A review on structured scheme representation on data security application

With the rapid development in the era of Internet and networking technology, there is always a requirement to improve the security systems, which secure the transmitted data over an unsecured channel. The needs to increase the level of security in transferring the data always become the critical issue. Therefore, data security is a significant area in covering the issue of security, which refers to protect the data from unwanted forces and prevent unauthorized access to a communication. This paper presents a review of structured-scheme representation for data security application. There are five structured-scheme types, which can be represented as dual-scheme, triple-scheme, quad-scheme, octal-scheme and hexa-scheme. These structured-scheme types are designed to improve and strengthen the security of data on the application

A DATA HIDING SCHEME BASED ON CHAOTIC MAP AND PIXEL PAIRS

Information security is one of the most common areas of study today. In the literature, there are many algorithms developed in the information security. The Least Significant Bit (LSB) method is the most known of these algorithms. LSB method is easy to apply however it is not effective on providing data privacy and robustness. In spite of all its disadvantages, LSB is the most frequently used algorithm in literature due to providing high visual quality. In this study, an effective data hiding scheme alternative to LSB, 2LSBs, 3LSBs and 4LSBs algorithms (known as xLSBs), is proposed. In this method, random numbers which are to be used as indices of pixels of the cover image are obtained from chaotic maps and data hiding process is applied on the values of these pixels by using modulo function. Calculated values are embedded in cover image as hidden data. Success of the proposed data hiding scheme is assessed by Peak Signal-to-Noise Ratio (PSNR), payload capacity and quality

Protecting Information with Subcodstanography

In modern communication systems, one of the most challenging tasks involves the implementation of adequate methods for successful and secure transfer of confidential digital information over an unsecured communication channel. Many encryption algorithms have been developed for protection of confidential information. However, over time, flaws have been discovered even with the most sophisticated encryption algorithms. Each encryption algorithm can be decrypted within sufficient time and with sufficient resources. The possibility of decryption has increased with the development of computer technology since available computer speeds enable the decryption process based on the exhaustive data search. This has led to the development of steganography, a science which attempts to hide the very existence of confidential information. However, the stenography also has its disadvantages, listed in the paper. Hence, a new method which combines the favourable properties of cryptography based on substitution encryption and stenography is analysed in the paper. The ability of hiding the existence of confidential information comes from steganography and its encryption using a coding table makes its content undecipherable. This synergy greatly improves protection of confidential information

Providing End-to-End Security Using Quantum Walks in IoT Networks

Internet of Things acts an essential role in our everyday lives and it definitely has the potential to grow on the importance and revolutionize our future. However, the present communication technologies have several security related issues which is required to provide secure end to end connectivity among services. Moreover, due to recent, rapid growth of quantum technologies, most common security mechanisms considered secure today may be soon imperilled. Thus, the modern security mechanisms during their construction also require the power of quantum technologies to resist various potential attacks from quantum computers. Because of its characteristics, quantum walks (QW) is considered as a universal quantum computation paradigm that can be accepted as an excellent key generator. In this regard, in this paper a new lightweight image encryption scheme based on QW for secure data transfer in the internet of things platforms and wireless networking with edge computing is proposed. The introduced approach utilises the power of nonlinear dynamic behaviour of QW to construct permutation boxes and generates pseudo-random numbers for encrypting the plain image after dividing it into blocks. The results of the conducted simulation and numerical analyses confirm that the presented encryption algorithm is effective. The encrypted images have randomness properties, no useful data about the ciphered image can be obtained via analysing the correlation of adjacent pixels. Moreover, the entropy value is close to 8, the number of the pixel change rate is greater than 99.61%, and there is high sensitivity of the key parameters with large key space to resist various attack

Privacy-preserving information hiding and its applications

The phenomenal advances in cloud computing technology have raised concerns about data privacy. Aided by the modern cryptographic techniques such as homomorphic encryption, it has become possible to carry out computations in the encrypted domain and process data without compromising information privacy. In this thesis, we study various classes of privacy-preserving information hiding schemes and their real-world applications for cyber security, cloud computing, Internet of things, etc. Data breach is recognised as one of the most dreadful cyber security threats in which private data is copied, transmitted, viewed, stolen or used by unauthorised parties. Although encryption can obfuscate private information against unauthorised viewing, it may not stop data from illegitimate exportation. Privacy-preserving Information hiding can serve as a potential solution to this issue in such a manner that a permission code is embedded into the encrypted data and can be detected when transmissions occur. Digital watermarking is a technique that has been used for a wide range of intriguing applications such as data authentication and ownership identification. However, some of the algorithms are proprietary intellectual properties and thus the availability to the general public is rather limited. A possible solution is to outsource the task of watermarking to an authorised cloud service provider, that has legitimate right to execute the algorithms as well as high computational capacity. Privacypreserving Information hiding is well suited to this scenario since it is operated in the encrypted domain and hence prevents private data from being collected by the cloud. Internet of things is a promising technology to healthcare industry. A common framework consists of wearable equipments for monitoring the health status of an individual, a local gateway device for aggregating the data, and a cloud server for storing and analysing the data. However, there are risks that an adversary may attempt to eavesdrop the wireless communication, attack the gateway device or even access to the cloud server. Hence, it is desirable to produce and encrypt the data simultaneously and incorporate secret sharing schemes to realise access control. Privacy-preserving secret sharing is a novel research for fulfilling this function. In summary, this thesis presents novel schemes and algorithms, including: • two privacy-preserving reversible information hiding schemes based upon symmetric cryptography using arithmetic of quadratic residues and lexicographic permutations, respectively. • two privacy-preserving reversible information hiding schemes based upon asymmetric cryptography using multiplicative and additive privacy homomorphisms, respectively. • four predictive models for assisting the removal of distortions inflicted by information hiding based respectively upon projection theorem, image gradient, total variation denoising, and Bayesian inference. • three privacy-preserving secret sharing algorithms with different levels of generality

New watermarking methods for digital images.

The phenomenal spread of the Internet places an enormous demand on content-ownership-validation. In this thesis, four new image-watermarking methods are presented. One method is based on discrete-wavelet-transformation (DWT) only while the rest are based on DWT and singular-value-decomposition (SVD) ensemble. The main target for this thesis is to reach a new blind-watermarking-method. Method IV presents such watermark using QR-codes. The use of QR-codes in watermarking is novel. The choice of such application is based on the fact that QR-Codes have errors self-correction-capability of 5% or higher which satisfies the nature of digital-image-processing. Results show that the proposed-methods introduced minimal distortion to the watermarked images as compared to other methods and are robust against JPEG, resizing and other attacks. Moreover, watermarking-method-II provides a solution to the detection of false watermark in the literature. Finally, method IV presents a new QR-code guided watermarking-approach that can be used as a steganography as well. --Leaf ii.The original print copy of this thesis may be available here: http://wizard.unbc.ca/record=b183575

On Foundations of Protecting Computations

Information technology systems have become indispensable to uphold our way of living, our economy and our safety. Failure of these systems can have devastating effects. Consequently, securing these systems against malicious intentions deserves our utmost attention. Cryptography provides the necessary foundations for that purpose. In particular, it provides a set of building blocks which allow to secure larger information systems. Furthermore, cryptography develops concepts and tech- niques towards realizing these building blocks. The protection of computations is one invaluable concept for cryptography which paves the way towards realizing a multitude of cryptographic tools. In this thesis, we contribute to this concept of protecting computations in several ways. Protecting computations of probabilistic programs. An indis- tinguishability obfuscator (IO) compiles (deterministic) code such that it becomes provably unintelligible. This can be viewed as the ultimate way to protect (deterministic) computations. Due to very recent research, such obfuscators enjoy plausible candidate constructions. In certain settings, however, it is necessary to protect probabilistic com- putations. The only known construction of an obfuscator for probabilistic programs is due to Canetti, Lin, Tessaro, and Vaikuntanathan, TCC, 2015 and requires an indistinguishability obfuscator which satisfies extreme security guarantees. We improve this construction and thereby reduce the require- ments on the security of the underlying indistinguishability obfuscator. (Agrikola, Couteau, and Hofheinz, PKC, 2020) Protecting computations in cryptographic groups. To facilitate the analysis of building blocks which are based on cryptographic groups, these groups are often overidealized such that computations in the group are protected from the outside. Using such overidealizations allows to prove building blocks secure which are sometimes beyond the reach of standard model techniques. However, these overidealizations are subject to certain impossibility results. Recently, Fuchsbauer, Kiltz, and Loss, CRYPTO, 2018 introduced the algebraic group model (AGM) as a relaxation which is closer to the standard model but in several aspects preserves the power of said overidealizations. However, their model still suffers from implausibilities. We develop a framework which allows to transport several security proofs from the AGM into the standard model, thereby evading the above implausi- bility results, and instantiate this framework using an indistinguishability obfuscator. (Agrikola, Hofheinz, and Kastner, EUROCRYPT, 2020) Protecting computations using compression. Perfect compression algorithms admit the property that the compressed distribution is truly random leaving no room for any further compression. This property is invaluable for several cryptographic applications such as “honey encryption” or password-authenticated key exchange. However, perfect compression algorithms only exist for a very small number of distributions. We relax the notion of compression and rigorously study the resulting notion which we call “pseudorandom encodings”. As a result, we identify various surprising connections between seemingly unrelated areas of cryptography. Particularly, we derive novel results for adaptively secure multi-party computation which allows for protecting computations in distributed settings. Furthermore, we instantiate the weakest version of pseudorandom encodings which suffices for adaptively secure multi-party computation using an indistinguishability obfuscator. (Agrikola, Couteau, Ishai, Jarecki, and Sahai, TCC, 2020

Applied Metaheuristic Computing

For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC

Applied Methuerstic computing

For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC

ICTERI 2020: ІКТ в освіті, дослідженнях та промислових застосуваннях. Інтеграція, гармонізація та передача знань 2020: Матеріали 16-ї Міжнародної конференції. Том II: Семінари. Харків, Україна, 06-10 жовтня 2020 р.

This volume represents the proceedings of the Workshops co-located with the 16th International Conference on ICT in Education, Research, and Industrial Applications, held in Kharkiv, Ukraine, in October 2020. It comprises 101 contributed papers that were carefully peer-reviewed and selected from 233 submissions for the five workshops: RMSEBT, TheRMIT, ITER, 3L-Person, CoSinE, MROL. The volume is structured in six parts, each presenting the contributions for a particular workshop. The topical scope of the volume is aligned with the thematic tracks of ICTERI 2020: (I) Advances in ICT Research; (II) Information Systems: Technology and Applications; (III) Academia/Industry ICT Cooperation; and (IV) ICT in Education.Цей збірник представляє матеріали семінарів, які були проведені в рамках 16-ї Міжнародної конференції з ІКТ в освіті, наукових дослідженнях та промислових застосуваннях, що відбулася в Харкові, Україна, у жовтні 2020 року. Він містить 101 доповідь, які були ретельно рецензовані та відібрані з 233 заявок на участь у п'яти воркшопах: RMSEBT, TheRMIT, ITER, 3L-Person, CoSinE, MROL. Збірник складається з шести частин, кожна з яких представляє матеріали для певного семінару. Тематична спрямованість збірника узгоджена з тематичними напрямками ICTERI 2020: (I) Досягнення в галузі досліджень ІКТ; (II) Інформаційні системи: Технології і застосування; (ІІІ) Співпраця в галузі ІКТ між академічними і промисловими колами; і (IV) ІКТ в освіті