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Title: Managing the OTT Traffic in NFV Environment

Abstract: The emerging concepts Software Defined Networking (SDN) and Network Functions Virtualisation (NFV) lay the ground for system softwarization of future networks and services, under the umbrella of 5G. In this regard, a special focus is given to Video Distribution Networks (VDN), particularly in relation to existing difficulties in handling demands laid on the network as well as in relation to challenges in providing the expected Quality of Experience (QoE) and other performance demands like minimum energy consumption. The paper is focused on some of the most important elements associated with the virtualisation of Over-The-Top (OTT) video distribution networks and also advancing the system for managing the OTT traffic in Network Function Virtualisation (NFV) environment. The paper provides motivation, problem description, virtualisation target, standardisation efforts, NFV framework as well as short presentation of the main technical issues associated with managing the OTT traffic in NFV scenarios.

Keywords: Video Distribution Networks, Network Functions, Virtualisation, standards, architectural framework, Over-The-Top, QoE-service.
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WYSIWYG Web Builder
Blekinge Institute of Technology, Sweden
Mohammad Asad Rehman CHAUDHRY
Soptimizer, Canada
Dimitrie POPESCU
Old Dominion University, United States
Old Dominion University, United States
University of the District of Columbia, United States
Rashed RABIE
University of the District of Columbia, United States
Bogdan GHIȚĂ
Plymouth University, United Kingdom
Title: Transmitter Adaptation in Cognitive Radio Systems and Applications to Cognitive Radar

Abstract: The paper presents transmitter adaptation through interference avoidance (IA) for enabling more efficient use of the frequency spectrum in emerging cognitive radio (CR) systems. IA is introduced in a general signal space framework as a procedure that mitigates interference and improves the signal-to-interference+noise ratio (SINR) at the intended receiver by distributing the transmitted signal energy over signal dimensions with minimum interference. Application of IA for transmitter adaptation is illustrated in the context of spectral shaping for OFDM-based CR systems as well as SINR-based waveform design for cognitive radar for estimating the characteristics of multiple mutually interfering targets.

Keywords: cognitive radio, cognitive radar, interference avoidance, transmitter adaptation, waveform design.
Title: On a Game Theoretic Approach to Detect the Low-Rate Denial of Service Attacks

Abstract: Low-Rate DoS attacks such as “Shrew” and “New Shrew” attacks, unlike the high rate attacks, are hard for the router to detect. Attackers choose a malicious low-rate bandwidth to exploit the TCP’s congestion control window algorithm and the transition time-out mechanism. By using a game theoretic approach, we focus on the best strategy and solution for a computer network to detect the Low-Rate Denial of Service attacks. In our experiments we simulated the network congestion attacks and we proposed a practical solution by using a sigmoid filter. The proposed solution is to create a threshold bandwidth filter at the router that allows a specific bandwidth, so when traffic exceeds the threshold it will be dropped, or if the traffic is below the threshold, it will be redirected to a honeypot server. In our game theory approach, we considered the game players in a static simultaneous game. The defender’s strategy is to determine an optimal firewall option to detect the attacker traffic, and the attacker’s strategy is to find the low rate to exploit the retransmission time-out mechanism and elude the detector. We calculated the payoff for the each player and for each strategy. We solved the game by finding the Nash Equilibrium where players do not have any profit in using any other strategy. Our experiments and calculations lead to the conclusion that a mixed strategy will the best response for an organization which will be using the proposed approach.
Title: Internet of Profiling - Traffic, Users, and Applications

Abstract: Recent years have witnessed a significant increase in monitoring network traffic in order to profile user behaviour in order to provide better service. The presentation will provide a review of these efforts, highlighting the benefits brought by traffic profiling, particularly in relation to providing a better user experience and higher quality of service. The discussion will focus on three headings: identifying and profiling applications based on statistical analysis of traffic, identifying users and anomaly detection based on network interaction, and providing fairness in a heterogeneous user environment. Profiling applications is a challenging task in the context of encryption and tunnelling, but allows better provision of network resources, in line with the needs of each application, from email to video streaming. Identifying users may raise concerns in terms of privacy, but the primary aim is not to single them out but to cater for their needs at an aggregate level, both in terms of dealing with significant variations as well as potentially acting as afirst line of defence when anomalies are detected. Finally, while globally the behaviour of users may appear similar, there is significant variation in terms of the demand, usage,and expectations of each user; ensuring fairness in such a diverse environment requiresacknowledging the user requirements and accommodating them against a heterogenous environment in terms of provision and demand. The presentation will draw from a number of research studies undertaken over the recent years in the above areas, both across the research community as well as at Plymouth University, and discuss how the findings impact on the wider user community.
National University of Computer & Emerging Sciences, Pakistan