## 10 Possible Solutions to Security Issues  
We have proposed some solutions in [15, 26] to the issues mentioned above. The issues of identity, PN generation, security, and privacy preservation have been addressed in [15]. We propose a digital identity scheme for VANETs (DIVA) by considering that it is the driver who is to be held liable for the vehicle and not _vice versa_. Therefore, we use the identification of the vehicle (VID) and the driver (DrL) to form a new digital identity. The two identities are merged into one after authentication from two authorities, _i.e._, the vehicle registration authority and the driver license authority. Each of the two authorities issues the user a token and secret keys which are then used by the user to generate their pseudonym. Therefore, even if the master key is compromised, the tokens can only be traced by the two authorities and no individual authority can reveal the true identity of the user. Moreover, in DIVA, the PNs are being generated at the OBU, which reduces the latency at the RSU. The performance of the scheme is compared with two other schemes efficient conditional privacy preservation (ECPP) [33] and pseudonymous authentication-based conditional privacy (PACP) [34] as shown in Figure 6.  
To compute latency at the RSU, the same parameters are used as in [34], _i.e._, key size of 160 bits and times required for a pairing operation and point multiplication to be 7.3 ms and 8.5 ms, respectively. Figure 6: Comparison of protocol latency at RSU [15]. The major operations in our scheme for RSU to perform decryption and signature verification involve two pairing operations (PO) and one point multiplication (MP), whereas ECPP requires 13 MPs and six POs and PACP requires two POs and one MP for verification at RSU. However, in both PACP and ECPP, the RSU generates and verifies the PN tokens and short-lived key pairs, respectively, for the vehicles, which causes more delay as shown in Figure 6. The graph shows the latency when only one token is being generated for each vehicle as the number of vehicles increases from one to 100. In DIVA, the PNs are being generated at the OBU and therefore, there is no extra delay at the RSU and the latency is reduced at the RSU, which is desirable. The issues associated with trust and rogue nodes in VANETs are addressed in [26]. As discussed previously, trust is difficult to maintain in VANETs and honest nodes can turn rogue once they become part of the network. Therefore, a data-centric rogue node detection scheme (C-DAC) is presented in [26] to address the issues of trust and security in VANETs. A mechanism has been proposed where users can aggregate the data that they are receiving while sharing their own data with their neighbours. The scheme is not dependent on any past trust value and only relies on the data that is received from the node, which is highly desirable as trust is difficult to manage in VANETs. C-DAC allows the vehicles to get a very good picture of the _normal_ conditions/data in their vicinity. Therefore, any abnormal or anomalous data received can be rejected and the user reported. In order to check the proposed model, it is simulated using OMNET\(++\), SUMO [35], and VACaMobil [36]. OMNET is a modular C\(++\) library and framework that is used for network simulations. Simulation of Urban Mobility (SUMO) is a software tool for vehicular traffic generation by specifying speed, vehicle behaviour, road type, and conditions. VACaMobil is a car mobility manager for OMNET that works with SUMO. Different scenarios with and without accidents are simulated with parameters given in Table 3. The results show that using this scheme, vehicles can effectively determine false data and the emergency message can successfully be conveyed to vehicles that are far off so that they can gradually slow down. The proposed C-DAC scheme also effectively solves the problem of broadcast storms, _i.e._, when nodes try to send the same emergency message to alert other vehicles causing congestion and a choked network very quickly.