{'fraction_non_alphanumeric': 0.02527075812274368, 'fraction_numerical': 0.0009025270758122744, 'mean_word_length': 5.845679012345679, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A Novel Framework for Misbehavior Detection in SDN-based VANET

Vehicular Ad Hoc Networks (VANET) enables the communication between vehicles and Road Side Units (RSU) to execute numerous safety and non-safety applications. Insider nodes of VANET can misbehave by transmitting faulty and incorrect Vehicle-to-Everything (V2X) messages. Effective Misbehavior Detection System (MDS) is developed to detect such misbehaving insider nodes. MDS constantly monitors the transmitting messages to detect incorrect data packets by using plausibility and consistency checks. Based on these checks, MDS identifies misbehaving vehicles. However, existing detection systems are not adaptive to network changes. Hence, we propose a framework for misbehavior detection in Software-Defined Networking (SDN)based VANET by exploiting the programmability and flexibility features of SDN. SDN allows the dynamic adjustment of input parameters for the detection process according to the varying network context. Consequently, the proposed framework provides effective and accurate detection performance in diverse VANET scenarios.