Securing the Future of Library Cloud Infrastructure with AQFA: Adaptive Quantum-Resistant Authentication

In today’s digital landscape, where data is a critical asset for businesses, building a resilient backup infrastructure is paramount to ensuring data availability and protection. This research investigates the synergy between three essential elements—data redundancy, encryption, and Role-Based Access Control (RBAC) to enhance backup system resilience. Data redundancy, achieved through methods like the 3-2-1 rule and cloud replication, ensures continuous availability and protection against hardware failures. Encryption secures backup data, making it unreadable to unauthorized users and safeguarding sensitive information in compliance with regulatory standards. RBAC, on the other hand, provides granular control over user access, enforcing the principle of least privilege and minimizing the risk of unauthorized data manipulation. By combining these strategies, organizations can mitigate the risks of data loss, breaches, and unauthorized access, creating a robust, secure, and efficient backup infrastructure. This paper provides a comprehensive analysis of how these technologies can be integrated, offers best practices for implementation, and discusses the future of backup systems in an increasingly complex threat environment. Keywords: Backup Infrastructure, Data Redundancy, Data Encryption, Role-Based Access Control, RBAC, Data Security, Disaster Recovery, Data Protection, Cloud Backup, Data Availability, Security Best Practices, IT Resilience, Cybersecurity, Backup Strategies.

Encryption of data is a cornerstone of information security with confidentiality, integrity, and availability of sensitive information. However, the advent of quantum computing (QC) adds complexity to the classical encryption mechanisms by threatening their quantum resilience. This work looks into incorporating QC into cryptographic schemes through the evolution of an Elliptic Quantum Cryptosystem (EQC), fusing elliptic curve cryptography (ECC) and quantum annealing. The objective is to offer protection against attacks in conventional cryptographic schemes and enhance quantum attack resistance. Quantum annealing maximizes encryption through quantum fluctuations to locate best solutions, resulting in higher efficiency and reliability. The research examines top performance measures, including encryption time, decryption time, bit error rate (BER), computational efficiency, level of security, and scalability. Experimental results confirm that the proposed EQC technique has improved performance compared to existing approaches. Specifically, it takes 35 ms encryption time, 40 ms decryption time, 0.0005% BER, 80 seconds computational complexity, 9 level of security, and graded scalability as 8. These outcomes confirm the efficiency of the approach in enhancing encryption security and adaptability against quantum attacks. The problem addressed is the vulnerability of classical encryption systems to quantum advancements. By the addition of quantum-safe procedures, EQC provides a safe alternative, ensuring data confidentiality and integrity during the era of quantum. Disadvantages are the challenge in using quantum annealing and scalability problems for larger datasets. Future researches need to focus on the optimization of quantum approaches, addressing scalability issues, and studying real-world applications to ensure the generalizability of this new approach.

Virtualization technologies employed by the cloud providers allow scalable and fast deployment of computation resources at a small cost. Being a core component in the cloud configuration, the hypervisor becomes the target of outside attacks that try to disrupt the normal operation of other users' systems or to gain control over the cloud infrastructure. Therefore, an effective and reliable method of discovering security vulnerabilities inside the hypervisors is needed.We created a testing environment that employs fuzzing to detect possible vulnerabilities inside the Firecracker hypervisor. We present a complete fuzzing toolchain that can be integrated into the Firecracker development cycle to discover and report bugs that can be missed by other testing methods. Our solution was internally tested by the Amazon Web Services team with promising results.

This issue of Libellarium includes papers from the invited speakers who gave lectures at the Summer School in User Studies (SSUS) organized by the Department of Information Sciences and held at the University of Zadar, 11. - 14. April, 2012. The SSUS is associated with the Knowledge Society and Information Transfer PhD programme at the Department of Information Sciences at the University of Zadar. This programme is designed for Croatian and international doctoral students in the field of theories and studies of information needs and use, as well as the field of reading and learning concepts and strategies in digital environment. The main goal of the Summer School 2012 was to introduce the participants to the most recent research, the latest developments and the newly emerged concepts in the fields of users’ information behaviour, learning and education in the digital age, information literacy theories and concepts, as well as the reading paradigms. In the recent times the information society changes rapidly which influences processing and the approaches to information while it changes the existing paradigms of learning and education. New literacies emerge and reading, as the key competency necessary to access the information, changes its forms and practices. The SUSS organized the above mentioned issues in three segments: Users’ information behaviour, Literacy and reading in the digital environment, and Learning and education in the digital age. In the Users’ information behaviour segment this issue of Libellarium contains articles from two invited speakers and two doctoral students who discuss the subject from different viewpoints. Paul Sturges starts with the assumption that people are much more dependent than they realise on information and ideas that are acquired and processed by areas of the brain, not always immediately accessible to the conscious mind. Polona Vilar discusses information behaviour of scholars and scholarly practice influenced by increased accessibility of digital resources and tools. Doctoral students Dora Rubinic and Darko Lacovic base their literature reviews on the specific context of university students’ information behaviour. The former review deals with information behavior of university students in general, while the latter one deals with university students’ information behaviour in relation to the role of academic libraries. Four invited speakers discuss literacy and reading in the digital environment. Livija Knaflic presents literacy as a complex phenomenon and focuses her work toward psychological aspects of literacy. Sonja Spiranec investigates information literacy in the context of Web 2.0 which transformed information environments into complex and unstructured places so the contexts of information literacy are being re-examined and reshaped respectively. Ivanka Kuic writes about the postmodern theoretical approaches to the reader and the validity of these approaches in the digital environment while emphasizing that existing concepts of the reader and reading adapt to electronic environment, because the electronic text deconstructs the printed one and it changes the way of reading. Vita Mozuraite discusses these rapid changes in the reading paradigm in the age of e-book to which the young readers are especially susceptible considering their frequent use of the internet. The changes in information environment influence learning. This fact demands careful consideration from education experts in order to achieve the maximal degree of the rich media environment contribution to the quality of education. Hence, Milan Matijevic writes about the influence the e-environment has on the new curriculum paradigms. These papers are the starting point for the new directions of thought about the changes in the digital environment that reflect on information behaviour, learning and the related practices. The papers were received in 2012/2013 and were peer reviewed in 2013/2014. * Department of Information Sciences, University of Zadar, Croatia e-mail: istricev@unizd.hr

More than ever, the healthcare industry witnesses a remarkable transformation with cloud computing becoming a new data-driven era involving healthcare delivery. However, existing methodologies lean heavily on classical encryption algorithms but will alter with emerging and new security threats. This work lies the exhibition of a new paradigm involving NTRU, (N-th degree truncated polynomial ring units), a post-quantum key generation method, and salsa20 for fast data encryption. The entire process involves the generation of keys from the NTRU polynomial-based private-public key pairs and the actual encryption of data using the salsa20 keystream in order for secure data storage inside the cloud environment. The encrypted data is uploaded to the cloud, and decryption is carried out by the authorized receivers using the complete key and the nonce. Results indicated a relationship between the cryptographic processing time, which gradually increased from 2200 ms for a 75-bit key to 3500 ms for a 250-bit key. Further, encryption time went from 2000 ms for a 50-bit key to 16,000 ms for a 300-bit key, while decryption time was observed between 10 ms for a 500-bit key and over 700 ms for a 3500-bit key. Thus, it provides extra strength against quantum attacks yet also balances the performance and makes it viable for future healthcare data protection.

The rapid expansion of the Internet of Things (IoT) has introduced unprecedented cybersecurity challenges, as traditional cryptographic methods struggle to provide both efficiency and quantum resistance in resource-constrained environments. This research introduces Adaptive Quantum Cryptography (AQC), a novel security framework that integrates Quantum Key Distribution (QKD), Post-Quantum Cryptography (PQC), Quantum Random Number Generators (QRNGs), and AI-driven dynamic adaptation to safeguard IoT networks against evolving cyber threats. Unlike classical encryption techniques such as RSA and ECC, which are vulnerable to quantum attacks, AQC leverages quantum mechanical principles—such as superposition, entanglement, and the no-cloning theorem—to ensure provably secure key exchange and data encryption. The proposed AQC system dynamically adjusts cryptographic protocols based on real-time network conditions, computational resources, and threat intelligence, optimizing security without imposing excessive overhead. Experimental evaluations demonstrate that AQC achieves a 70% improvement in key exchange efficiency, a 50% reduction in computational load, and a 95% resilience rate against quantum attacks compared to conventional encryption methods. Additionally, the integration of QRNGs enhances cryptographic key entropy, while AI-driven anomaly detection enables proactive threat mitigation. This framework is particularly suited for next-generation IoT applications, including smart grids, autonomous vehicles, and industrial automation, where security, scalability, and energy efficiency are critical. By combining quantum-resistant algorithms with adaptive security mechanisms, AQC provides forward secrecy, resistance to quantum adversaries, and robust authentication, ensuring long-term protection for IoT ecosystems in the post-quantum era. The findings underscore AQC’s potential as a foundational security architecture for future quantum-safe IoT networks.

As cloud computing continues to gain traction, a great deal of effort is being expended in researching the most effective ways to build and manage secure and trustworthy clouds. Providing consistent security services in on-demand provisioned Cloud infrastructure services is of primary importance due to the multi-tenant and potentially multi-provider nature of Cloud Infrastructure. Cloud security infrastructure should address two aspects of the IaaS operation and dynamic security services provisioning: (1) provide security infrastructure for secure Cloud IaaS operation; (2) provisioning dynamic security services. Although the first task is a traditional task in security engineering, dynamic provisioning of managed security services in virtualized environment remains a problem and requires additional research. Entire frameworks have been proposed and demonstrated but although successful, there is a tendency to see such solutions as integrated 'all in one' infrastructures. This paper describes a light-weight mechanism and protocol for building trust between two machines that takes advantage of the Trusted Platform Module (TPM) to handle a key exchange and remote trusted deployment of a bootstrapping tool (referred to as the Bootstrapping Initiator (BI)). Once deployed, the BI can execute any arbitrary software required which could be (but is not limited to) solutions for advanced architecture management such as the Dynamic Access Control Infrastructure (DACI). The proposed solution provides a light-weight layer of trust backed by a TPM that additional systems can build upon as required by the individual use case without the requirement for a specific management or security infrastructure to be deployed along with it.

Quantum-mechanical devices have the potential to transform cryptography. Most research in this area has focused either on the information-theoretic advantages of quantum protocols or on the security of classical cryptographic schemes against quantum attacks. In this work, we initiate the study of another relevant topic: the encryption of quantum data in the computational setting. In this direction, we establish quantum versions of several fundamental classical results. First, we develop natural definitions for private-key and public-key encryption schemes for quantum data. We then define notions of semantic security and indistinguishability, and, in analogy with the classical work of Goldwasser and Micali, show that these notions are equivalent. Finally, we construct secure quantum encryption schemes from basic primitives. In particular, we show that quantum-secure one-way functions imply IND-CCA1-secure symmetric-key quantum encryption, and that quantum-secure trapdoor one-way permutations imply semantically-secure public-key quantum encryption.

This study investigates proactive monitoring and security within cloud infrastructure, focusing on implementing tools like Prometheus, Grafana, and HashiCorp Vault to enhance operational resilience and data security. As cloud adoption grows, so does the complexity of maintaining secure systems amidst ever-evolving threats and regulatory pressures. By integrating these tools within DevOps workflows, organizations can achieve real-time monitoring, visualization, and secure access management, significantly strengthening their cloud environments. A systematic literature review was conducted, examining each tool's unique capabilities, the limitations they address, and the potential for combined functionality to offer a layered security approach. The findings reveal that while these tools are invaluable for preemptively detecting threats and managing access, they require continuous refinement to meet scalability, compatibility, and compliance demands. This study concludes that a proactive, integrative approach utilizing Prometheus for data collection and alerting, Grafana for visualization, and HashiCorp Vault for secret management fosters robust cloud security practices. Recommended strategies include adopting zero-trust architectures, utilizing automated compliance tools, and integrating sustainability principles in cloud management to ensure both security and operational efficiency. Ultimately, this study emphasizes the need for adaptive security frameworks that evolve alongside technological advancements, positioning organizations to safeguard their digital assets and respond to emerging threats with agility and confidence.

Advances in quantum computers may pose a significant threat to existing public-key encryption methods, which are crucial to the current infrastructure of cyber security. Both RSA and ECDSA, the two most widely used security algorithms today, may be (in principle) solved by the Shor algorithm in polynomial time due to its ability to efficiently solve the discrete logarithm problem, potentially making present infrastructures insecure against a quantum attack. The National Institute of Standards and Technology (NIST) reacted with the post-quantum cryptography (PQC) standardization process to develop and optimize a series of post-quantum algorithms (PQAs) based on difficult mathematical problems that are not susceptible to being solved by Shor’s algorithm. Whilst high-powered computers can run these PQAs efficiently, further work is needed to investigate and benchmark the performance of these algorithms on lower-powered (constrained) devices and the ease with which they may be integrated into existing protocols such as TLS. This paper provides quantitative benchmark and handshake performance data for the most recently selected PQAs from NIST, tested on a Raspberry Pi 4 device to simulate today’s IoT (Internet of Things) devices, and provides quantitative comparisons with previous benchmarking data on a range of constrained systems. CRYSTALS-Kyber and CRYSTALS-Dilithium are shown to be the most efficient PQAs in the key encapsulation and signature algorithms, respectively, with Falcon providing the optimal TLS handshake size.

The adoption of cloud computing in regulated industries like in healthcare, finance and government has escalated the necessity of continuous compliance verification of security controls. Conventional compliance controls are based on periodic auditing and validation tools that are rule based and not dynamic enough to meet the large scale cloud infrastructures. The solution is that such approaches tend to yield slow detection, excessive false positive rate, and poor contextual recognition. This paper attempts to provide Deep Learning-powered Compliance Automation architecture to monitor security controls in regulated cloud systems continuously. The suggested architecture combines the multi-source telemetry, such as cloud logs, configuration states, identity records, and policy metadata, into a single pipeline of analytical processing. High quality deep learning models such as LSTM based sequence learning, convolutional feature learning and transformer based semantic analysis are used to identify anomalies, configuration drift and control violation by regulations in real-time. High-level regulatory requirements are translated into machine-readable rules by a control mapping and policy encoding mechanism and the detected violations are prioritized in a dynamic risk scoring module depending on their severity and compliance impact. Experimental analysis has shown a better detection rate, false positives have been minimized, and real-time monitoring is more efficient as opposed to conventional rule-driven systems. The framework contains scalable, adaptive and regulation conscious compliance management in multi-cloud environment. The study demonstrates that deep learning can transform the compliance assurance system to ensure security governance within the contemporary cloud infrastructure.

In this paper, privacy preserving at the cloud side is enabled by adopting Homomorphic Encryption (HE) as a major solution for protecting users' sensitive data. As a Proof Of Concept (POC), we take the case of a university that is adopting the cloud as a practical method for storing and operating over its private data. The main contribution of this application is that different data are stored encrypted at the cloud side. Students' data such as name, gender, date of birth, etc are encrypted using AES and hash functions. Students' indexes and grades are encrypted homomorphically using our modified Domingo Ferrer (DF) encryption scheme [1]. The main importance of the usage of HE in this application is allowing the process over encrypted data at the cloud side such as computing encrypted students' average. Different queries are sent from the university side to the cloud side, after operating and processing over encrypted data all results are shipped back encrypted to the university where the primitive data is recovered. Cloud infrastructure is created using Apache CloudStack and different encryption schemes are implemented under Python using SageMath library.

In the dynamic landscape of cloud computing, ensuring the resilience and availability of data is paramount, particularly in emergency situations such as cyberattacks, system failures, or natural disasters. This abstract presents a comprehensive examination of emergency backup strategies tailored specifically for cloud environments. It delves into the challenges associated with data loss and downtime, emphasizing the critical need for proactive measures to mitigate risks and safeguard valuable data assets. By exploring various backup methodologies including incremental backups, differential backups, and snapshot-based backups, this abstract provides insights into the diverse approaches available for creating robust data redundancy in the cloud. Furthermore, it discusses the importance of geographical redundancy, data encryption, and access controls in enhancing the security and integrity of backup data. Additionally, emerging technologies such as blockchain-based backup solutions and AI-driven anomaly detection systems are explored as potential avenues for further enhancing data resilience in the cloud. By adopting a proactive approach to emergency data backup, organizations can fortify their cloud infrastructures against unforeseen disruptions and ensure the continuous availability and integrity of their critical data assets

Digital Forensics has become an indispensable tool in contemporary cybercrime investigations, which ensures systematic identification, collection, preservation, and presentation of electronic evidence in a legally admissible manner. As cybercrimes continue to escalate, investigative authorities are required to operate across multiple digital domains, including personal devices, mobile platforms, cloud infrastructures, and transnational communication networks, with strict adherence to the law. Digital forensics is important not only because it can recover the deleted or concealed data, but also because it ensures that the evidence remains authentic and untouched throughout the investigation. Due to its dual emphasis on both technology and law, it effectively bridges the gap between technical accuracy and legal accountability. Despite being so advanced in the contemporary world, the field of digital forensics still faces persistent challenges. The extensive reliance on data encryption, rapid technological innovations, and the issue of complex jurisdiction in cross-border investigations complicate and hamper the effective use of digital forensics. Moreover, the escalation of data generated in the digital age raises concerns about privacy, transparency, and the timely administration of justice. Addressing these concerns requires some advanced and well-developed standardized forensic frameworks, legal protocols, and greater international cooperation to harmonize investigative procedures. This paper shall dwell upon the continuous evolution of the role of digital forensics in cybercrimes in the contemporary world. It shall particular ly focus on the foundations, challenges, evidentiary value, and implications for law enforcement and global cybersecurity. It shall also emphasize the strengthening of digital forensics so that harmonious international relations and global cybersecurity can be achieved.

The aggression of russia has created numerous problems in terms of legal and organizational protection of personal data. Therefore, this article analyzes the current state and prospects of personal data protection during a state of war. The author examines the changes to legislation in this field caused by russia’s full-scale invasion and analyzes the state of cybersecurity legislation in Ukraine as part of personal data protection.Emphasis is placed on the fact that effective protection of personal data is impossible without ensuring cybersecurity. The experience of Estonia as a leading European country in this field is highlighted. The main directions of Estonia’s data protection policy are indicated.The analysis of legislation and law enforcement practices highlights a number of issues, such as the absence of a plan for cyber attacks and the vulnerability of devices used for photo and video documentation at checkpoints. It is expressed that these shortcomings need to be addressed through the adoption of a new law on personal data protection.Regarding the prospects of personal data protection in a state of war, the article argues that measures for safeguarding personal data should be taken by both private individuals and state institutions. Private individuals should employ measures such as using reliable software and data encryption. State institutions should implement the following measures: in the event of a threat of occupation of a specific locality, the authorities and their officials should destroy documents and other physical media containing personal data of Ukrainian citizens.The overall conclusion is that the protection of personal data is a constant challenge, and the development of new technologies requires continual updating of security measures. Users and organizations must be knowledgeable and cautious in the processing and transmission of personal data, while legislation and standards need to constantly adapt to changes in the digital environment and the military-political sphere.