Cloud computing adoption framework:A security framework for business clouds

This paper presents a Cloud Computing Adoption Framework (CCAF) security suitable for business clouds. CCAF multi-layered security is based on the development and integration of three major security technologies: firewall, identity management and encryption based on the development of Enterprise File Sync and Share technologies. This paper presents our motivation, related work and our views on security framework. Core technologies have been explained in details and experiments were designed to demonstrate the robustness of the CCAF multi-layered security. In penetration testing, CCAF multi-layered security could detect and block 99.95% viruses and trojans and could maintain 85% and above of blocking for 100 hours of continuous attacks. Detection and blocking took less than 0.012 second per trojan and viruses. A full CCAF multi-layered security protection could block all SQL injection providing real protection to data. CCAF multi-layered security had 100% rate of not reporting false alarm. All F-measures for CCAF test results were 99.75% and above. How CCAF multi-layered security can blend with policy, real services and blend with business activities have been illustrated. Research contributions have been justified and CCAF multi-layered security can offer added value for volume, velocity and veracity for Big Data services operated in the Cloud

Toward Effective Access Control Using Attributes and Pseudoroles

Sharing of information is fundamental to modern computing environments across many application domains. Such information sharing, however, raises security and privacy concerns that require effective access control to prevent unauthorized access and ensure compliance with various laws and regulations. Current approaches such as Role-Based Access Control (RBAC), and Attribute-Based Access Control (ABAC) and their variants are inadequate. Although it provides simple administration of access control and user revocation and permission review, RBAC demands complex initial role engineering and makes access control static. ABAC, on the other hand, simplifies initial security setup and enables flexible access control, but increases the complexity of managing privileges, user revocation and user permissions review. These limitations of RBAC and ABAC have thus motivated research into the development of newer models that use attributes and policies while preserving RBAC\u27s advantages. This dissertation explores the role of attributes---characteristics of entities in the system---in achieving effective access control. The first contribution of this dissertation is the design and development of a secure access system using Ciphertext-Policy Attribute-Based Encryption (CP-ABE). The second contribution is the design and validation of a two-step access control approach, the BiLayer Access Control (BLAC) model. The first layer in BLAC checks whether subjects making access requests have the right BLAC pseudoroles---a pseudorole is a predefined subset of a subject\u27s static attributes. If requesting subjects hold the right pseudoroles, the second layer checks rule(s) within associated BLAC policies for further constraints on access. BLAC thus makes use of attributes effectively while preserving RBAC\u27s advantages. The dissertation\u27s third contribution is the design and definition of an evaluation framework for time complexity analysis, and uses this framework to compare BLAC model with RBAC and ABAC. The fourth contribution is the design and construction of a generic access control threat model, and applying it to assess the effectiveness of BLAC, RBAC and ABAC in mitigating insider threats

A patient agent controlled customized blockchain based framework for internet of things

Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.Doctor of Philosoph

Aggregating privatized medical data for secure querying applications

 This thesis analyses and examines the challenges of aggregation of sensitive data and data querying on aggregated data at cloud server. This thesis also delineates applications of aggregation of sensitive medical data in several application scenarios, and tests privatization techniques to assist in improving the strength of privacy and utility

Confidential Data-Outsourcing and Self-Optimizing P2P-Networks: Coping with the Challenges of Multi-Party Systems

This work addresses the inherent lack of control and trust in Multi-Party Systems at the examples of the Database-as-a-Service (DaaS) scenario and public Distributed Hash Tables (DHTs). In the DaaS field, it is shown how confidential information in a database can be protected while still allowing the external storage provider to process incoming queries. For public DHTs, it is shown how these highly dynamic systems can be managed by facilitating monitoring, simulation, and self-adaptation

Intel SGX Explained

Intel\u27s Software Guard Extensions (SGX) is a set of extensions to the Intel architecture that aims to provide integrity and privacy guarantees to security-sensitive computation performed on a computer where all the privileged software (kernel, hypervisor, etc) is potentially malicious. This paper analyzes Intel SGX, based on the 3 papers that introduced it, on the Intel Software Developer\u27s Manual (which supersedes the SGX manuals), on an ISCA 2015 tutorial, and on two patents. We use the papers, reference manuals, and tutorial as primary data sources, and only draw on the patents to fill in missing information. This paper\u27s contributions are a summary of the Intel-specific architectural and micro-architectural details needed to understand SGX, a detailed and structured presentation of the publicly available information on SGX, a series of intelligent guesses about some important but undocumented aspects of SGX, and an analysis of SGX\u27s security properties

Introductory Computer Forensics

INTERPOL (International Police) built cybercrime programs to keep up with emerging cyber threats, and aims to coordinate and assist international operations for ?ghting crimes involving computers. Although signi?cant international efforts are being made in dealing with cybercrime and cyber-terrorism, ?nding effective, cooperative, and collaborative ways to deal with complicated cases that span multiple jurisdictions has proven dif?cult in practic