Data Auditing and Security in Cloud Computing: Issues, Challenges and Future Directions

Cloud computing is one of the significant development that utilizes progressive computational power and upgrades data distribution and data storing facilities. With cloud information services, it is essential for information to be saved in the cloud and also distributed across numerous customers. Cloud information repository is involved with issues of information integrity, data security and information access by unapproved users. Hence, an autonomous reviewing and auditing facility is necessary to guarantee that the information is effectively accommodated and used in the cloud. In this paper, a comprehensive survey on the state-of-art techniques in data auditing and security are discussed. Challenging problems in information repository auditing and security are presented. Finally, directions for future research in data auditing and security have been discussed

Data auditing and security in cloud computing: issues, challenges and future directions

Cloud computing is one of the significant development that utilizes progressive computational power and upgrades data distribution and data storing facilities. With cloud information services, it is essential for information to be saved in the cloud and also distributed across numerous customers. Cloud information repository is involved with issues of information integrity, data security and information access by unapproved users. Hence, an autonomous reviewing and auditing facility is necessary to guarantee that the information is effectively accommodated and used in the cloud. In this paper, a comprehensive survey on the state-of-art techniques in data auditing and security are discussed. Challenging problems in information repository auditing and security are presented. Finally, directions for future research in data auditing and security have been discusse

Efficient Ciphertext-policy Attribute Based Encryption for Cloud-Based Access Control

Outsourcing data to some cloud servers enables a massive, flexible usage of cloud computing resources and it is typically held by different organizations and data owners. However, various security concerns have been raised due to hosting sensitive data on an untrusted cloud environment, and the control over such data by their owners is lost after uploading to the cloud. Access control is the first defensive line that forbids unauthorized access to the stored data. Moreover, fine-grained access control on the untrusted cloud can be enforced using advanced cryptographic mechanisms. Some schemes have been proposed to deliver such access control using Ciphertext-policy attribute based encryption (CP-ABE) that can enforce data owners’ access policies to achieve such cryptographic access control and tackle the majority of those concerns. However, some challenges are still outstanding due to the complexity of frequently changing the cryptographic enforcements of the owners’ access policies in the hosted cloud data files, which poses computational and communicational overheads to data owners. These challenges are: 1) making dynamic decisions to grant access rights to the cloud resources, 2) solving the issue of the revocation process that is considered as a performance killer, and 3) building a collusion resistant system. The aim of our work is to construct an access control scheme that provides secure storing and sharing sensitive data on the cloud and suits limited-resources devices. In this thesis, we analyse some of the existing, related issues and propose a scheme that extends the relevant existing techniques to resolve the inherent problems in CP-ABE without incurring heavy computation overhead. In particular, most existing revocation techniques require re-issuing many private keys for all non-revoked users as well as re-encrypting the related ciphertexts. Our proposed scheme offers a solution to perform a novel technique that dynamically changes the access privileges of legitimate users. The scheme drives the access privileges in a specific way by updating the access policy and activating a user revocation property. Our technique assigns processing-intensive tasks to cloud servers without any information leakage to reduce the computation cost on resource-limited computing devices. Our analytical theoretical and experimental findings and comparisons of our work with related existing systems indicate that our scheme is efficient, secure and more practical compared to the current related systems, particularly in terms of policy updating and ciphertext re-encryption. Therefore, our proposed scheme is suited to Internet of Things (IoT) applications that need a practical, secure access control scheme. Moreover, to achieve secure, public cloud storage and minimise the limitations of CP-ABE which mainly supports storing data only on a private cloud storage system managed by only one single authority, our proposed access control scheme is extended to a secure, critical access control scheme with multiple authorities. This scheme ought to be carefully designed to achieve fine-grained access control and support outsourced-data confidentiality. In addition, most existing multi-authority access control schemes do not properly consider the revocation issue due to the difficulty of addressing it in distributed settings. Therefore, building a multi-authority CP-ABE scheme along with addressing changes to policy attributes and users, have motivated many researchers to develop more suitable schemes with limited success. By leveraging the existing work, in this thesis, we propose a second CP-ABE scheme that tackles most of the existing work’s limitations and allows storing data securely on a public cloud storage system by employing multiple authorities which manage a joint set of attributes. Furthermore, the proposed scheme efficiently maintains the revocation by adapting the two techniques used in the first proposed single authority access control scheme to allow dynamic policy update and invalidate a revoked user’s secret key that eliminates collusion attacks. In terms of computation overhead, the proposed multi-authority scheme outsources expensive operations of encryption and decryption to a cloud server to mitigate the burden on a data owner and data users, respectively. Our scheme analysis and the theoretical and implemented results demonstrate that our scheme is scalable and efficient

Securing clouds using cryptography and traffic classification

Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction. Over the last decade, cloud computing has gained popularity and wide acceptance, especially within the health sector where it offers several advantages such as low costs, flexible processes, and access from anywhere. Although cloud computing is widely used in the health sector, numerous issues remain unresolved. Several studies have attempted to review the state of the art in eHealth cloud privacy and security however, some of these studies are outdated or do not cover certain vital features of cloud security and privacy such as access control, revocation and data recovery plans. This study targets some of these problems and proposes protocols, algorithms and approaches to enhance the security and privacy of cloud computing with particular reference to eHealth clouds. Chapter 2 presents an overview and evaluation of the state of the art in eHealth security and privacy. Chapter 3 introduces different research methods and describes the research design methodology and processes used to carry out the research objectives. Of particular importance are authenticated key exchange and block cipher modes. In Chapter 4, a three-party password-based authenticated key exchange (TPAKE) protocol is presented and its security analysed. The proposed TPAKE protocol shares no plaintext data; all data shared between the parties are either hashed or encrypted. Using the random oracle model (ROM), the security of the proposed TPAKE protocol is formally proven based on the computational Diffie-Hellman (CDH) assumption. Furthermore, the analysis included in this chapter shows that the proposed protocol can ensure perfect forward secrecy and resist many kinds of common attacks such as man-in-the-middle attacks, online and offline dictionary attacks, replay attacks and known key attacks. Chapter 5 proposes a parallel block cipher (PBC) mode in which blocks of cipher are processed in parallel. The results of speed performance tests for this PBC mode in various settings are presented and compared with the standard CBC mode. Compared to the CBC mode, the PBC mode is shown to give execution time savings of 60%. Furthermore, in addition to encryption based on AES 128, the hash value of the data file can be utilised to provide an integrity check. As a result, the PBC mode has a better speed performance while retaining the confidentiality and security provided by the CBC mode. Chapter 6 applies TPAKE and PBC to eHealth clouds. Related work on security, privacy preservation and disaster recovery are reviewed. Next, two approaches focusing on security preservation and privacy preservation, and a disaster recovery plan are proposed. The security preservation approach is a robust means of ensuring the security and integrity of electronic health records and is based on the PBC mode, while the privacy preservation approach is an efficient authentication method which protects the privacy of personal health records and is based on the TPAKE protocol. A discussion about how these integrated approaches and the disaster recovery plan can ensure the reliability and security of cloud projects follows. Distributed denial of service (DDoS) attacks are the second most common cybercrime attacks after information theft. The timely detection and prevention of such attacks in cloud projects are therefore vital, especially for eHealth clouds. Chapter 7 presents a new classification system for detecting and preventing DDoS TCP flood attacks (CS_DDoS) for public clouds, particularly in an eHealth cloud environment. The proposed CS_DDoS system offers a solution for securing stored records by classifying incoming packets and making a decision based on these classification results. During the detection phase, CS_DDOS identifies and determines whether a packet is normal or from an attacker. During the prevention phase, packets classified as malicious are denied access to the cloud service, and the source IP is blacklisted. The performance of the CS_DDoS system is compared using four different classifiers: a least-squares support vector machine (LS-SVM), naïve Bayes, K-nearest-neighbour, and multilayer perceptron. The results show that CS_DDoS yields the best performance when the LS-SVM classifier is used. This combination can detect DDoS TCP flood attacks with an accuracy of approximately 97% and a Kappa coefficient of 0.89 when under attack from a single source, and 94% accuracy and a Kappa coefficient of 0.9 when under attack from multiple attackers. These results are then discussed in terms of the accuracy and time complexity, and are validated using a k-fold cross-validation model. Finally, a method to mitigate DoS attacks in the cloud and reduce excessive energy consumption through managing and limiting certain flows of packets is proposed. Instead of a system shutdown, the proposed method ensures the availability of service. The proposed method manages the incoming packets more effectively by dropping packets from the most frequent requesting sources. This method can process 98.4% of the accepted packets during an attack. Practicality and effectiveness are essential requirements of methods for preserving the privacy and security of data in clouds. The proposed methods successfully secure cloud projects and ensure the availability of services in an efficient way

Security Strategies of Electronic Health Record Systems

Users of electronic health record (EHR) systems lack data security mechanisms and are at risk of patient data breaches. Grounded in routine activities theory, the purpose of this qualitative case study was to explore strategies information technology security managers in the health care industry use to minimize electronic health record data breaches. The participants were nine information security managers of large, medium, and small health care organizations in the Midwest United States. Data collection included semistructured interviews and organizational documents. Through methodological triangulation, three themes emerged: (a) requirements based on government and organizational regulations, (b) implementation of best practice industry-standard security measures, and (c) emerging interoperability with a security and privacy program. A key recommendation is for information security managers to understand the motivations and triggers of positive behavior change that minimizes organizations\u27 external and internal data breaches. The implications for positive social change include the potential to enhance the security presence and reputation of the health care organizations

Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation: Special Report of the Intergovernmental Panel on Climate Change

This Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) has been jointly coordinated by Working Groups I (WGI) and II (WGII) of the Intergovernmental Panel on Climate Change (IPCC). The report focuses on the relationship between climate change and extreme weather and climate events, the impacts of such events, and the strategies to manage the associated risks. The IPCC was jointly established in 1988 by the World Meteorological Organization (WMO) and the United Nations Environment Programme (UNEP), in particular to assess in a comprehensive, objective, and transparent manner all the relevant scientific, technical, and socioeconomic information to contribute in understanding the scientific basis of risk of human-induced climate change, the potential impacts, and the adaptation and mitigation options. Beginning in 1990, the IPCC has produced a series of Assessment Reports, Special Reports, Technical Papers, methodologies, and other key documents which have since become the standard references for policymakers and scientists.This Special Report, in particular, contributes to frame the challenge of dealing with extreme weather and climate events as an issue in decisionmaking under uncertainty, analyzing response in the context of risk management. The report consists of nine chapters, covering risk management; observed and projected changes in extreme weather and climate events; exposure and vulnerability to as well as losses resulting from such events; adaptation options from the local to the international scale; the role of sustainable development in modulating risks; and insights from specific case studies

Investigation of mobile devices usage and mobile augmented reality applications among older people

Mobile devices such as tablets and smartphones have allow users to communicate, entertainment, access information and perform productivity. However, older people are having issues to utilise mobile devices that may affect their quality of life and wellbeing. There are some potentials of mobile Augmented Reality (AR) applications to increase older users mobile usage by enhancing their experience and learning. The study aims to investigate mobile devices potential barriers and influence factors in using mobile devices. It also seeks to understand older people issues in using AR applications