Biblio

Geospatial fog computing system offers various benefits as a platform for geospatial computing services closer to the end users, including very low latency, good mobility, precise position awareness, and widespread distribution. In recent years, it has grown quickly. Fog nodes' security is susceptible to a number of assaults, including denial of service and resource abuse, because to their widespread distribution, complex network environments, and restricted resource availability. This paper proposes a Quantum Key Distribution (QKD)-based geospatial quantum fog computing environment that offers a symmetric secret key negotiation protocol that can preserve information-theoretic security. In QKD, after being negotiated between any two fog nodes, the secret keys can be given to several users in various locations to maintain forward secrecy and long-term protection. The new geospatial quantum fog computing environment proposed in this work is able to successfully withstand a variety of fog computing assaults and enhances information security.

Information exchange occurs all the time in today’s internet era. Some of the data are public, and some are private. Asymmetric cryptography plays a critical role in securing private data transfer. However, technological advances caused private data at risk due to the presence of quantum computers. Therefore, we need a new method for securing private data. This paper proposes combining DNA cryptography methods based on the NTRU cryptosystem to enhance security data confidentiality. This method is compared with conventional public key cryptography methods. The comparison shows that the proposed method has a slow encryption and decryption time compared to other methods except for RSA. However, the key generation time of the proposed method is much faster than other methods tested except for ECC. The proposed method is superior in key generation time and considerably different from other tested methods. Meanwhile, the encryption and decryption time is slower than other methods besides RSA. The test results can get different results based on the programming language used.

Counterfeited products are a significant problem in both developed and developing countries and has become more critical as an aftermath of COVID-19, exclusively for drugs and medical equipment’s. In this paper, an innovative approach is proposed to resist counterfeiting which is based on the principles of Synthetic DNA. The proposed encryption approach has employed the distinctive features of synthetic DNA in amalgamation with DNA encryption to provide information security and functions as an anticounterfeiting method that ensures usability. The scheme’s security analysis and proof of concept are detailed. Scyther is used to carry out the formal analysis of the scheme, and all of the modeled assertions are verified without any attacks.

This research investigates efficient architectures for the implementation of the CRYSTALS-Dilithium post-quantum digital signature scheme on reconfigurable hardware, in terms of speed, memory usage, power consumption and resource utilisation. Post quantum digital signature schemes involve a significant computational effort, making efficient hardware accelerators an important contributor to future adoption of schemes. This is work in progress, comprising the establishment of a comprehensive test environment for operational profiling, and the investigation of the use of novel architectures to achieve optimal performance.

Cyber threats can cause severe damage to computing infrastructure and systems as well as data breaches that make sensitive data vulnerable to attackers and adversaries. It is therefore imperative to discover those threats and stop them before bad actors penetrating into the information systems.Threats hunting algorithms based on machine learning have shown great advantage over classical methods. Reinforcement learning models are getting more accurate for identifying not only signature-based but also behavior-based threats. Quantum mechanics brings a new dimension in improving classification speed with exponential advantage. The accuracy of the AI/ML algorithms could be affected by many factors, from algorithm, data, to prejudicial, or even intentional. As a result, AI/ML applications need to be non-biased and trustworthy.In this research, we developed a machine learning-based cyber threat detection and assessment tool. It uses two-stage (both unsupervised and supervised learning) analyzing method on 822,226 log data recorded from a web server on AWS cloud. The results show the algorithm has the ability to identify the threats with high confidence.

Researchers have investigated the dark web for various purposes and with various approaches. Most of the dark web data investigation focused on analysing text collected from HTML pages of websites hosted on the dark web. In addition, researchers have documented work on dark web image data analysis for a specific domain, such as identifying and analyzing Child Sexual Abusive Material (CSAM) on the dark web. However, image data from dark web marketplace postings and forums could also be helpful in forensic analysis of the dark web investigation.The presented work attempts to conduct image classification on classes other than CSAM. Nevertheless, manually scanning thousands of websites from the dark web for visual evidence of criminal activity is time and resource intensive. Therefore, the proposed work presented the use of quantum computing to classify the images using a Quantum Convolutional Neural Network (QCNN). Authors classified dark web images into four categories alcohol, drugs, devices, and cards. The provided dataset used for work discussed in the paper consists of around 1242 images. The image dataset combines an open source dataset and data collected by authors. The paper discussed the implementation of QCNN and offered related performance measures.

Can quantum entanglement increase the capacity of (classical) covert channels? To one familiar with Holevo's Theorem it is tempting to think that the answer is obviously no. However, in this work we show: quantum entanglement can in fact increase the capacity of a classical covert channel, in the presence of an active adversary; on the other hand, a zero-capacity channel is not improved by entanglement, so entanglement cannot create ‘purely quantum’ covert channels; the problem of determining the capacity of a given channel in the presence of entanglement is undecidable; but there is an algorithm to bound the entangled capacity of a channel from above, adapted from the semi-definite hierarchy from the theory of non-local games, whose close connection to channel capacity is at the core of all of our results.

We propose a methodology for the simulation of electrostatic confinement wells in transistors at cryogenic temperatures. This is considered in the context of 22-nm fully depleted silicon-on-insulator transistors due to their potential for imple-menting quantum bits in scalable quantum computing systems. To overcome thermal fluctuations and improve decoherence times in most quantum bit implementations, they must be operated at cryogenic temperatures. We review the dominant sources of electric field at these low temperatures, including material interface work function differences and trapped interface charges. Intrinsic generation and dopant ionisation are shown to be negligible at cryogenic temperatures when using a mode of operation suitable for confinement. We propose studying cryogenic electrostatic confinement wells in transistors using a finite-element model simulation, and decoupling carrier transport generated fields.

Blockchain technology has made it possible to store and send digital currencies. Bitcoin wallets and marketplaces have made it easy for nontechnical users to use the protocol. Since its inception, the price of Bitcoin is going up and the number of nodes in the network has increased drastically. The increasing popularity of Bitcoin has made exchanges and individual nodes a target for an attack. Understanding the Bitcoin protocol better helps security engineers to harden the network and helps regular users secure their hot wallets. In this paper, Bitcoin protocol is presented with description of the mining process which secures transactions. In addition, the Bitcoin algorithms and their security are described with potential vulnerabilities in the protocol and potential exploits for attackers. Finally, we propose some security solutions to help mitigate attacks on Bitcoin exchanges and hot wallets.

Considered sensitive information by the ISO/IEC 24745, biometric data should be stored and used in a protected way. If not, privacy and security of end-users can be compromised. Also, the advent of quantum computers demands quantum-resistant solutions. This work proposes the use of Kyber and Saber public key encryption (PKE) algorithms together with homomorphic encryption (HE) in a face recognition system. Kyber and Saber, both based on lattice cryptography, were two finalists of the third round of NIST post-quantum cryptography standardization process. After the third round was completed, Kyber was selected as the PKE algorithm to be standardized. Experimental results show that recognition performance of the non-protected face recognition system is preserved with the protection, achieving smaller sizes of protected templates and keys, and shorter execution times than other HE schemes reported in literature that employ lattices. The parameter sets considered achieve security levels of 128, 192 and 256 bits.

When it comes to cryptographic random number generation, poor understanding of the security requirements and “mythical aura” of black-box statistical testing frequently leads it to be used as a substitute for cryptanalysis. To make things worse, a seemingly standard document, NIST SP 800–22, describes 15 statistical tests and suggests that they can be used to evaluate random and pseudorandom number generators in cryptographic applications. The Chi-nese standard GM/T 0005–2012 describes similar tests. These documents have not aged well. The weakest pseudorandom number generators will easily pass these tests, promoting false confidence in insecure systems. We strongly suggest that SP 800–22 be withdrawn by NIST; we consider it to be not just irrelevant but actively harmful. We illustrate this by discussing the “reference generators” contained in the SP 800–22 document itself. None of these generators are suitable for modern cryptography, yet they pass the tests. For future development, we suggest focusing on stochastic modeling of entropy sources instead of model-free statistical tests. Random bit generators should also be reviewed for potential asymmetric backdoors via trapdoor one-way functions, and for security against quantum computing attacks.

Recent trends in the convergence of edge computing and artificial intelligence (AI) have led to a new paradigm of “edge intelligence”, which are more vulnerable to attack such as data and model poisoning and evasion of attacks. This paper proposes a white-box poisoning attack against online regression model for edge intelligence environment, which aim to prepare the protection methods in the future. Firstly, the new method selects data points from original stream with maximum loss by two selection strategies; Secondly, it pollutes these points with gradient ascent strategy. At last, it injects polluted points into original stream being sent to target model to complete the attack process. We extensively evaluate our proposed attack on open dataset, the results of which demonstrate the effectiveness of the novel attack method and the real implications of poisoning attack in a case study electric energy prediction application.

Current cryptographic solutions used in information technologies today like Transport Layer Security utilize algorithms with underlying computationally difficult problems to solve. With the ongoing research and development of quantum computers, these same computationally difficult problems become solvable within reasonable (polynomial) time. The emergence of large-scale quantum computers would put the integrity and confidentiality of today’s data in jeopardy. It then becomes urgent to develop, implement, and test a new suite of cybersecurity measures against attacks from a quantum computer. This paper explores, understands, and evaluates this new category of cryptosystems as well as the many tradeoffs among them. All the algorithms submitted to the National Institute of Standards and Technology (NIST) for standardization can be categorized into three major categories, each relating to the new underlying hard problem: namely error code correcting, algebraic lattices (including ring learning with errors), and supersingular isogenies. These new mathematical hard problems have shown to be resistant to the same type of quantum attack. Utilizing hardware clock cycle registers, the work sets up the benchmarks of the four Round 3 NIST algorithms in two environments: cloud computing and embedded system. As expected, there are many tradeoffs and advantages in each algorithm for applications. Saber and Kyber are exceedingly fast but have larger ciphertext size for transmission over a wire. McEliece key size and key generation are the largest drawbacks but having the smallest ciphertext size and only slightly decreased performance allow a use case where key reuse is prioritized. NTRU finds a middle ground in these tradeoffs, being better than McEliece performance wise and better than Kyber and Saber in ciphertext size allows for a use case of highly varied environments, which need to value speed and ciphertext size equally. Going forward, the benchmarking system developed could be applied to digital signature, another vital aspect to a cryptosystem.

An efficient quantum circuit (program) compiler aims to minimize the gate-count - through efficient instruction translation, routing, gate, and cancellation - to improve run-time and noise. Therefore, a high-efficiency compiler is paramount to enable the game-changing promises of quantum computers. To date, the quantum computing hardware providers are offering a software stack supporting their hardware. However, several third-party software toolchains, including compilers, are emerging. They support hardware from different vendors and potentially offer better efficiency. As the quantum computing ecosystem becomes more popular and practical, it is only prudent to assume that more companies will start offering software-as-a-service for quantum computers, including high-performance compilers. With the emergence of third-party compilers, the security and privacy issues of quantum intellectual properties (IPs) will follow. A quantum circuit can include sensitive information such as critical financial analysis and proprietary algorithms. Therefore, submitting quantum circuits to untrusted compilers creates opportunities for adversaries to steal IPs. In this paper, we present a split compilation methodology to secure IPs from untrusted compilers while taking advantage of their optimizations. In this methodology, a quantum circuit is split into multiple parts that are sent to a single compiler at different times or to multiple compilers. In this way, the adversary has access to partial information. With analysis of over 152 circuits on three IBM hardware architectures, we demonstrate the split compilation methodology can completely secure IPs (when multiple compilers are used) or can introduce factorial time reconstruction complexity while incurring a modest overhead ( 3% to 6% on average).

The Multivariate Polynomial Public Key (MPPK) algorithm, over a prime Galois field, takes a multiplier multivariate polynomial and two multiplicand univariate solvable polynomials to create two product multivariate polynomials. One of variables is for secret message and all others are for noises. The public key consists of all coefficients of the product multivariate polynomials, except the two constant terms for the message variable. The private key is made of both multiplicands. Encryption takes a list of random numbers, over the prime Galois field. The first number is the secret to exchange. The other random numbers generate noise automatically cancelled by decryption. The secret is easily extracted from the evaluation of a solvable equation. The level of security provided by MPPK is adaptable. The algorithm can be used in several different ways. In this paper, we review the performance achieved by MPPK for several combinations of polynomial configurations and Galois field sizes. For every combination, we calculated key generation time, encryption time and decryption time. We also compare the effectiveness of MPPK with the performance of all four NIST PQC finalists. For MPPK, the data has been collected from the execution of an implementation in Java. In comparison to the NIST PQC finalists, MPPK key generation, encryption and decryption performance is excellent.

Distribution of keys in classical cryptography is one of the most significant affairs to deal with. The computational hardness is the fundamental basis of the security of these keys. However, in the era of quantum computing, quantum computers can break down these keys with their substantially more computation capability than normal computers. For instance, a quantum computer can easily break down RSA or ECC in polynomial time. In order to make the keys quantum resistant, Quantum Key Distribution (QKD) is developed to enforce security of the classical cryptographic keys from the attack of quantum computers. By using quantum mechanics, QKD can reinforce the durability of the keys of classical cryptography, which were practically unbreakable during the pre-quantum era. Thus, an extensive study is required to understand the importance of QKD to make the classical cryptographic key distributions secure against both classical and quantum computers. Therefore, in this paper, we discuss trends and limitations of key management protocols in classical cryptography, and demonstrates a relative study of different QKD protocols. In addition, we highlight the security implementation aspects of QKD, which lead to the solution of threats occurring in a quantum computing scenario, such that the cryptographic keys can be quantum resistant.

One of the most essential ways of communication is the wireless network. As a result, ensuring the security of information transmitted across wireless networks is a critical concern. For wireless networks, classical cryptography provides conditional security with several loopholes, but quantum cryptography claims to be unconditionally safe. People began to consider beyond classical cryptosystems for protecting future electronic communication when quantum computers became functional. With all of these flaws in classical cryptosystems in mind, people began to consider beyond it for protecting future electronic communication. Quantum cryptography addresses practically all flaws in traditional cryptography.

Recent advancements in quantum information theory and quantum computation intend the possibilities of breaking the existing classical cryptographic systems. To mitigate these kinds of threats with quantum computers we need some advanced quantum-based cryptographic systems. The research orientation towards this is tremendous in recent years, and many excellent approaches have been reported. In this article, we discuss the probable approaches of the quantum cryptographic systems from implementation point of views to handle the post-quantum cryptographic attacks.

Cloud computing has changed the paradigm of using computing resources. It has shifted from traditional storage and computing to Internet based computing leveraging economy of scale, cost saving, elimination of data redundancy, scalability, availability and regulatory compliance. With these, cloud also brings plenty of security issues. As security is not a one-time solution, there have been efforts to investigate and provide countermeasures. In the wake of emerging quantum computers, the aim of post-quantum cryptography is to develop cryptography schemes that are secure against both classical computers and quantum computers. Since cloud is widely used across the globe for outsourcing data, it is essential to strive at providing betterment of security schemes from time to time. This paper reviews recent development, methods of cloud data security in post-quantum perspectives. It provides useful insights pertaining to the security schemes used to safeguard data dynamics associated with cloud computing. The findings of this paper gives directions for further research in pursuit of more secure cloud data storage and retrieval.

The paradigm of quantum computation has led to the development of new algorithms as well variations on existing algorithms. In particular, novel cryptographic techniques based upon quantum computation are of great interest. Many classical encryption techniques naturally translate into the quantum paradigm because of their well-structured factorizations and the fact that they can be phased in the form of unitary operators. In this work, we demonstrate a quantum approach to data encryption and decryption based upon the McEliece cryptosystem using Reed-Muller codes. This example is of particular interest given that post-quantum analyses have highlighted this system as being robust against quantum attacks. Finally, in anticipation of quantum computation operating over binary fields, we discuss alternative operator factorizations for the proposed cryptosystem.

Quantum computing is poised to be the innovation driver of the next decade. Its information processing capabilities will radically accelerate drug discovery, improve online security, or even boost artificial intelligence [1]. Building a quantum computer promises to have a major positive impact in society, however building the hardware that will enable that paradigm change its one of the greatest technological challenges for humanity.

The advancements in quantum computing and quantum cryptology have recently started to gain momentum and transformation of usable quantum technologies from dream to reality has begun to look viable. This has created an immediate requirement to comprehend quantum attacks and their cryptographic implications, which is a prerequisite obligation to design cryptographic systems resistant to current and futuristic projected quantum and conventional attacks. In this context, this paper reviews the prevalent quantum concepts and analyses their envisaged impact on various aspects of modern-day communication and information security technologies. Moreover, the paper also presents six open-problems and two conjectures, which are formulated to define prerequisite technological obligations for fully comprehending the futuristic quantum threats to contemporary communication security technologies and information assets processed through these systems. Furthermore, the paper also presents some important concepts in the form of questions and discusses some recent trends adapted in cryptographic designs to thwart quantum attacks.

The development of edge computing and machine learning technologies have led to the growth of Industrial IoT systems. Autonomous decision making and smart manufacturing are flourishing in the current age of Industry 4.0. By providing more compute power to edge devices and connecting them to the internet, the so-called Cyber Physical Systems are prone to security threats like never before. Security in the current industry is based on cryptographic techniques that use pseudorandom number keys. Keys generated by a pseudo-random number generator pose a security threat as they can be predicted by a malicious third party. In this work, we propose a secure Industrial IoT Architecture that makes use of true random numbers generated by a quantum random number generator (QRNG). CITRIOT's FireConnect IoT node is used to show the proof of concept in a quantum-safe network where the random keys are generated by a cloud based quantum device. We provide an implementation of QRNG on both real quantum computer and quantum simulator. Then, we compare the results with pseudorandom numbers generated by a classical computer.

With the development of quantum computers, classical cryptography for secure communication is in danger of becoming obsolete. Quantum cryptography, however, can exploit the laws of quantum mechanics to guarantee unconditional security independently of the computational power of a potential eavesdropper. An example is quantum key distribution (QKD), which allows two parties to encrypt a message through a random secret key encoded in the degrees of freedom of quantum particles, typically photons.

At present, in the face of the huge and complex data in cloud computing, the parallel computing ability of quantum computing is particularly important. Quantum principal component analysis algorithm is used as a method of quantum state tomography. We perform feature extraction on the eigenvalue matrix of the density matrix after feature decomposition to achieve dimensionality reduction, proposed quantum principal component extraction algorithm (QPCE). Compared with the classic algorithm, this algorithm achieves an exponential speedup under certain conditions. The specific realization of the quantum circuit is given. And considering the limited computing power of the client, we propose a quantum homomorphic ciphertext dimension reduction scheme (QHEDR), the client can encrypt the quantum data and upload it to the cloud for computing. And through the quantum homomorphic encryption scheme to ensure security. After the calculation is completed, the client updates the key locally and decrypts the ciphertext result. We have implemented a quantum ciphertext dimensionality reduction scheme implemented in the quantum cloud, which does not require interaction and ensures safety. In addition, we have carried out experimental verification on the QPCE algorithm on IBM's real computing platform. Experimental results show that the algorithm can perform ciphertext dimension reduction safely and effectively.