Technical Issues of Forensic Investigations in Cloud Computing Environments

The IT Industry and the wider media are abuzz with the phrase “cloud computing” and most of us have no idea what this latest terminology means. This paper starts by addressing the question – “what is cloud computing, and provides an understanding of the technology?” Cloud computing is related to technologies that has been around for ages, however, what can be done differently with the same technology when integrated with Internet is cloud computing.Individuals who might be considering cloud computing services for personal use will also benefit by the information provided. Web sites like Flickr, FaceBook, YouTube and others are used to store and share personal photos, music and videos for free. Easy as: 1). Register, 2). Upload, 3). Share. Free and easy, there has to be a downside, and there is awareness regarding this.There is information regarding cloud computing for businesses! Businesses, who wish to get on the “flight to the clouds” like their peers to keep their heads above the “cloud” and competition. With cloud service providers, businesses can tap into the IT services that they need, when they need, for as long as they need; without investing in any IT infrastructure. The result is a far more agile and cost-effective IT services and this paper looks at how and why.After looking at the good of cloud computing, the bad, and the ugly is revealed. Not all our experiences on the Internet have been totally positive. A range of security and trust issues exist. Individuals and businesses ask is “how secured are their information once it is with the cloud service providers?” There is analysis on the ownership of data and information stored with the cloud service providers and taxonomy of data that you post on social networking web sites.Finally, anecdotes about cloud computing that support our endeavour to compute in the cloud. Cloud computing is not a hype, it is a reality. Cloud computing is not a fad, it is here to stay. The question is no longer “will cloud computing happen?” but “how you are going to exploit this technology?”Keywordscloud computingvirtual computingcluster computingdistributed computingpervasive computing

Cloud computing has become a cornerstone of modern IT infrastructure, offering scalability and efficiency but also exposing organizations to evolving cyber threats such as data breaches, insider threats, and advanced persistent threats (APTs). Traditional security mechanisms struggle to address these dynamic challenges, necessitating the integration of AI-driven threat detection and prevention strategies. This conceptual paper explores the comparative effectiveness of supervised learning, unsupervised learning, reinforcement learning, and hybrid AI models in cloud security. Supervised learning excels in identifying known attack patterns, while unsupervised learning is crucial for detecting zero-day threats and anomalies. Reinforcement learning enables self-adaptive security measures, and hybrid models offer a comprehensive, multi-layered approach to cloud security. However, AI-driven cybersecurity faces significant challenges, including data privacy risks, bias in threat detection, adversarial AI attacks, and lack of model interpretability. Emerging AI trends such as federated learning, quantum security, and explainable AI (XAI) are shaping the future of cloud security, while regulatory frameworks like GDPR, NIST AI Risk Management, and the EU AI Act play a crucial role in standardizing ethical AI use. This study provides insights into the strengths, weaknesses, and future directions of AI-driven cloud security, offering recommendations for researchers, policymakers, and cybersecurity practitioners to enhance AI resilience against emerging threats.

Managing Cloud Computing Environment: Gaining Customer Trust with Security and Ethical Management

Online service is used to be as Pay-Per-Use in Cloud computing. Service user need not be in a long time contract with cloud service providers. Service level agreements (SLAs) are understandings marked between a cloud service providers and others, for example, a service user, intermediary operator, or observing operators. Since cloud computing is an ongoing technology giving numerous services to basic business applications and adaptable systems to manage online agreements are significant. SLA maintains the quality-of-service to the cloud user. If service provider fails to maintain the required service SLA is considered to be SLA violated. The main aim is to minimize the SLA violations for maintain the QoS of their cloud users. In this research article, a toolbox is proposed to help the procedure of exchanging of a SLA with the service providers that will enable the cloud client in indicating service quality demands and an algorithm as well as Negotiation model is also proposed to negotiate the request with the service providers to produce a better agreement between service provider and cloud service consumer. Subsequently, the discussed framework can reduce SLA violations as well as negotiation disappointments and have expanded cost-adequacy. Moreover, the suggested SLA toolkit is additionally productive to clients so clients can secure a sensible value repayment for diminished QoS or conceding time. This research shows the assurance level in the cloud service providers can be kept up by as yet conveying the services with no interruption from the client's perspective

Enhancement of Security in Cloud Maas and JUJU Using Foxiproxy

Cloud Forensics refers to digital forensics investigations performed in Cloud Computing Environments. Nowadays digital investigators face various technical, legal, and organizational challenges to keep up with current developments in the field of Cloud Computing. But, due to its dynamic nature, Cloud Computing also offers several opportunities to improve digital investigations in Cloud Environments. Digital investigators may utilize Cloud Computing setups and process complex tasks in cloud infrastructures. Thus they can take advantage of the enormous computing power at hand in such environments.In this paper we focus on the current State-of-the-Art of affected fields of Cloud Forensics. The benefit for the reader of this paper is a clear overview of the challenges and opportunities for scientific developments in the field of Cloud Forensics.KeywordsCloud Forensicsdigital forensicsevidence

Copyright: © 2013 Deka GC. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. As governments around the world continue to grapple with slow-moving economies, cloud computing is emerging as a viable and valuable answer to the persistent demands for reducing public sector spending. Recent attention has shifted to a new initiative called Cloud Government (G-Cloud) incorporating cloud computing into e-Government services, particularly aimed at communicating directly with citizens and implementing cloud computing services in order to cut costs and improve upon the IT services infrastructure. G-Cloud is an Internet based communications which enable public bodies to host, select and use computing services from secure, resilient and cost-effective IT service environment. The ambition of the journey from traditional IT infrastructures towards cloud computing and IaaS is a trusted Cloud with the network as the logical platform to bring the existing assets in the Datacenter and new Cloud computing approaches with Virtualization, Governance, Security, Information and Application. The G-Cloud program’s core benefits are cost reduction, improved services, faster delivery and progressive sustainability agenda. The citizen-centric data, services and applications will be stored, maintained and delivered from G-Cloud and a comprehensive government portal will be a part and parcel of this cloud-based service delivery. Government applications store will provide a “portal” to purchase G-Cloud services. The latest trend on G-Cloud is following the agency-by-agency implementation scenario. Various Ministries/Departments may use cloud services provided by various Cloud Service Provider (CSP) based on the availability in a particular locality as well as the specific requirement of the particular Department/Ministry. It is a fact that all the CSPs are not equally competent in all types of services like accounting, ERP, CRM etc. But for the smooth function of the Government machinery these clouds must be interoperable. Current cloud frameworks are not designed to interact with each other, which make it more difficult for organizations to consolidate their applications and fully realize the savings and productivity benefits of cloud solutions. The dynamic location of service facilities, Virtualization of hardware and software elements is stressing the communication network & protocols, when datacenters are interconnected through the Internet. Although the “Computing” aspects of Cloud have been largely investigated, lower attention has been devoted to the “Networking of Clouds”.

<span lang="EN-US">Cloud Computing is the ability to improve the utility or train new human resources without investing in new infrastructure, or add capabilities to existence without the latest software licensing. It expanded the capabilities of Information Technology (IT). From the past few years, cloud computing has developed from a good business concept in the best rising sectors of the IT industry. But more information on individuals and companies was put in the cloud, and concerns began to think about how secure the cloud environment was. Despite cloud surrounding structures, enterprise users still do not want to expand their business in the cloud. Security reduces the growth of cloud computing and continues to spread the market with complexity with data privacy and data protection. The security of cloud computing has constantly been an significant aspect of improved quality of service from cloud service providers. Data storage in the cloud has a problem related to data security. However, cloud computing construct many new security challenges which have not been well examine. In order to ensure that the user's data in the cloud is secure, we have proposed an effective mechanism with a distinctive feature of data integrity and privacy. This paper focusing on problems relating to the cloud data storage techniques and security in virtual environment. We recommend a method for providing data storage and security in cloud using public key Cryptosystem, which uses the concept of the modified RSA algorithm to provide better security for the data stored in the cloud. </span>

Cloud computing is an emerging computing model that provides numerous advantages to organizations (both service providers and customers) in terms of massive scalability, lower cost, and flexibility, to name a few. Despite these technical and economical advantages of cloud computing, many potential cloud consumers are still hesitant to adopt cloud computing due to security and privacy concerns. This paper describes some of the unique cloud computing security factors and subfactors that play a critical role in addressing cloud security and privacy concerns. To mitigate these concerns, we develop a security metric tool to provide information to cloud users about the security status of a given cloud vendor. The primary objective of the proposed metric is to produce a security index that describes the security level accomplished by an evaluated cloud computing vendor. The resultant security index will give confidence to different cloud stakeholders and is likely to help them in decision making, increase the predictability of the quality of service, and allow appropriate proactive planning if needed before migrating to the cloud. To show the practicality of the proposed metric, we provide two case studies based on the available security information about two well-known cloud service providers (CSP). The results of these case studies demonstrated the effectiveness of the security index in determining the overall security level of a CSP with respect to the security preferences of cloud users.

With the increasing popularity of network technology and information concepts, Big Data (BD) and cloud computing technologies have emerged and are widely used in all industries. BD technology can fully utilize the application value of information. Cloud computing can store a large amount of data, and improve data usage efficiency, so as to make full use of the value of data. At the same time, data security issues have become increasingly important. However, due to various factors, many users are faced with data breaches and privacy violations in the BD cloud computing environment. In this case, there are some data security risks, and the key issue is to consider how to avoid these risks. By analyzing the relationship and differences between BD and cloud computing, this article studied the issues and influencing factors of Artificial Intelligence (AI) data security in the BD cloud computing environment, and proposed corresponding optimization strategies, so as to improve data security and provide users with a brand new experience. Through comparison, it could be seen that the data processing speed and legal integrity after using the optimization strategy significantly improved. Among them, data processing speed increased by 7.2% and legal integrity increased by 10.4%. BD cloud computing could effectively improve AI data security performance.

Over the past years, Machine Learning has been applied to an increasing number of problems across numerous industries. However, the steady rise in the application of Machine Learning has not come without challenges since companies often lack the expertise or infrastructure to build their own Machine Learning systems. These challenges led to the emergence of a new paradigm, called Machine Learning as a Service. Scientific literature has mainly analyzed this topic in the context of platform solutions that provide ready-to-use environments for companies. We recently have developed a platform-independent approach and labeled it Machine Learning Services. The aim of the present study is to identify and evaluate challenges and opportunities in the application of Machine Learning Services. To do so, we conducted a Delphi Study with a panel of machine learning experts. The study consisted of three rounds and was structured according to the five steps of the Data Science Lifecycle. A variety of challenges from the areas “Communication”, “Environment”, “Approach”, “Data”, “Retraining, Testing, Monitoring and Updating”, “Model Training and Evaluation” were identified. Subsequently, the challenges revealed by the Delphi Study were compared with previous work on Machine Learning as a Service, which resulted from a structured literature review. The identified areas serve as possible future research fields and give further implications for practice. Alleviating communication issues and assessing the business IT infrastructure prior to the machine learning project are among the key findings of our study.

The robustness of mission-critical database platforms has become a key issue of concern to the enterprises that rely on constant availability of transactional and analytical data to run their day-to-day operations. Not only does SAP HANA as the most popular in-memory enterprise resource planning and real-time analytics platform need to have high performance, but also fault tolerance, scalability, and predictable lifecycle management. With such a dramatic change in the business IT infrastructure, organizations are still struggling with the very thorny issues of downtime, performance loss and complex upgrade processes, which kill the continuity of the business and elevates operational risk. The losses incurred in the event of down time in both financial and reputational terms have increased the need to have frameworks that inculcate resiliency to all phases of the deployment and governance of SAP HANA. This paper formulates an evidence-based approach to designing resilient SAP HANA systems combining implementation procedures, performance optimization approaches, and lifecycle maintenance. Based solely on the vendor documentation, technical notes and best-practice reports, which were published in December 2022, the framework proposes to pull together the fragmented guidance and condense it into a roadmap of resilience. The approach puts a strong focus on pre-deployment testing and certified platform testing, wherein operating system, database and virtualization compatibility matrices are used to protect against unsupported configuration. The migration pathways, i.e. phased, near-zero-downtime pathways are analyzed against their effects on service level agreements and exposure to risk. This research has a contribution to the fact that it has consolidated resilience strategies to a prescriptive and practical model that fits with the realities of enterprise IT landscapes. It synthesizes deployment rigor, tuning precision and governance continuity and thus forms a roadmap that does not just provide greater technical resilience but also augurs business requirements of continuity, compliance and optimization of performance. The results are an addition to the academic literature on the topic of enterprise database resilience, as well as a practical guide to IT leaders, architects, and administrators who must ensure the safety of mission-critical SAP HANA infrastructures

Today, cloud computing has developed a transformative model for the organization, business, governments that brings huge potentials and turn into popular for pay as you go, on-demand service, scalability and efficient services. However, cloud computing has made the concern for forensic data because of the architecture of cloud system is not measured appropriately. Due to the distributed nature of the cloud system, many aspects relating to the forensic investigation such as data collection, data storage, crime target, data violation are difficult to achieve. Investigating the incidents in the cloud environment is a challenging task because the forensics investigator still needs to relay on the third party such as cloud service provider for performing their investigation tasks. It makes the overall forensic process difficult to complete with a duration and presented it to the court. Recently, there are some cloud forensics studies to address the challenges such as evidence collection, data acquisition, identifying the incidents and so on. However, still, there is a research gap in terms of consistency of analysing forensic evidence from distributed environment and methodology to analyse the forensic data in the cloud. This thesis contributes towards the direction of addressing the research gaps. In particular, this work proposes a forensic investigation framework CeFF: A framework for forensics enabled cloud investigation to investigate evidence in the cloud computing environment. The framework includes a set of concepts from organisational, technical and legal perspectives, which gives a holistic view of analysing cybercrime from organisation context where the crime has occurred through technical context and legal impact. The CeFF also includes a systematic process that uses the concept for performing the investigation. The cloud-enabled forensics framework meets all the forensics related requirement such as data collection, examination, presents the report, and identifies the potential risks that can consider while investigating the evidence in the cloud-computing environment. Finally, the proposed CeFF is applied to a real-life example to validate its applicability. The result shows that CeFF supports analysing the forensic data for a crime occurred in cloud-based system in a systematic way.

Cloud computing is recently everyone uses increasing tendency in distributed and parallel computing environment changes. Cloud is an Internet. It works the largest group of interconnected individual desktop computers or network servers; these are used public cloud or private cloud or hybrid. It’s an active implementation by IT industry resource and remote provisioning scalable and measured documents and decentralized its resources. It is different security issues facing cloud environmental. Cloud computing consists of different services providing. One of the Software as a Service (SaaS) has on many business orientated application. It is shared software and resources and information are available on demand device access in public it allows cost and complexity of service providers to access and operational costs anytime and anywhere uses provide cloud services. Another service is a IaaS is provides protect security customer’s knowledge, functions also secured. Other models Platform as a Service (PaaS) clouds. Security of PaaS clouds forms multitenant access control. Its privacy protected together the service provides and user security. problems., security and threats.

Cloud computing has emerged as a new computing paradigm, with provisioning model generally consisting of cloud service providers (CSPs), network service providers (NSPs), and end users. The associated economics has opened up a new research area; and with the expansion of the cloud computing market, the relationship between CSPs and NSPs, is changing profoundly. In addition to providing the default network services, traditional NSPs, in attempt to compete with CSPs, have started offering cloud services to end users. Though much progress has been made toward addressing competitions among CSPs themselves or among NSPs themselves, few studies have focused on the competition between CSPs and NSPs. In this paper, we investigate the problem of insufficient studies on the competition between CSPs and NSPs by presenting a new economic model to characterize the competition between CSPs and NSPs, and by conducting thorough theoretical analysis as well as numeric experiments to validate the proposed model. We believe, based on results, that the proposed economic model is general and feasible, and thus is applicable to modeling the competition among service providers in cloud computing market.