Biblio
Software Defined Network (SDN) is getting popularity both from academic and industry. Lot of researches have been made to combine SDN with future Internet paradigms to manage and control networks efficiently. SDN provides better management and control in a network through decoupling of data and control plane. Named Data Networking (NDN) is a future Internet technique with aim to replace IPv4 addressing problems. In NDN, communication between different nodes done on the basis of content names rather than IP addresses. Vehicular Ad-hoc Network (VANET) is a subtype of MANET which is also considered as a hot area for future applications. Different vehicles communicate with each other to form a network known as VANET. Communication between VANET can be done in two ways (i) Vehicle to Vehicle (V2V) (ii) Vehicle to Infrastructure (V2I). Combination of SDN and NDN techniques in future Internet can solve lot of problems which were hard to answer by considering a single technique. Security in VANET is always challenging due to unstable topology of VANET. In this paper, we merge future Internet techniques and propose a new scheme to answer timing attack problem in VANETs named as Timing Attack Prevention (TAP) protocol. Proposed scheme is evaluated through simulations which shows the superiority of proposed protocol regarding detection and mitigation of attacker vehicles as compared to normal timing attack scenario in NDN based VANET.
Nowadays, Online Social Networks (OSNs) are very popular and have become an integral part of our life. People are dependent on Online Social Networks for various purposes. The activities of most of the users are normal, but a few of the users exhibit unusual and suspicious behavior. We term this suspicious and unusual behavior as malicious behavior. Malicious behavior in Online Social Networks includes a wide range of unethical activities and actions performed by individuals or communities to manipulate thought process of OSN users to fulfill their vested interest. Such malicious behavior needs to be checked and its effects should be minimized. To minimize effects of such malicious activities, we require proper detection and containment strategy. Such strategy will protect millions of users across the OSNs from misinformation and security threats. In this paper, we discuss the different studies performed in the area of malicious behavior analysis and propose a framework for detection of malicious behavior in OSNs.