Us and them: identifying cyber hate on Twitter across multiple protected characteristics

Hateful and antagonistic content published and propagated via the World Wide Web has the potential to cause harm and suffering on an individual basis, and lead to social tension and disorder beyond cyber space. Despite new legislation aimed at prosecuting those who misuse new forms of communication to post threatening, harassing, or grossly offensive language - or cyber hate - and the fact large social media companies have committed to protecting their users from harm, it goes largely unpunished due to difficulties in policing online public spaces. To support the automatic detection of cyber hate online, specifically on Twitter, we build multiple individual models to classify cyber hate for a range of protected characteristics including race, disability and sexual orientation. We use text parsing to extract typed dependencies, which represent syntactic and grammatical relationships between words, and are shown to capture ‘othering’ language - consistently improving machine classification for different types of cyber hate beyond the use of a Bag of Words and known hateful terms. Furthermore, we build a data-driven blended model of cyber hate to improve classification where more than one protected characteristic may be attacked ( e.g. race and sexual orientation), contributing to the nascent study of intersectionality in hate crime

Sensing real-world events using Arabic Twitter posts

In recent years, there has been increased interest in event detection using data posted to social media sites. Automatically transforming user-generated content into information relating to events is a challenging task due to the short informal language used within the content and the variety oftopics discussed on social media. Recent advances in detecting real-world events in English and other languages havebeen published. However, the detection of events in the Arabic language has been limited to date. To address this task, wepresent an end-to-end event detection framework which comprises six main components: data collection, pre-processing, classification, feature selection, topic clustering and summarization. Large-scale experiments over millions of Arabic Twitter messages show the effectiveness of our approach for detecting real-world event content from Twitter posts

Automatic summarization of real world events using Twitter

Microblogging sites, such as Twitter, have become increasingly popular in recent years for reporting details of real world events via the Web. Smartphone apps enable people to communicate with a global audience to express their opinion and commentate on ongoing situations - often while geographically proximal to the event. Due to the heterogeneity and scale of the data and the fact that some messages are more salient than others for the purposes of understanding any risk to human safety and managing any disruption caused by events, automatic summarization of event-related microblogs is a non-trivial and important problem. In this paper we tackle the task of automatic summarization of Twitter posts, and present three methods that produce summaries by selecting the most representative posts from real-world tweet-event clusters. To evaluate our approaches, we compare them to the state-of-the-art summarization systems and human generated summaries. Our results show that our proposed methods outperform all the other summarization systems for English and non-English corpora

Advanced access control in support and distributed collaborative working and de-perimeterization

This thesis addresses the problem of achieving fine-grained and sustained control of access to electronic information, shared in distributed collaborative environments. It presents an enhanced approach to distributed information security architecture, driven by the risks, guidelines and legislation emerging due to the growth of collaborative working, and the often associated increase in storage of information outside of a secured information system perimeter. Traditional approaches to access control are based on applying controls at or within the network perimeter of an information system. One issue with this approach when applying it to shared information is that, outside of the perimeterized zone, the owner loses control of their information. This loss of control could dissuade collaborating parties from sharing their information resources. Information resources can be thought of as a collection of related content stored in a container. Another issue with current approaches to access control, particularly to unstructured resources such as text documents, is the coarse granularity of control they provide. That is, controls can only apply to a resource in its entirety. In reality, the content within a resource could have varying levels of security requirements with different levels of control. For example, some of the content may be completely free from any access restriction, while other parts may be too sensitive to share outside of an internal organisation. The consequence being that the entire resource is restricted with the controls relevant to the highest level content. Subsequently, a substantial amount of information that could feasibly be shared in collaborative environments is prevented from being shared, due to being part of a highly restricted resource. The primary focus of this thesis is to address these two issues by investigating the appropriateness and capability of perimeter security, and entire-resource protection, to provide access control for information shared in collaborative distributed environments. To overcome these problems, the thesis develops an access control framework, based on which, several formulae are defined to clarify the problems, and to allow them to be contextualised. The formulae have then been developed and improved, with the problem in mind, to create a potential solution, which has been implemented and tested to demonstrate that it is possible to enhance access control technology to implement the capability to drill down into the content of an information resource and apply more fine-grained controls, based on the security requirements of the content within. Furthermore, it is established that it is possible to shift part of the controls that protect information resources within a secure network perimeter, to the body of the resources themselves so that they become, to some extent, self protecting. This enables the same controls to be enforced outside of the secure perimeter. The implementation is based on the structuring of information and embedding of metadata within the body of an information resource. The metadata effectively wraps sections of content within a resource into containers that define fine-grained levels of access control requirement, to protect its confidentiality and integrity. Examples of the granularity afforded by this approach could be page, paragraph, line or even word level in a text document. Once metadata has been embedded, it is bound to a centrally controlled access control policy for the lifetime of the resource. Information can then be shared, copied, distributed and accessed in support of collaborative working, but a link between the metadata and the centrally controlled policy is sustained, meaning that previously assigned access privileges to different sections of content can be modified or revoked at any time in the future. The result of this research is to allow information sharing to reach a greater level of acceptance and usage due to: i. the enhanced level of access control made possible through finer-grained controls, allowing the content of a single resource to be classified and restricted at different levels, and ii. the ability to retain sustained control over information through modifiable controls, that can be enforced both while the information is stored on local information systems, and after the information has been shared outside the local environment

Methodology for Designing Decision Support Systems for Visualising and Mitigating Supply Chain Cyber Risk from IoT Technologies

This paper proposes a methodology for designing decision support systems for visualising and mitigating the Internet of Things cyber risks. Digital technologies present new cyber risk in the supply chain which are often not visible to companies participating in the supply chains. This study investigates how the Internet of Things cyber risks can be visualised and mitigated in the process of designing business and supply chain strategies. The emerging DSS methodology present new findings on how digital technologies affect business and supply chain systems. Through epistemological analysis, the article derives with a decision support system for visualising supply chain cyber risk from Internet of Things digital technologies. Such methods do not exist at present and this represents the first attempt to devise a decision support system that would enable practitioners to develop a step by step process for visualising, assessing and mitigating the emerging cyber risk from IoT technologies on shared infrastructure in legacy supply chain systems

Self protecting data for de-perimeterised information sharing

The emergence of high-speed networks, Grid Computing, Service-Oriented Architectures, and an ever increasing ambient connection to mobile Internet has enabled an underpinning infrastructure for the development of dynamically formed, collaborative working groups known as Virtual Organisations (VOs). VOs provide strong motivation for investigation into the infrastructure, and in particular the security necessary to protect the information and resources shared within a VO, both while resident on local machines and when allowed to move beyond the secure boundary of a local organisational network perimeter and into the realm of the distributed VO. Traditional access control systems are perimeter- centric, meaning they apply the controls to both internal and external requests for access to information within or at the perimeter of their information system. • This paper presents the initial results of the JISC funded SPIDER project, being led by Cardiff University. Through case based example, the research investigates the limitations to granularity and persistent control over information when using the perimeter- centric approach in a collaborative working environment

Automation of the supplier role in the GB power system using blockchain based smart contracts

An electricity supply smart contract was developed and demonstrated to perform pre-time-of-use price negotiation between demand and generation and posttime- of-use settlement and payment. The smart contract was demonstrated with 1000 loads/generators with usages simulated using lognormal probability distributions. It combines payment of deposit, negotiation of price based on estimates, settlement based on actual usage and enactment of payments using crypto-currency. The settlement procedure rewards customers that adjusted to balance the system. The smart contract was written in the Solidity programming language and implemented with a simulated Ethereum blockchain using testrpc and go-ethereum. In the example test case, a price was agreed, settled and payment enacted