Biblio

Named Data Network (NDN) is considered to be the future of Internet architecture. The nature of NDN is to disseminate data based on the naming scheme rather than the location of the node. This feature caters to the need of vehicular applications, resulting in Vehicular Named Data Networks (VNDN). Although it is still in the initial stages of research, the collaboration has assured various advantages which attract the researchers to explore the architecture further. VNDN face challenges such as intermittent connectivity, mobility of nodes, design of efficient forwarding and naming schemes, among others. In order to develop effective forwarding strategies, behavior of data and interest packets under various circumstances needs to be studied. In this paper, propagation behavior of data and interest packets is analyzed by considering metrics such as Interest Satisfaction Ratio (ISR), Hop Count Difference (HCD) and Copies of Data Packets Processed (CDPP). These metrics are evaluated under network conditions such as varying network size, node mobility and amount of interest produced by each node. Simulation results show that data packets do not follow the reverse path of interest packets.

With the global widespread usage of the Internet, more and more cyber-attacks are being performed. Many of these attacks utilize IP address spoofing. This paper describes IP spoofing attacks and the proposed methods currently available to detect or prevent them. In addition, it presents a statistical analysis of the Hop Count parameter used in our proposed IP spoofing detection algorithm. We propose an algorithm, inspired by the Hop Count Filtering (HCF) technique, that changes the learning phase of HCF to include all the possible available Hop Count values. Compared to the original HCF method and its variants, our proposed method increases the true positive rate by at least 9% and consequently increases the overall accuracy of an intrusion detection system by at least 9%. Our proposed method performs in general better than HCF method and its variants.
 

IP spoofing based DDoS attack that relies on multiple compromised hosts in the network to attack the victim. In IP spoofing, IP addresses can be forged easily, thus, makes it difficult to filter illegitimate packets from legitimate one out of aggregated traffic. A number of mitigation techniques have been proposed in the literature by various researchers. The conventional Hop Count Filtering or probabilistic Hop Count Filtering based research work indicates the problems related to higher computational time and low detection rate of illegitimate packets. In this paper, DPHCF-RTT technique has been implemented and analysed for variable number of hops. Goal is to improve the limitations of Conventional HCF or Probabilistic HCF techniques by maximizing the detection rate of illegitimate packets and reducing the computation time. It is based on distributed probabilistic HCF using RTT. It has been used in an intermediate system. It has the advantage for resolving the problems of network bandwidth jam and host resources exhaustion. MATLAB 7 has been used for simulations. Mitigation of DDoS attacks have been done through DPHCF-RTT technique. It has been shown a maximum detection rate up to 99% of malicious packets.