Non-stationary behavior of aggregated IP traffic patterns was demonstrated in a number of studies. However, none of those did either consider practical aspects of this phenomenon or propose suitable model to capture it. Searching for model for IP traffic aggregates we introduce the concept of local stationarity and demonstrate that it allows to model traffic patterns measured in high-speed oper...

OBJECTIVE The purpose of this study was to explore the interrelationship between driver distraction and characteristics of driver behavior associated with reduced highway traffic efficiency. BACKGROUND Research on the three-phase traffic theory and on behavioral driving suggests that a number of characteristics associated with efficient traffic flow may be affected by driver distraction. Prev...

in this paper, the advantage of reinforcement learning to develop a new traffic shaper is invoked in order to obtain a reasonable utilization of bandwidth while preventing traffic overload in other parts of the network. this leads to a reduction in the total number of packet droppings in the whole network. the method is implemented in a novel proposed intelligent simulation environment. keeping...

Risky driving behavior is regarded as being one of the best predictors of traffic accidents. Traffic violations certainly signal risky driving behavior, but the analysis of the linkage of traffic violations, individual and vehicle characteristics and annual mileage has so far been hampered by the difficulty of gaining access to appropriate disaggregate data. The contribution of this paper is th...

Malware is a major threat to security and privacy of network users. A large variety of malware is typically spread over the Internet, hiding in benign traffic. New types of malware appear every day, challenging both the research community and security companies to improve malware identification techniques. In this paper we present MAGMA, MultilAyer Graphs for MAlware detection, a novel malware ...

Traffic generation in mobile networks is heavily dependent on user behavior because the users move around with their terminals. For example, at a special event such as a fireworks display or football game, the people will congregate in a specific place and may try to make calls, generating unpredictable excessive traffic, leading to network congestion. When the users cannot get through due to c...

Traffic measurement and analysis is nowadays a very critical task and requires complex and high-cost traffic analysis equipment and infrastructure. The difficulty increases when high bandwidth connections are to be monitored. Network topology, the network technology used, applications and user behavior influence the overall traffic on the network. For network planning and provisioning is crucia...

Seasonal ARIMA model is a good traffic model capable of capturing the behavior of a network traffic stream. In this paper, we give a general expression of seasonal ARIMA models with two periodicities and provide procedures to model and to predict traffic using seasonal ARIMA models. The experiments conducted in our feasibility study showed that seasonal ARIMA models can be used to model and pre...