Biblio

Named Data Networking (NDN) is one of the most promising data-centric networks. NDN is resilient to most of the attacks that are possible in TCP/IP stack. Since NDN has different network architecture than TCP/IP, so it is prone to new types of attack. These attacks are Interest Flooding Attack (IFA), Cache Privacy Attack, Cache Pollution Attack, Content Poisoning Attack, etc. In this paper, we discussed the detection of IFA. First, we model the IFA on linear topology using the ndnSIM and CCNx code base. We have selected most promising feature among all considered features then we applied diïňĂerent machine learning techniques to detect the attack. We have shown that result of attack detection in case of simulation and implementation is almost same. We modeled IFA on DFN topology and compared the results of different machine learning approaches.

A Mobile Ad hoc Network (MANET) is a spontaneous network consisting of wireless nodes which are mobile and self-configuring in nature. Devices in MANET can move freely in any direction independently and change its link frequently to other devices. MANET does not have centralized infrastructure and its characteristics makes this network vulnerable to various kinds of attacks. Data transfer is a major problem due to its nature of unreliable wireless medium. Commonly used technique for secure transmission in wireless network is cryptography. Use of cryptography key is often involved in most of cryptographic techniques. Key management is main component in security issues of MANET and various schemes have been proposed for it. In this paper, a study on various kinds of key management techniques in MANET is presented.