Wireless sensor networks (WSNs) are low-cost, special-purpose networks introduced to resolve various daily life domestic, industrial, and strategic problems. These networks are deployed in such places where the repairments, in most cases, become difficult. The nodes in WSNs, due to their vulnerable nature, are always prone to various potential threats. The deployed environment of WSNs is noncentral, unattended, and administrativeless; therefore, malicious attacks such as distributed denial of service (DDoS) attacks can easily be commenced by the attackers. Most of the DDoS detection systems rely on the analysis of the flow of traffic, ultimately with a conclusion that high traffic may be due to the DDoS attack. On the other hand, legitimate users may produce a larger amount of traffic known, as the flash crowd (FC). Both DDOS and FC are considered abnormal traffic in communication networks. The detection of such abnormal traffic and then separation of DDoS attacks from FC is also a focused challenge. This paper introduces a novel mechanism based on a Bayesian model to detect abnormal data traffic and discriminate DDoS attacks from FC in it. The simulation results prove the effectiveness of the proposed mechanism, compared with the existing systems.

The innovations in the internet of things and the advent of media-intensive applications have massively increased the data burden on third-and fourth-generation (wireless cellular technology) mobile networks. The existing cellular networks face an overloading issue due to the growing rate of data traffics resultantly reducing the quality of service (QoS) in terms of delay and throughput. To overcome this issue, mobile network operators are searching for well-organized ways to support such a massive data flow. Mobile data offloading schemes through small cells such as WiFi can be implemented to provide a lucrative and effective solution. A game-based quality of service model for heterogeneous traffic to achieve the quality of service parameters is proposed. This model deals with a trade-off between mobile network operators and access points, allocating economic incentives by mobile network operators to acess points for saving the spectrum. The model is simulated in MATLAB and the preliminary analyses proved the intense impact of the model on the offloading ratio and energy consumption by achieving superior results in the aforementioned parameters.