The enhancement of big data security in cloud computing has become inevitable dues to factors such as the volume, velocity, veracity, Value, and velocity of the big data. These enhancements of big data and cloud technologies have computing enabled a wide range of vulnerabilities in applications in organizational business environments leading to various attacks such as denial-of-service attacks, injection attacks, and Phishing among others. Deploying big data in cloud computing environments is a rapidly growing technology that significantly impacts organizations and provides benefits such as demand-driven access to computational services, a distorted version of infinite computing capacity, and assistance with demand-driven scaling up, scaling down, and scaling out. To secure cloud computing for big data processing, a variety of encryption techniques such as RSA, and AES can be applied. However, there are several vulnerabilities during processing. The paper aims to explore the enhancement of big data security in cloud computing using the RSA algorithm to improve the deployment and processing of the variety, volume, veracity, velocity and value of the data utilizing RSA encryptions. The novelty contribution of the paper is threefold: First, explore the current challenges and vulnerabilities in securing big data in cloud computing and how the RSA algorithm can be used to address them. Secondly, we implement the RSA algorithm in a cloud computing environment using the AWS cloud platform to secure big data to improve the performance and scalability of the RSA algorithm for big data security in cloud computing. We compare the RSA algorithm to other cryptographic algorithms in terms of its ability to enhance big data security in cloud computing. Finally, we recommend control mechanisms to improve security in the cloud platform. The results show that the RSA algorithm can be used to improve Cloud Security in a network environment.

Cloud computing has turned into an important technology of our time. It has drawn attention due to its, availability, dynamicity, elasticity and pay as per use pricing mechanism this made multiple organizations to shift onto the cloud platform. It leverages the cloud to reduce administrative and backup overhead. Cloud computing offers a lot of versatility. Quantum technology, on the other hand, advances at a breakneck pace. Experts anticipate a positive outcome and predict that within the next decade, powerful quantum computers will be available. This has and will have a substantial impact on various sciences streams such as cryptography, medical research, and much more. Sourcing applications for business and informational data to the cloud, presents privacy and security concerns, which have become crucial in cloud installation and services adoption. To address the current security weaknesses, researchers and impacted organizations have offered several security techniques in the literature. The literature also gives a thorough examination of cloud computing security and privacy concerns.

IoT shares data with other things, such as applications, networked devices, or industrial equipment. With a large-scale complex architecture de-sign composed of numerous ‘things’, the scalability and reliability of various models stand out. When these advantages are vulnerable to security, constant problems occur continuously. Since IoT devices are provided with services closely to users, it can be seen that there are many users with various hacking methods and environments vulnerable to hacking.

Different contemporary organisations are using cloud computing application in business operation activities to gain competitive advantages over other competitors. It also helps in promoting flexibility of the business operation activities. Cloud computing involves delivery of different computer resources to data centres over the internet services. Different kinds of delivered computer resources include data storage, servers, database, analytics, software, networking, and other types of data applications etc. In this present era of data breaches, cloud computing ensures security protocols to protect different kinds of sensitive transaction data and confidential information. Use of cloud computing ensures that a third party individual does not tamper the data. Use of cloud computing also provides different kinds of competitive advantages to the organisations. Cloud computing also helps in providing efficiency and a platform for innovation for the contemporary organisations. Theoretical frameworks are usedin the literature review section to determine the important roles of cloud computing in effective data and security management in the organisations. It is also justified in the research work that qualitative methodology is suitable for the researcher to meet the developed research objectives. A secondary data analysis approach has been considered by the researcher in this study to carry out the investigation and meet the developed objectives. From the findings, few challenges associated with the cloud computing system have been identified. Proper recommendations are suggested at the end of the study to help future researchers in overcoming the identified associated challenges.

As a result of this new computer design, edge computing can process data rapidly and effectively near to the source, avoiding network resource and latency constraints. By shifting computing power to the network edge, edge computing decreases the load on cloud services centers while also reducing the time required for users to input data. Edge computing advantages for data-intensive services, in particular, could be obscured if access latency becomes a bottleneck. Edge computing raises a number of challenges, such as security concerns, data incompleteness, and a hefty up-front and ongoing expense. There is now a shift in the worldwide mobile communications sector toward 5G technology. This unprecedented attention to edge computing has come about because 5G is one of the primary entry technologies for large-scale deployment. Edge computing privacy has been a major concern since the technology’s inception, limiting its adoption and advancement. As the capabilities of edge computing have evolved, so have the security issues that have arisen as a result of these developments, as well as the increasing public demand for privacy protection. The lack of trust amongst IoT devices is exacerbated by the inherent security concerns and assaults that plague IoT edge devices. A cognitive trust management system is proposed to reduce this malicious activity by maintaining the confidence of an appliance \& managing the service level belief \& Quality of Service (QoS). Improved packet delivery ratio and jitter in cognitive trust management systems based on QoS parameters show promise for spotting potentially harmful edge nodes in computing networks at the edge.

The big data platform based on cloud computing realizes the storage, analysis and processing of massive data, and provides users with more efficient, accurate and intelligent Internet services. Combined with the characteristics of college teaching resource sharing platform based on cloud computing mode, the multi-faceted security defense strategy of the platform is studied from security management, security inspection and technical means. In the detection module, the optimization of the support vector machine is realized, the detection period is determined, the DDoS data traffic characteristics are extracted, and the source ID blacklist is established; the triggering of the defense mechanism in the defense module, the construction of the forwarder forwarding queue and the forwarder forwarding capability are realized. Reallocation.

Cloud computing (CC) is vulnerable to existing information technology attacks, since it extends and utilizes information technology infrastructure, applications and typical operating systems. In this manuscript, an Enhanced capsule generative adversarial network (ECGAN) with blockchain based Proof of authority consensus procedure fostered Intrusion detection (ID) system is proposed for enhancing cyber security in CC. The data are collected via NSL-KDD benchmark dataset. The input data is fed to proposed Z-Score Normalization process to eliminate the redundancy including missing values. The pre-processing output is fed to feature selection. During feature selection, extracting the optimum features on the basis of univariate ensemble feature selection (UEFS). Optimum features basis, the data are classified as normal and anomalous utilizing Enhanced capsule generative adversarial networks. Subsequently, blockchain based Proof of authority (POA) consensus process is proposed for improving the cyber security of the data in cloud computing environment. The proposed ECGAN-BC-POA-IDS method is executed in Python and the performance metrics are calculated. The proposed approach has attained 33.7\%, 25.7\%, 21.4\% improved accuracy, 24.6\%, 35.6\%, 38.9\% lower attack detection time, and 23.8\%, 18.9\%, 15.78\% lower delay than the existing methods, like Artificial Neural Network (ANN) with blockchain framework, Integrated Architecture with Byzantine Fault Tolerance consensus, and Blockchain Random Neural Network (RNN-BC) respectively.

This paper offers a thorough investigation into quantum cryptography, a security paradigm based on the principles of quantum mechanics that provides exceptional guarantees for communication and information protection. The study covers the fundamental principles of quantum cryptography, mathematical modelling, practical applications, and future prospects. It discusses the representation of quantum states, quantum operations, and quantum measurements, emphasising their significance in mathematical modelling. The paper showcases the real-world applications of quantum cryptography in secure communication networks, financial systems, government and defence sectors, and data centres. Furthermore, it identifies emerging domains such as IoT, 5G networks, blockchain technology, and cloud computing as promising areas for implementing quantum cryptographic solutions. The paper also presents avenues for further research, including post-quantum cryptography, quantum cryptanalysis, multi-party quantum communication, and device-independent quantum cryptography. Lastly, it underscores the importance of developing robust infrastructure, establishing standards, and ensuring interoperability to facilitate widespread adoption of quantum cryptography. This comprehensive exploration of quantum cryptography contributes to the advancement of secure communication, information protection, and the future of information security in the era of quantum technology.

Over the past decade, we ve witnessed a remarkable and rapid surge in the realm of high-performance computing. The entire computing landscape, encompassing cloud and fog computing, has seen an unprecedented surge in popularity. Cloud computing, a system interconnecting myriad components, delivers application, data, and storage services over the internet. Quantum computing, on the other hand, harnesses the remarkable phenomena of quantum mechanics like superposition and entanglement for computational purposes. This paper serves as an expansive introduction to the fundamental principles, historical evolution, and breakthroughs in quantum computing, shedding light on its applications in network technology and cryptography. Moreover, it delves into the exciting potential for future game development empowered by quantum technology. In particular, we ll uncover the latest strides in cognitive networking and cryptography, drawing attention to the cutting-edge developments. Finally, we ll scrutinize the on-going research endeavours and lingering questions demanding further exploration within the dynamic realm of quantum computing.

Sustainability within the built environment is increasingly important to our global community as it minimizes environmental impact whilst providing economic and social benefits. Governments recognize the importance of sustainability by providing economic incentives and tenants, particularly large enterprises seek facilities that align with their corporate social responsibility objectives. Claiming sustainability outcomes clearly has benefits for facility owners and facility occupants that have sustainability as part of their business objectives but there are also incentives to overstate the value delivered or only measure parts of the facility lifecycle that provide attractive results. Whilst there is a plethora of research on Building Information Management (BIM) systems within the construction industry there has been limited research on BIM in the facilities management \& sustainability fields. The significant contribution with this research is the integration of blockchain for the purposes of transaction assurance with development of a working model spanning BIM and blockchain underpinning phase one of this research. From an industry perspective the contribution of this paper is to articulate a path to integrate a wide range of mature and emerging technologies into solutions that deliver trusted results for government, facility owners, tenants and other directly impacted stakeholders to assess the sustainability impact.

The changes in technologies has also changed the way we compute. Computing applications provide various types of functionalities. However, a common thing is to secure the same computing system. It requires a high level of developer skills to secure a system. Generally, verifying users before access of services, encryption of data, and techniques of parallel access of information by multiple users is done to ensure only valid users can access the services. One need to verify person, device, process, or service before it access the related service(s). In this paper, we present a review of authentication techniques used in computing computing. It elaborates methods used for traditional authentication using articles, letters, people, passwords, one-time passwords, digital certificates, two-way authentication to latest behavioural, doodles, image sequence, gestures based recognition of users using biometrics, gait-based and their behavioural analytics. It also discusses key features of various methods including gaps and scope of improvement.

Data encryption is the process of turning data into encrypted data. It is a crucial technology for securing data while it is being stored or transmitted, especially in cloud environments where data is stored remotely and accessed over the internet. In our study, we compared five well-known algorithms to determine which is the most reliable for data encryption in cloud environments. This research study provides insights into the performance of different data encryption algorithms in the cloud environment and their potential applications in various industries. There are several benefits of using data encryption, including cost efficiency, management control and remote worker protection. Encryption is cheap to implement as many of today s devices and systems come with built-in encryption technology. Encryption can free organizations from government-imposed regulatory fines as some governments have mandated regulations and requirements regarding data protection that require private data to be encrypted and prevent all unauthorized access and all illegal activities. Encryption can help secure and protect remote workers by securing their data and communications. As more and more employees opt for remote working, that is, working from home, the need for data security has become more important.

In today s world, security is a very important issue. People should always keep their belongings safe. To increase security, this research work proposes a IoT-based smart lockers with sensors and access keys with security, verification, and user-friendly tools. This model alerts the user when someone else tries to access their locker and quickly sends an alarm to the authorized user, and provides the option to either grant or reject access to the valid user. In this paper, smart locker is kept registered early to use a locker in the bank, office, home, etc. to ensure safety. The user demands to send an unlock direction with the help of microcontroller NUDE MCU ESP8266 and after accepting the command from the cloud (BLYNK APP), only the user can unlock the closet and access the valuables. This study has also introduced the encroachment detection in lockers with sensors and finally installed smart lockers with fire alarms for security and reliability.

In today s world, security is a very important issue. People should always keep their belongings safe. To increase security, this research work proposes a IoT-based smart lockers with sensors and access keys with security, verification, and user-friendly tools. This model alerts the user when someone else tries to access their locker and quickly sends an alarm to the authorized user, and provides the option to either grant or reject access to the valid user. In this paper, smart locker is kept registered early to use a locker in the bank, office, home, etc. to ensure safety. The user demands to send an unlock direction with the help of microcontroller NUDE MCU ESP8266 and after accepting the command from the cloud (BLYNK APP), only the user can unlock the closet and access the valuables. This study has also introduced the encroachment detection in lockers with sensors and finally installed smart lockers with fire alarms for security and reliability.

In the landscape of modern computing, fog computing has emerged as a service provisioning mechanism that addresses the dual demands of low latency and service localisation. Fog architecture consists of a network of interconnected nodes that work collectively to execute tasks and process data in a localised area, thereby reducing the delay induced from communication with the cloud. However, a key issue associated with fog service provisioning models is its limited localised processing capability and storage relative to the cloud, thereby presenting inherent issues on its scalability. In this paper, we propose volunteer computing coupled with optimisation methods to address the issue of localised fog scalability. The use of optimisation methods ensures the optimal use of fog infrastructure. To scale the fog network as per the requirements, we leverage the notion of volunteer computing. We propose an intelligent approach for node selection in a trustworthy fog environment to satisfy the performance and bandwidth requirements of the fog network. The problem is formulated as a multi-criteria decision-making (MCDM) problem where nodes are evaluated and ranked based on several factors, including service level agreement (SLA) parameters and reputation value.

The digitalization and smartization of modern digital systems include the implementation and integration of emerging innovative technologies, such as Artificial Intelligence. By incorporating new technologies, the surface attack of the system also expands, and specialized cybersecurity mechanisms and tools are required to counter the potential new threats. This paper introduces a holistic security risk assessment methodology that aims to assist Artificial Intelligence system stakeholders guarantee the correct design and implementation of technical robustness in Artificial Intelligence systems. The methodology is designed to facilitate the automation of the security risk assessment of Artificial Intelligence components together with the rest of the system components. Supporting the methodology, the solution to the automation of Artificial Intelligence risk assessment is also proposed. Both the methodology and the tool will be validated when assessing and treating risks on Artificial Intelligence-based cybersecurity solutions integrated in modern digital industrial systems that leverage emerging technologies such as cloud continuum including Software-defined networking (SDN).

IBMD(Intelligent Behavior-Based Malware Detection) aims to detect and mitigate malicious activities in cloud computing environments by analyzing the behavior of cloud resources, such as virtual machines, containers, and applications.The system uses different machine learning methods like deep learning and artificial neural networks, to analyze the behavior of cloud resources and detect anomalies that may indicate malicious activity. The IBMD system can also monitor and accumulate the data from various resources, such as network traffic and system logs, to provide a comprehensive view of the behavior of cloud resources. IBMD is designed to operate in a cloud computing environment, taking advantage of the scalability and flexibility of the cloud to detect malware and respond to security incidents. The system can also be integrated with existing security tools and services, such as firewalls and intrusion detection systems, to provide a comprehensive security solution for cloud computing environments.

Due to its adaptability and pay-per-use services, cloud computing has grown in popularity among businesses, but security and privacy issues are still very much present. Intruders can exploit vulnerabilities in the open and dispersed nature of cloud environments, leading to attacks that can damage entire projects within a short period of time. To address this issue, organizations need to implement effective intrusion detection systems (IDS) that can detect and alert administrators of any suspicious activities. There are three widely used methods for IDS: signature-based detection, anomaly-based detection, and hybrid detection. Hybrid detection, which combines the strengths of signature-based and anomaly-based detection, has been shown to produce superior results. IDS can be categorized into host- based IDS (HIDS), network-based IDS (NIDS), hypervisor-based IDS, and distributed IDS (DIDS), each with their own unique characteristics and benefits. The CICIDS2017 dataset provides a diverse set of attacks and benign traffic for researchers and practitioners to develop and evaluate IDS systems. Overall, putting in place a strong intrusion detection system is critical for maintaining the security and privacy of cloud-based projects, as well as ensuring their availability.

The increase in the usage of various computing and mobile devices has resulted in implementing large scale ad hoc networks as the user demand is on the rise and companies’ find it difficult to invest more in the IT infrastructure to meet the surging demand. The traditional model of networking enables the mobile devices to face various issues like lower bandwidth, mobility, security and storage et. Hence, in order to meet the overall service requirement and to enhance the overall efficiency of the network, cloud computing was introduced. The implementation of these devices tends to support in every node, it enhances better communication in a better range towards another nodes. There is a critical administration and support devices from everywhere in an effective manner.

The releases of Intel SGX and AMD SEV mark the transition of hardware-based enclaves from research prototypes to mainstream products. These two paradigms of secure enclaves are attractive to both the cloud providers and tenants, since security is one of the key pillars of cloud computing. However, it is found that current hardware-defined enclaves are not flexible and efficient enough for the cloud. For example, although SGX can provide strong memory protection with both confidentiality and integrity, the size of secure memory is tightly restricted. On the contrary, SEV enables enclaves to use more memory but has critical security flaws due to no memory integrity protection. Meanwhile, both types of enclaves have relatively long booting latency, which makes them not suitable for short-term tasks like serverless workloads. After an in-depth analysis, we find that there are some intrinsic tradeoffs between security and performance due to the limitation of architectural designs. In this article, we investigate a novel hardware-software co-design of enclaves to meet the requirements of cloud by placing a part of the logic of the enclave mechanism into a lightweight software layer, named Enclavisor, to achieve a balance between security, performance, and flexibility. Specifically, our implementation is based on AMD’s SEV and, Enclavisor is placed in the guest kernel mode of SEV’s secure virtual machines. Enclavisor inherently supports memory encryption with no memory limitation and also achieves efficient booting, multiple enclave granularities, and post-launch remote attestation. Meanwhile, we also propose hardware/ software solutions to mitigate the security flaws caused by the lack of memory integrity. We implement a prototype of Enclavisor on an AMD SEV server. The experiments on both micro-benchmarks and application benchmarks show that enclaves on Enclavisor can have close-to-native performance.

The releases of Intel SGX and AMD SEV mark the transition of hardware-based enclaves from research prototypes to mainstream products. These two paradigms of secure enclaves are attractive to both the cloud providers and tenants, since security is one of the key pillars of cloud computing. However, it is found that current hardware-defined enclaves are not flexible and efficient enough for the cloud. For example, although SGX can provide strong memory protection with both confidentiality and integrity, the size of secure memory is tightly restricted. On the contrary, SEV enables enclaves to use more memory but has critical security flaws due to no memory integrity protection. Meanwhile, both types of enclaves have relatively long booting latency, which makes them not suitable for short-term tasks like serverless workloads. After an in-depth analysis, we find that there are some intrinsic tradeoffs between security and performance due to the limitation of architectural designs. In this article, we investigate a novel hardware-software co-design of enclaves to meet the requirements of cloud by placing a part of the logic of the enclave mechanism into a lightweight software layer, named Enclavisor, to achieve a balance between security, performance, and flexibility. Specifically, our implementation is based on AMD’s SEV and, Enclavisor is placed in the guest kernel mode of SEV’s secure virtual machines. Enclavisor inherently supports memory encryption with no memory limitation and also achieves efficient booting, multiple enclave granularities, and post-launch remote attestation. Meanwhile, we also propose hardware/ software solutions to mitigate the security flaws caused by the lack of memory integrity. We implement a prototype of Enclavisor on an AMD SEV server. The experiments on both micro-benchmarks and application benchmarks show that enclaves on Enclavisor can have close-to-native performance.

In the context of cloud environments, data providers entrust their data to data consumers in order to allow further computing on their own IT infrastructure. Usage control measures allow the data provider to restrict the usage of its data even on the data consumer’s system. Two of these restrictions can be the geographic location and time limitations. Current solutions that could be used to enforce such constraints can be easily manipulated. These include solutions based on the system time, organizational agreements, GPS-based techniques or simple delay measurements to derive the distance to known reference servers.

With the development of cloud computing and edge computing, data sharing and collaboration have become increasing between cloud edge and end. Under the assistance of edge cloud, end users can access the data stored in the cloud by data owners. However, in an unprotected cloud-edge-end network environment, data sharing is vulnerable to security threats from malicious users, and data confidentiality cannot be guaranteed. Most of the existing data sharing approaches use the identity authentication mechanism to resist unauthorized accessed by illegal end users, but the mechanism cannot guarantee the credibility of the end user’s network environment. Therefore, this article proposes an approach for trusted sharing of data under cloud-edge-end collaboration (TSDCEE), in which we verify the trustworthiness of the data requester’s network environment based on the mechanism of attribute remote attestation. Finally, this article uses model checking Spin method to formally analyze TSDCEE, and verifies the security properties of TSDCEE.

In today s world, security is a very important issue. People should always keep their belongings safe . To increase security, this research work proposes a IoT-based smart lockers with sensors and access keys with security, verification, and user-friendly tools. This model alerts the user when someone else tries to access their locker and quickly sends an alarm to the authorized user, and provides the option to either grant or reject access to the valid user. In this paper, smart locker is kept registered early to use a locker in the bank, office, home, etc. to ensure safety. The user demands to send an unlock direction with the help of microcontroller NUDE MCU ES P8266 and after accepting the command from the cloud (BLYNK APP), only the user can unlock the closet and access the valuables. This study has also introduced the encroachment detection in lockers with sensors and finally installed smart lockers with fire alarms for security and reliability.

Recently, the manufacturing industry is changing into a smart manufacturing era with the development of 5G, artificial intelligence, and cloud computing technologies. As a result, Operational Technology (OT), which controls and operates factories, has been digitized and used together with Information Technology (IT). Security is indispensable in the smart manu-facturing industry as a problem with equipment, facilities, and operations in charge of manufacturing can cause factory shutdown or damage. In particular, security is required in smart factories because they implement automation in the manufacturing industry by monitoring the surrounding environment and collecting meaningful information through Industrial IoT (IIoT). Therefore, in this paper, IIoT security proposed in 2022 and recent technology trends are analyzed and explained in order to understand the current status of IIoT security technology in a smart factory environment.