Secure data sharing and processing in heterogeneous clouds

The extensive cloud adoption among the European Public Sector Players empowered them to own and operate a range of cloud infrastructures. These deployments vary both in the size and capabilities, as well as in the range of employed technologies and processes. The public sector, however, lacks the necessary technology to enable effective, interoperable and secure integration of a multitude of its computing clouds and services. In this work we focus on the federation of private clouds and the approaches that enable secure data sharing and processing among the collaborating infrastructures and services of public entities. We investigate the aspects of access control, data and security policy languages, as well as cryptographic approaches that enable fine-grained security and data processing in semi-trusted environments. We identify the main challenges and frame the future work that serve as an enabler of interoperability among heterogeneous infrastructures and services. Our goal is to enable both security and legal conformance as well as to facilitate transparency, privacy and effectivity of private cloud federations for the public sector needs. © 2015 The Authors

A hybrid model for managing personal health records in South Africa

Doctors can experience difficulty in accessing medical information of new patients. One reason for this is that the management of medical records is mostly institution-centred. The lack of access to medical information may negatively affect patients in several ways. These include new medical tests that may need to be carried out at a cost to the patient and doctors prescribing drugs to which the patient is allergic. This research investigates how patients can play an active role in sharing their personal health records (PHRs) with doctors located in geographically separate areas. In order to achieve the goal of this research, existing literature concerning medical health records and standards was reviewed. A literature review of techniques that can be used to ensure privacy of health information was also undertaken. Interview studies were carried out with three medical practices in Port Elizabeth with the aim of contextualising the findings from the literature study. The Design Science Research methodology was used for this research. A Hybrid Model for Managing Personal Health Records in South Africa is proposed. This model allows patients to view their PHRs on their mobile phones and medical practitioners to manage the patients’ PHRs using a web-based application. The patients’ PHR information is stored both on a cloud server and on mobile devices hence the hybrid nature. Two prototypes were developed as a proof of concept; a mobile application for the patients and a web-based application for the medical practitioners. A field study was carried out with the NMMU health services department and 12 participants over a period of two weeks. The results of the field study were highly positive. The successful evaluation of the prototypes provides empirical evidence that the proposed model brings us closer to the realisation of ubiquitous access to PHRS in South Africa

Data Sharing and Access Using Aggregate Key Concept

Cloud Storage is a capacity of information online in the cloud, which is available from different and associated assets. Distributed storage can provide high availability and consistent quality, reliable assurance, debacle free restoration, and reduced expense. Distributed storage has imperative usefulness, i.e., safely, proficiently, adaptably offering information to others. Data privacy is essential in the cloud to ensure that the user’s identity is not leaked to unauthorized persons. Using the cloud, anyone can share and store the data, as much as they want. To share the data in a secure way, cryptography is very useful. By using different encryption techniques, a user can store data in the cloud. Encryption and decryption keys are created for unique data that the user provides. Only a particular set of decryption keys are shared so that the data can be decrypted. A public–key encryption system which is called a Key-Aggregate cryptosystem (KAC) is presented. This system produces constant size ciphertexts. Any arrangement of secret keys can be aggregated and make them into a single key, which has the same power of the keys that are being used. This total key can then be sent to the others for decoding of a ciphertext set and remaining encoded documents outside the set stays private. The project presented in this paper is an implementation of the proposed system

Privacy-aware Security Applications in the Era of Internet of Things

In this dissertation, we introduce several novel privacy-aware security applications. We split these contributions into three main categories: First, to strengthen the current authentication mechanisms, we designed two novel privacy-aware alternative complementary authentication mechanisms, Continuous Authentication (CA) and Multi-factor Authentication (MFA). Our first system is Wearable-assisted Continuous Authentication (WACA), where we used the sensor data collected from a wrist-worn device to authenticate users continuously. Then, we improved WACA by integrating a noise-tolerant template matching technique called NTT-Sec to make it privacy-aware as the collected data can be sensitive. We also designed a novel, lightweight, Privacy-aware Continuous Authentication (PACA) protocol. PACA is easily applicable to other biometric authentication mechanisms when feature vectors are represented as fixed-length real-valued vectors. In addition to CA, we also introduced a privacy-aware multi-factor authentication method, called PINTA. In PINTA, we used fuzzy hashing and homomorphic encryption mechanisms to protect the users\u27 sensitive profiles while providing privacy-preserving authentication. For the second privacy-aware contribution, we designed a multi-stage privacy attack to smart home users using the wireless network traffic generated during the communication of the devices. The attack works even on the encrypted data as it is only using the metadata of the network traffic. Moreover, we also designed a novel solution based on the generation of spoofed traffic. Finally, we introduced two privacy-aware secure data exchange mechanisms, which allow sharing the data between multiple parties (e.g., companies, hospitals) while preserving the privacy of the individual in the dataset. These mechanisms were realized with the combination of Secure Multiparty Computation (SMC) and Differential Privacy (DP) techniques. In addition, we designed a policy language, called Curie Policy Language (CPL), to handle the conflicting relationships among parties. The novel methods, attacks, and countermeasures in this dissertation were verified with theoretical analysis and extensive experiments with real devices and users. We believe that the research in this dissertation has far-reaching implications on privacy-aware alternative complementary authentication methods, smart home user privacy research, as well as the privacy-aware and secure data exchange methods

A Survey on Homomorphic Encryption Schemes: Theory and Implementation

Legacy encryption systems depend on sharing a key (public or private) among the peers involved in exchanging an encrypted message. However, this approach poses privacy concerns. Especially with popular cloud services, the control over the privacy of the sensitive data is lost. Even when the keys are not shared, the encrypted material is shared with a third party that does not necessarily need to access the content. Moreover, untrusted servers, providers, and cloud operators can keep identifying elements of users long after users end the relationship with the services. Indeed, Homomorphic Encryption (HE), a special kind of encryption scheme, can address these concerns as it allows any third party to operate on the encrypted data without decrypting it in advance. Although this extremely useful feature of the HE scheme has been known for over 30 years, the first plausible and achievable Fully Homomorphic Encryption (FHE) scheme, which allows any computable function to perform on the encrypted data, was introduced by Craig Gentry in 2009. Even though this was a major achievement, different implementations so far demonstrated that FHE still needs to be improved significantly to be practical on every platform. First, we present the basics of HE and the details of the well-known Partially Homomorphic Encryption (PHE) and Somewhat Homomorphic Encryption (SWHE), which are important pillars of achieving FHE. Then, the main FHE families, which have become the base for the other follow-up FHE schemes are presented. Furthermore, the implementations and recent improvements in Gentry-type FHE schemes are also surveyed. Finally, further research directions are discussed. This survey is intended to give a clear knowledge and foundation to researchers and practitioners interested in knowing, applying, as well as extending the state of the art HE, PHE, SWHE, and FHE systems.Comment: - Updated. (October 6, 2017) - This paper is an early draft of the survey that is being submitted to ACM CSUR and has been uploaded to arXiv for feedback from stakeholder

A Practical Framework for Storing and Searching Encrypted Data on Cloud Storage

Security has become a significant concern with the increased popularity of cloud storage services. It comes with the vulnerability of being accessed by third parties. Security is one of the major hurdles in the cloud server for the user when the user data that reside in local storage is outsourced to the cloud. It has given rise to security concerns involved in data confidentiality even after the deletion of data from cloud storage. Though, it raises a serious problem when the encrypted data needs to be shared with more people than the data owner initially designated. However, searching on encrypted data is a fundamental issue in cloud storage. The method of searching over encrypted data represents a significant challenge in the cloud. Searchable encryption allows a cloud server to conduct a search over encrypted data on behalf of the data users without learning the underlying plaintexts. While many academic SE schemes show provable security, they usually expose some query information, making them less practical, weak in usability, and challenging to deploy. Also, sharing encrypted data with other authorized users must provide each document's secret key. However, this way has many limitations due to the difficulty of key management and distribution. We have designed the system using the existing cryptographic approaches, ensuring the search on encrypted data over the cloud. The primary focus of our proposed model is to ensure user privacy and security through a less computationally intensive, user-friendly system with a trusted third party entity. To demonstrate our proposed model, we have implemented a web application called CryptoSearch as an overlay system on top of a well-known cloud storage domain. It exhibits secure search on encrypted data with no compromise to the user-friendliness and the scheme's functional performance in real-world applications.Comment: 146 Pages, Master's Thesis, 6 Chapters, 96 Figures, 11 Table

Secure Data Sharing and Collaboration in the Cloud

Cloud technology can be leveraged to enable data-sharing capabilities, which can benefit the user through greater productivity and efficiency. However, the Cloud is susceptible to many privacy and security vulnerabilities, which hinders the progress and widescale adoption of data sharing for the purposes of collaboration. Thus, there is a strong demand for data owners to not only ensure that their data is kept private and secure in the Cloud, but to also have a degree of control over their own data contents once they are shared with data consumers. Specifically, the main issues for data sharing in the Cloud include key management, security attacks, and data-owner access control. In terms of key management, it is vital that data must first be encrypted before storage in the Cloud, to prevent privacy and security breaches. However, the management of encryption keys is a great challenge. The sharing of keys with data consumers has proven to be ineffective, especially when considering data-consumer revocation. Security attacks may also prevent the widescale usage of the Cloud for data-sharing purposes. Common security attacks include insider attacks, collusion attacks, and man-in-the-middle attacks. In terms of access control, authorised data consumers could do anything they wish with an owner's data, including sending it to their peers and colleagues without the data owner's knowledge. Throughout this thesis, we investigate ways in which to address these issues. We first propose a key partitioning technique that aims to address the key management problem. We deploy this technique in a number of scenarios, such as remote healthcare management. We also develop secure data-sharing protocols that aim to mitigate and prevent security attacks on the Cloud. Finally, we focus on giving the data owner greater control, by developing a self-controlled software object called SafeProtect

Git as an Encrypted Distributed Version Control System

This thesis develops and presents a secure Git implementation, Git Virtual Vault (GV2), for users of Git to work on sensitive projects with repositories located in unsecure distributed environments, such as in cloud computing. This scenario is common within the Department of Defense, as much work is of a sensitive nature. In order to provide security to Git, additional functionality is added for confidentiality and integrity protection. This thesis examines existing Git encryption implementations and baselines their performance compared to unencrypted Git. Real-world Git repositories are examined to characterize typical Git usage and determine if the existing Git encryption implementations are capable of efficient performance with regards to typical Git usage. This research shows that the existing Git encryption implementations do not provide efficient performance. This research develops an improved secure Git implementation, GV2, with transparent authenticated encryption. The fundamental contribution of this research is developing GV2 to perform Git garbage collection on plaintext data before encrypting the data. The result is a secure Git implementation that is transparent to the user with only a minor performance penalty, compared to unencrypted Git