{"id":{"repo_id":"utc","oai_identifier":"oai:scholar.utc.edu:theses-2155"},"canonical_url":"https://search.dev.ndltd.org/etd/utc/oai:scholar.utc.edu:theses-2155","repository":{"repo_id":"utc","name":"University of Tennessee - Chattanooga","base_url":"https://scholar.utc.edu/do/oai/"},"display":{"title":"Phantom jam Sybil attack in connected vehicular networks","abstract":"Vehicular Ad-hoc Networks (VANETs) are vulnerable to Sybil attacks, mostly due to the lack of encryption in BSMs. In VANETs, multiple digital certificates (pseudonyms) are assigned to each vehicle to ensure their privacy. However, malicious nodes can exploit these pseudonyms to create ghost vehicles, inducing fake traffic jams and disturbance to other vehicles which may lead to accidents. In this work, we have developed the first sophisticated sybil attack, in which an attacker uses legitimate pseudonyms to create multiple ghost vehicles. These ghost vehicles transmit realistic kinematic data, using trajectory formulas and road maps. Additionally, the ghost vehicles randomly simulate sudden brakes before acceleration to cause sudden reactions from surrounding vehicles, potentially leading to collisions. The attack was tested using a mainstream simulation framework. Our experimental results demonstrate that the proposed attack is evasive to the state-of-the-art misbehavior detection systems.","abstract_html":"Vehicular Ad-hoc Networks (VANETs) are vulnerable to Sybil attacks, mostly due to the lack of encryption in BSMs. In VANETs, multiple digital certificates (pseudonyms) are assigned to each vehicle to ensure their privacy. However, malicious nodes can exploit these pseudonyms to create ghost vehicles, inducing fake traffic jams and disturbance to other vehicles which may lead to accidents. In this work, we have developed the first sophisticated sybil attack, in which an attacker uses legitimate pseudonyms to create multiple ghost vehicles. These ghost vehicles transmit realistic kinematic data, using trajectory formulas and road maps. Additionally, the ghost vehicles randomly simulate sudden brakes before acceleration to cause sudden reactions from surrounding vehicles, potentially leading to collisions. The attack was tested using a mainstream simulation framework. Our experimental results demonstrate that the proposed attack is evasive to the state-of-the-art misbehavior detection systems.","abstract_has_math":false,"creators":["Mohamed, Ahmed Ali Elamin"],"institution":"University of Tennessee at Chattanooga","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Xie, Mengjun","Liang, Yu; Sakib, Shahnewaz Karim","College of Engineering and Computer Science"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-24T05:47:21Z","subjects":["Anomaly detection (Computer security)","Vehicular ad hoc networks (Computer networks)--Security measures"],"languages":["English","eng"],"rights":[],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://scholar.utc.edu/theses/975","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Xie, Mengjun","Liang, Yu; Sakib, Shahnewaz Karim","College of Engineering and Computer Science"]},{"key":"dc:creator","label":"Author","values":["Mohamed, Ahmed Ali Elamin"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2024-12-01T08:00:00Z"]},{"key":"dc:publisher","label":"Institution","values":["University of Tennessee at Chattanooga","Chattanooga (Tenn.)"]},{"key":"dc:relation","label":"Dc Relation","values":["Masters Theses and Doctoral Dissertations"]},{"key":"dc:type","label":"Dc Type","values":["Masters theses","Text"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Anomaly detection (Computer security)","Vehicular ad hoc networks (Computer networks)--Security measures"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholar.utc.edu/theses/975"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Dept. of Computer Science and Engineering","M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science."]},{"key":"dc:description.abstract","label":"Abstract","values":["Vehicular Ad-hoc Networks (VANETs) are vulnerable to Sybil attacks, mostly due to the lack of encryption in BSMs. In VANETs, multiple digital certificates (pseudonyms) are assigned to each vehicle to ensure their privacy. However, malicious nodes can exploit these pseudonyms to create ghost vehicles, inducing fake traffic jams and disturbance to other vehicles which may lead to accidents. In this work, we have developed the first sophisticated sybil attack, in which an attacker uses legitimate pseudonyms to create multiple ghost vehicles. These ghost vehicles transmit realistic kinematic data, using trajectory formulas and road maps. Additionally, the ghost vehicles randomly simulate sudden brakes before acceleration to cause sudden reactions from surrounding vehicles, potentially leading to collisions. The attack was tested using a mainstream simulation framework. Our experimental results demonstrate that the proposed attack is evasive to the state-of-the-art misbehavior detection systems."]},{"key":"dc:title","label":"Title","values":["Phantom jam Sybil attack in connected vehicular networks"]}]}],"canonical_facts":{"dc:contributor":["Xie, Mengjun","Liang, Yu; Sakib, Shahnewaz Karim","College of Engineering and Computer Science"],"dc:creator":["Mohamed, Ahmed Ali Elamin"],"dc:date":["2024-12-01T08:00:00Z"],"dc:description":["Dept. of Computer Science and Engineering","M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science."],"dc:description.abstract":["Vehicular Ad-hoc Networks (VANETs) are vulnerable to Sybil attacks, mostly due to the lack of encryption in BSMs. In VANETs, multiple digital certificates (pseudonyms) are assigned to each vehicle to ensure their privacy. However, malicious nodes can exploit these pseudonyms to create ghost vehicles, inducing fake traffic jams and disturbance to other vehicles which may lead to accidents. In this work, we have developed the first sophisticated sybil attack, in which an attacker uses legitimate pseudonyms to create multiple ghost vehicles. These ghost vehicles transmit realistic kinematic data, using trajectory formulas and road maps. Additionally, the ghost vehicles randomly simulate sudden brakes before acceleration to cause sudden reactions from surrounding vehicles, potentially leading to collisions. The attack was tested using a mainstream simulation framework. Our experimental results demonstrate that the proposed attack is evasive to the state-of-the-art misbehavior detection systems."],"dc:identifier":["https://scholar.utc.edu/theses/975"],"dc:language":["English","eng"],"dc:publisher":["University of Tennessee at Chattanooga","Chattanooga (Tenn.)"],"dc:relation":["Masters Theses and Doctoral Dissertations"],"dc:rights":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["Anomaly detection (Computer security)","Vehicular ad hoc networks (Computer networks)--Security measures"],"dc:title":["Phantom jam Sybil attack in connected vehicular networks"],"dc:type":["Masters theses","Text"]},"updated_at":"2026-07-24T05:47:21Z"}