Biblio

Mobile small cells that are enabled with Network Coding (NC) are seen as a potentially useful technique for Fifth Generation (5G) networks, since they can cover an entire city and can be put up on demand anywhere, any time, and on any device. Despite numerous advantages, significant security issues arise as a result of the fact that the NC-enabled mobile small cells are vulnerable to attacks. Intrusions are a severe security threat that exploits the inherent vulnerabilities of NC. In order to make NC-enabled mobile small cells to realize their full potential, it is essential to implement intrusion detection systems. When compared to homomorphic signature or hashing systems, homomorphic message authentication codes (MACs) provide safe network coding techniques with relatively smaller overheads. A number of research studies have been conducted with the goal of developing mobile small cells that are enabled with secure network coding and coming up with integrity protocols that are appropriate for such crowded situations. However, the intermediate nodes alter packets while they are in transit and hence the integrity of the data cannot be confirmed by using MACs and checksums. This research study has analyzed numerous intrusion detection models for NC enabled small cells. This research helps the scholars to get a brief idea about various intrusion detection models.

Reliable communication over the wireless network with high throughput is a major target for the next generation communication technologies. Network coding can significantly improve the throughput efficiency of the network in a cooperative environment. The small cell technology and device to device communication make network coding an ideal candidate for improved performance in the fifth generation of communication networks. However, the security concerns associated with network coding needs to be addressed before any practical implementations. Pollution attacks are considered one of the most threatening attacks in the network coding environment. Although there are different integrity schemes to detect polluted packets, identifying the exact adversary in a network coding environment is a less addressed challenge. This paper proposes a scheme for identifying and locating adversaries in a dense, network coding enabled environment of mobile nodes. It also discusses a non-repudiation protocol that will prevent adversaries from deceiving the network.

In this paper, we present a new Handover technique which combines Distribution Analysis Detector and Compressive Sampling Techniques. The proposed approach consists of analysing Received Signal probability density function instead of demodulating and analysing Received Signal itself as in classical handover. In this method we will exploit some mathematical tools like Kullback Leibler Distance, Akaike Information Criterion (AIC) and Akaike weights, in order to decide blindly the best handover and the best Base Station (BS) for each user. The Compressive Sampling algorithm is designed to take advantage from the primary signals sparsity and to keep the linearity and properties of the original signal in order to be able to apply Distribution Analysis Detector on the compressed measurements.