Security and Privacy for Modern Wireless Communication Systems

The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks

Distributed Learning for Multiple Source Data

Distributed learning is the problem of inferring a function when data to be analyzed is distributed across a network of agents. Separate domains of application may largely impose different constraints on the solution, including low computational power at every location, limited underlying connectivity (e.g. no broadcasting capability) or transferability constraints related to the enormous bandwidth requirement. Thus, it is no longer possible to send data in a central node where traditionally learning algorithms are used, while new techniques able to model and exploit locally the information on big data are necessary. Motivated by these observations, this thesis proposes new techniques able to efficiently overcome a fully centralized implementation, without requiring the presence of a coordinating node, while using only in-network communication. The focus is given on both supervised and unsupervised distributed learning procedures that, so far, have been addressed only in very specific settings only. For instance, some of them are not actually distributed because they just split the calculation between different subsystems, others call for the presence of a fusion center collecting at each iteration data from all the agents; some others are implementable only on specific network topologies such as fully connected graphs. In the first part of this thesis, these limits have been overcome by using spectral clustering, ensemble clustering or density-based approaches for realizing a pure distributed architecture where there is no hierarchy and all agents are peer. Each agent learns only from its own dataset, while the information about the others is unknown and obtained in a decentralized way through a process of communication and collaboration among the agents. Experimental results, and theoretical properties of convergence, prove the effectiveness of these proposals. In the successive part of the thesis, the proposed contributions have been tested in several real-word distributed applications. Telemedicine and e-health applications are found to be one of the most prolific area to this end. Moreover, also the mapping of learning algorithms onto low-power hardware resources is found as an interesting area of applications in the distributed wireless networks context. Finally, a study on the generation and control of renewable energy sources is also analyzed. Overall, the algorithms presented throughout the thesis cover a wide range of possible practical applications, and trace the path to many future extensions, either as scientific research or technological transfer results

Information Systems for Supporting Fire Emergency Response

Despite recent work on information systems, many first responders in emergency situations are unable to develop sufficient understanding of the situation to enable them to make good decisions. The record of the UK Fire and Rescue Service (FRS) has been particularly poor in terms of providing the information systems support to the fire fighters decision-making during their work. There is very little work on identifying the specific information needs of different types of fire fighters. Consequently, this study has two main aims. The first is to identify the information requirements of several specific members of the FRS hierarchy that lead to better Situation Awareness. The second is to identify how such information should be presented. This study was based on extensive data collected in the FRS brigades of three counties and focused on large buildings having a high-risk of fire and four key fire fighter job roles: Incident Commander, Sector Commander, Breathing Apparatus Entry Control Officer and Breathing Apparatus Wearers. The requirements elicitation process was guided by a Cognitive Task Analysis (CTA) tool: Goal Directed Information Analysis (GDIA), which was developed specifically for this study. Initially appropriate scenarios were developed. Based on the scenarios, 44 semi-structured interviews were carried out in three different elicitation phases with both novice and experienced fire fighters. Together with field observations of fire simulation and training exercises, fire and rescue related documentation; a comprehensive set of information needs of fire fighters was identified. These were validated through two different stages via 34 brainstorming sessions with the participation of a number of subject-matter experts. To explore appropriate presentation methods of information, software mock-up was developed. This mock-up is made up of several human computer interfaces, which were evaluated via 19 walkthrough and workshop sessions, involving 22 potential end-users and 14 other related experts. As a result, many of the methods used in the mock-up were confirmed as useful and appropriate and several refinements proposed. The outcomes of this study include: 1) A set of GDI Diagrams showing goal related information needs for each of the job roles with the link to their decision-making needs, 2) A series of practical recommendations suitable for designing of human computer interfaces of fire emergency response information system, 3) Human computer interface mock-ups for an information system to enhance Situation Awareness of fire fighters and 4) A conceptual architecture for the underlying information system. In addition, this study also developed an enhanced cognitive task analysis tool capable of exploring the needs of emergency first responders. This thesis contributes to our understanding of how information systems could be designed to enhance the Situation Awareness of first responders in a fire emergency. These results will be of particular interest to practicing information systems designers and developers in the FRS in the UK and to the wider academic community

Journal of Telecommunications and Information Technology

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