Cache-based Side-Channel Attacks in Multi-Tenant Public Clouds and Their Countermeasures

Cloud computing is gaining traction due to the business agility, resource scalability and operational efficiency that it enables. However, the murkiness of the security assurances offered by public clouds to their tenants is one of the major impediments to enterprise and government adoption of cloud computing. This dissertation explores one of the major design flaws in modern public clouds, namely insufficient isolation among cloud tenants as evidenced by the cloud's inability to prevent side-channel attacks between co-located tenants, in both Infrastructure-as-a-Service (IaaS) clouds and Platform-as-a-Service (PaaS) clouds. Specifically, we demonstrate that one virtual machine (VM) can successfully exfiltrate cryptographic private keys from another VM co-located on the same physical machine using a cache-based side-channel attack, which calls into question the established belief that the security isolation provided by modern virtualization technologies remains adequate under the new threat model in multi-tenant public IaaS clouds. We have also demonstrated in commercial PaaS clouds that cache-based side channels can penetrate container-based isolation by extracting sensitive information from the execution paths of the victim applications, thereby subverting their security. Finally, we devise two defensive techniques for the IaaS setting, which can be adopted by cloud tenants immediately on modern cloud platforms without extra help from cloud providers, to address side-channel threats: (1) for tenants requiring a high degree of security and physical isolation, a tool to facilitate cloud auditing of such isolation; and (2) for tenants who use multi-tenant cloud services, an operating-system-level defense to defend against cache-based side-channel threats on their own.Doctor of Philosoph

Whose news: Who is the political gatekeeper in the early 21st century.

The news media and the political public relations industry are linked in numerous ways and any change in their relationship has many repercussions, not just for those in the political news industry, but for society and democracy in the UK as a whole. Neither political PRs nor journalists can function effectively without the other and each relies upon the other to enhance their importance. They are both powerful groups but without the other their power is impaired and their ability to succeed is significantly reduced. The extent of this relationship on public life and society in the UK means that an analysis of these relationships is essential to understand just who the political gatekeeper is in the early 21st century. This thesis utilises interviews with professional practitioners in the political news industry to investigate the role of political journalists within the news media and the role of political PRs in the political public relations industry. It then establishes the extent and nature of the relationship between these two groups. The implications of this relationship are then analysed to determine whether it is possible for the news media to facilitate their role in democratic life in the UK. The thesis concludes that, as a result of all the changes in the news media and the dramatic growth in size and power of the political public relations industry, there is no longer a single political gatekeeper and that in fact political PRs and journalists conduct a collusive conflictual relationship. It presents a situation where not only are journalists hindered in carrying out the news media's democratic obligations but the news media is, as a whole, no longer able to effectively defend their obligations and journalists are failing in their role as a watchdog

Working with disaster: Transforming experience into useful practice: How I used action research to guide my path while walking it

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Personality Identification from Social Media Using Deep Learning: A Review

Social media helps in sharing of ideas and information among people scattered around the world and thus helps in creating communities, groups, and virtual networks. Identification of personality is significant in many types of applications such as in detecting the mental state or character of a person, predicting job satisfaction, professional and personal relationship success, in recommendation systems. Personality is also an important factor to determine individual variation in thoughts, feelings, and conduct systems. According to the survey of Global social media research in 2018, approximately 3.196 billion social media users are in worldwide. The numbers are estimated to grow rapidly further with the use of mobile smart devices and advancement in technology. Support vector machine (SVM), Naive Bayes (NB), Multilayer perceptron neural network, and convolutional neural network (CNN) are some of the machine learning techniques used for personality identification in the literature review. This paper presents various studies conducted in identifying the personality of social media users with the help of machine learning approaches and the recent studies that targeted to predict the personality of online social media (OSM) users are reviewed