU
cycles will be used as a measure of execution time. Table 7.1 shows the comparison of
computational time taken by algorithms specified in literature to that of proposed
algorithm to encrypt a 1024x1024 gray-scale Lena Image.
Algorithm Time in seconds for Lena Image
Bourbakis(SCAN patterns) 2.54
Mitra (CPT) 1.82
Proposed Algorithm 1.41
Table 7.1 Computational time comparison
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CHAPTER 8
Conclusion and Future Work
8.1 Conclusion
Based on the experimental results shown in section 6.3, it can be observed that
The proposed algorithm offers high encryption quality with minimal
computational time.
The key sensitivity and key space of the algorithm is very high which makes it
resistant towards Brute force attack and statistical cryptanalysis.
The time taken for encryption is relatively less in comparison with the algorithms
proposed in the literature.
The above mentioned features make the algorithm suitable for image encryption in real
time applications.
8.2 Future work
S-box is the pivotal part of AES. Research may be done to improve the quality of
S-box design.
AES-192 or AES-256 may be used to further increase the key sensitivity and key
space of the algorithm.
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References
[1] B.Subramanyan, Vivek.M.Chhabria, T.G.Sankar babu, Image Encryption Based On
AES Key Expansion, 2011 Second International Conference on Emerging Applications of
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[2] C.J.Kuo, Novel image Encryption Technique and its application in progressive
transmission. Journal of Electron imaging 24 1993 pp 345-351.
[3] N.J.Bourbakis , C.Alexopoulos, Picture data encryption using SCAN patterns. Pattern
Recognition 256 1992 pp567 -581.
[4] Chin-Chen Chang, Min-Shian Hwang, Tung-Shou Chen, ―A new encryption
algorithm for image cryptosystems‖, The Journal of Systems and Software 58 (2001), 83-
91.
[5] Fridrich Jiri, Symmetric ciphers based on two dimensional chaotic maps, Int. J.
Bifurcat Chaos 8 (1998) (6), pp. 1259– 1284.
[6] Mitra, Y. V. Subba Rao, and S. R. M. Prasanna, A new image encryption approach
using combinational permutation techniques, International Journal of Computer Science,
vol. 1, no. 2 , pp. 1306- 4428, 2006..
[7] http://csrc.nist.gov/publications/fips/fips197/fips-197.pdf.