Secure End-to-End Communications in Mobile Networks

2009 - 2010Cellular communication has become an important part of our daily life. Besides using cell phones for voice communication, we are now able to access the Internet, conduct monetary transactions, send voice, video and text messages and new services continue to be added. The frequencies over which voice is transmitted are public, so voice encryption is necessary to avoid interception of the signal over the air. But once the signal reaches the operators Base Station (BS), it will be transmitted to the receiver over a wired or wireless mean. In either case, no protection is de ned. This does not seem a problem, but this is not true. Along the path across operator network, voice is at risk. It will only be encrypted again, with a di erent key, from the BS to the receiver if the receiver is herself a mobile user. Moreover, voice encryption is not mandatory. The choice whether or not to accept an unprotected communication is up to the network. When adopted, the same encryption algorithm is used for sending SMS messages between mobile telephones and base stations and for encrypting of calls. Unfortunately, vulnerabilities in this encryption systems were already revealed more than 10 years ago and more continue to be discovered. Currently the most popular communication technologies are the GSM and the UMTS. The UMTS is in use as a successor to GSM. Along with mobile phone services, It provides rapid data communication. The security algo- rithms in UMTS di ers from GSM in two important ways: encryption and mutual authentication. Although security standards have been improved, the end- to-end security is not provided... [edited by Author]IX n.s

Multimedia in mobile networks: Streaming techniques, optimization and User Experience

1.UMTS overview and User Experience 2.Streaming Service & Streaming Platform 3.Quality of Service 4.Mpeg-4 5.Test Methodology & testing architecture 6.Conclusion

Performance evaluation of information and communications technology infrastructure for smart distribution network applications

This thesis was submitted for the degree of Master of Philosophy and awarded by Brunel University.Current electrical networks require secure, scalable and cost-effective Information and Communications Technology (ICT) solutions to facilitate the novel functionalities required by Smart Grids. Countries around the globe are investigating alternative energy sources to mitigate the current energy crisis and environmental issues experienced by many countries due to global warming, rapid growth of population, inefficient energy management, dwindling fossil fuel resources, etc. Therefore, alternative or renewable energy sources, such as wind, solar, hydro, combined heat and power, etc., are required to mitigate such a crisis and such sources will also need to be integrated in to the power grid in a distributed manner. Such distributed energy sources are mainly connected to the distribution networks and introduce huge challenges to the distribution network operator (DNO). Many of these challenges cannot be dealt with effectively using existing network operation mechanisms therefore the research and development of novel ICT solutions to support smart distribution network operation is required. This research investigated suitable ICT solutions to enable the Smart Grid to tackle these challenges and proposes ICT infrastructure models that can be used for simulation studies in order to investigate cost-effective, scalable and secure solutions for the DNOs. Initially, a Quality of Service (QoS) monitoring test-bed was proposed to evaluate the performance of bandwidth intensive applications, such as smart meter data transmission. Simulation studies for different communication technologies, cellular and Power Line Communication (PLC), were also carried out and the simulation models were verified using experimental test results. Finally, the modelling and analysis of smart metering infrastructure was carried out using simulation and extensive studies were performed to evaluate the data transmission rate performance for different configurations of smart meters and concentrators