Visible to the public Biblio

Filters: Keyword is vehicular networking  [Clear All Filters]
2018-05-02
Gu, P., Khatoun, R., Begriche, Y., Serhrouchni, A..  2017.  k-Nearest Neighbours classification based Sybil attack detection in Vehicular networks. 2017 Third International Conference on Mobile and Secure Services (MobiSecServ). :1–6.

In Vehicular networks, privacy, especially the vehicles' location privacy is highly concerned. Several pseudonymous based privacy protection mechanisms have been established and standardized in the past few years by IEEE and ETSI. However, vehicular networks are still vulnerable to Sybil attack. In this paper, a Sybil attack detection method based on k-Nearest Neighbours (kNN) classification algorithm is proposed. In this method, vehicles are classified based on the similarity in their driving patterns. Furthermore, the kNN methods' high runtime complexity issue is also optimized. The simulation results show that our detection method can reach a high detection rate while keeping error rate low.

2018-02-02
Anderson, E. C., Okafor, K. C., Nkwachukwu, O., Dike, D. O..  2017.  Real time car parking system: A novel taxonomy for integrated vehicular computing. 2017 International Conference on Computing Networking and Informatics (ICCNI). :1–9.
Automation of real time car parking system (RTCPS) using mobile cloud computing (MCC) and vehicular networking (VN) has given rise to a novel concept of integrated communication-computing platforms (ICCP). The aim of ICCP is to evolve an effective means of addressing challenges such as improper parking management scheme, traffic congestion in parking lots, insecurity of vehicles (safety applications), and other Infrastructure-to-Vehicle (I2V) services for providing data dissemination and content delivery services to connected Vehicular Clients (VCs). Edge (parking lot based) Fog computing (EFC) through road side sensor based monitoring is proposed to achieve ICCP. A real-time cloud to vehicular clients (VCs) in the context of smart car parking system (SCPS) which satisfies deterministic and non-deterministic constraints is introduced. Vehicular cloud computing (VCC) and intra-Edge-Fog node architecture is presented for ICCP. This is targeted at distributed mini-sized self-energized Fog nodes/data centers, placed between distributed remote cloud and VCs. The architecture processes data-disseminated real-time services to the connected VCs. The work built a prototype testbed comprising a black box PSU, Arduino IoT Duo, GH-311RT ultrasonic distance sensor and SHARP 2Y0A21 passive infrared sensor for vehicle detection; LinkSprite 2MP UART JPEG camera module, SD card module, RFID card reader, RDS3115 metal gear servo motors, FPM384 fingerprint scanner, GSM Module and a VCC web portal. The testbed functions at the edge of the vehicular network and is connected to the served VCs through Infrastructure-to-Vehicular (I2V) TCP/IP-based single-hop mobile links. This research seeks to facilitate urban renewal strategies and highlight the significance of ICCP prototype testbed. Open challenges and future research directions are discussed for an efficient VCC model which runs on networked fog centers (NetFCs).
2015-05-05
Eckhoff, D., Sommer, C..  2014.  Driving for Big Data? Privacy Concerns in Vehicular Networking Security Privacy, IEEE. 12:77-79.

Communicating vehicles will change road traffic as we know it. With current versions of European and US standards in mind, the authors discuss privacy and traffic surveillance issues in vehicular network technology and outline research directions that could address these issues.