NEMESYS: Enhanced Network Security for Seamless Service Provisioning in the Smart Mobile Ecosystem

As a consequence of the growing popularity of smart mobile devices, mobile malware is clearly on the rise, with attackers targeting valuable user information and exploiting vulnerabilities of the mobile ecosystems. With the emergence of large-scale mobile botnets, smartphones can also be used to launch attacks on mobile networks. The NEMESYS project will develop novel security technologies for seamless service provisioning in the smart mobile ecosystem, and improve mobile network security through better understanding of the threat landscape. NEMESYS will gather and analyze information about the nature of cyber-attacks targeting mobile users and the mobile network so that appropriate counter-measures can be taken. We will develop a data collection infrastructure that incorporates virtualized mobile honeypots and a honeyclient, to gather, detect and provide early warning of mobile attacks and better understand the modus operandi of cyber-criminals that target mobile devices. By correlating the extracted information with the known patterns of attacks from wireline networks, we will reveal and identify trends in the way that cyber-criminals launch attacks against mobile devices.Comment: Accepted for publication in Proceedings of the 28th International Symposium on Computer and Information Sciences (ISCIS'13); 9 pages; 1 figur

Visual analytics for non-expert users in cyber situation awareness

Situation awareness is often described as the perception and comprehension of the current situation, and the projection of future status. Whilst this may be well understood in an organisational cybersecurity context, there is a strong case to be made for effective cybersecurity situation awareness that is tailored to the needs of the Non-Expert User (NEU). Our online usage habits are rapidly evolving with smartphones and tablets being widely used to access resources online. In order for NEUs to remain safe online, there is a need to enhance awareness and understanding of cybersecurity concerns, such as how devices may be acting online, and what data is being shared between devices. In this paper, we extend our proposal of the Enhanced Personal Situation Awareness (ePSA) framework to consider the key details of cyber situation awareness that would be of concern to NEUs, and we consider how such information can be effectively conveyed using a visual analytic approach. We present the design of our visual analytics approach to show how this can represent the key details of cyber situation awareness whilst maintaining a simple and clean design scheme so as to not result in information-overload for the user. The guidance developed through the course of this work can help practitioners develop tools that could help NEUs better understand their online actions, with the aim of giving users greater control and safer experiences when their personal devices are acting online

Software Usability

This volume delivers a collection of high-quality contributions to help broaden developers’ and non-developers’ minds alike when it comes to considering software usability. It presents novel research and experiences and disseminates new ideas accessible to people who might not be software makers but who are undoubtedly software users

Using big data for customer centric marketing

This chapter deliberates on “big data” and provides a short overview of business intelligence and emerging analytics. It underlines the importance of data for customer-centricity in marketing. This contribution contends that businesses ought to engage in marketing automation tools and apply them to create relevant, targeted customer experiences. Today’s business increasingly rely on digital media and mobile technologies as on-demand, real-time marketing has become more personalised than ever. Therefore, companies and brands are striving to nurture fruitful and long lasting relationships with customers. In a nutshell, this chapter explains why companies should recognise the value of data analysis and mobile applications as tools that drive consumer insights and engagement. It suggests that a strategic approach to big data could drive consumer preferences and may also help to improve the organisational performance.peer-reviewe

An Ad-Hoc Crime Reporting Information Management System

Criminals often escape punishment due to delayed sharing of information with law enforcement agencies. The traditional method of reporting crimes is slow, thus, the need for a faster and modern approach, one that uses modern technology to apprehend perpetrators. It is therefore important to have a well-organized system for reporting criminal activities. This system should be free and easily accessible to the public. With information being delivered promptly and remotely, there is no need for visits to police stations, which can be time-consuming and tedious. This project aims to curb criminal activities by developing a smartphone application that enables victims or witnesses to report real-time information to security agencies, including GPS coordinates. The use of real-time data would prompt quick responses in emergency situations and make reactions proactive rather than reactive. The proposed methodology for the project involves designing and developing a user-friendly mobile app as well as a professional web application for security agencies. The creation of an integration platform allows for the registration of police stations and staff members. Feedback from users would help maintain and improve upon the app. Ultimately, this project aims at increasing public safety and improving crime reporting and management in Ghana by using modern technologies. By enabling citizens to report crimes in real-time, the mobile application has the potential to revolutionize crime reporting and foster a safer and secure environment. By collaborating with law enforcement agencies, the proposed solution can help provide a more efficient and proactive crime reporting system in Ghana.     &nbsp

Logico-linguistic semantic representation of documents

The knowledge behind the gigantic pool of data remains largely unextracted. Techniques such as ontology design, RDF representations, hpernym extraction, etc. have been used to represent the knowledge. However, the area of logic (FOPL) and linguistics (Semantics) has not been explored in depth for this purpose. Search engines suffer in extraction of specific answers to queries because of the absence of structured domain knowledge. The current paper deals with the design of formalism to extract and represent knowledge from the data in a consistent format. The application of logic and linguistics combined greatly eases and increases the precision of knowledge translation from natural language. The results clearly indicate the effectiveness of the knowledge extraction and representation methodology developed providing intelligence to machines for efficient analysis of data. The methodology helps machines to precise results in an efficient manner