scholarly journals The Impact of the Adversary’s Eavesdropping Stations on the Location Privacy Level in Internet of Vehicles

2020 ◽  
Author(s):  
Messaoud Babaghayou ◽  
Nabila Labraoui ◽  
Ado Adamou Abba Ari ◽  
Mohamed Amine Ferrag ◽  
Leandros Maglaras
Keyword(s):  
Location Privacy ◽  
Internet Of Vehicles ◽  
The Impact ◽  
Privacy Level

scholarly journals A Privacy Preserved, Trust Relationship (PTR) Model for Internet of Vehicles

Electronics ◽  
2021 ◽  
Vol 10 (24) ◽  
pp. 3105
Author(s):  
Haleem Farman ◽  
Abizar Khalil ◽  
Naveed Ahmad ◽  
Waleed Albattah ◽  
Muazzam A. Khan ◽  
...  
Keyword(s):  
Urban Areas ◽  
Location Privacy ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Analytic Network Process ◽  
Malicious Nodes ◽  
Privacy And Security ◽  
Internet Of Vehicles ◽  
Trust Relationship ◽  
The Impact

The Internet of vehicles (IoV) depicts a reality where ordinary things are connected to vehicular ad-hoc networks (VANETs), allowing them to transmit and collaborate. By placing these regular objects in VANETs and making them available at any time, this network and data sharing may raise real privacy and security issues. Thus, group-based communication is mostly preferred in the literature. However, in heavy network scenarios, cluster-based communication mostly leads to additional overload in the form of the group leader that causes delay and disrupts the performance of a network. Due to the interaction of VANETs with applications that are not stable for life, privacy and security mechanism for detecting many malicious nodes is in great demand. Therefore, a multi-phantom node selection has been proposed in this paper to select trustworthy, normal, and malicious nodes. The multi-phantom node scheme is proposed to reduce the phantom node load, where the multi-lateral nodes in a cluster act as a phantom node to share the load. A multi criteria decision-making (MCDM) methodology (analytic network process) is used to optimize the phantom node to pre-serve privacy using the privacy preserved trust relationship (PTR) model. The results show checking the stability of parameters and using sensitivity analysis by considering different scenarios for the most optimal phantom node to preserve vehicle location privacy. The impact of the proposed model will be more clearly visible in its real-time implementation in urban areas vehicle networks.

scholarly journals Impact of Frequency of Location Reports on the Privacy Level of Geo-indistinguishability

2020 ◽  
Vol 2020 (2) ◽  
pp. 379-396 ◽  
Author(s):  
Ricardo Mendes ◽  
Mariana Cunha ◽  
João P. Vilela
Keyword(s):  
Location Privacy ◽  
Differential Privacy ◽  
Location Based Services ◽  
Potential Threat ◽  
Mobility Data ◽  
Research Gap ◽  
Privacy Budget ◽  
The Impact ◽  
User Location ◽  
Privacy Level

AbstractLocation privacy has became an emerging topic due to the pervasiveness of Location-Based Services (LBSs). When sharing location, a certain degree of privacy can be achieved through the use of Location Privacy-Preserving Mechanisms (LPPMs), in where an obfuscated version of the exact user location is reported instead. However, even obfuscated location reports disclose information which poses a risk to privacy. Based on the formal notion of differential privacy, Geo-indistinguishability has been proposed to design LPPMs that limit the amount of information that is disclosed to a potential adversary observing the reports. While promising, this notion considers reports to be independent from each other, thus discarding the potential threat that arises from exploring the correlation between reports. This assumption might hold for the sporadic release of data, however, there is still no formal nor quantitative boundary between sporadic and continuous reports and thus we argue that the consideration of independence is valid depending on the frequency of reports made by the user. This work intends to fill this research gap through a quantitative evaluation of the impact on the privacy level of Geo-indistinguishability under different frequency of reports. Towards this end, state-of-the-art localization attacks and a tracking attack are implemented against a Geo-indistinguishable LPPM under several values of privacy budget and the privacy level is measured along different frequencies of updates using real mobility data.

scholarly journals A collaborative scheduling strategy for IoV computing resources considering location privacy protection in mobile edge computing environment

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Meiyu Pang ◽  
Li Wang ◽  
Ningsheng Fang
Keyword(s):  
Privacy Protection ◽  
Location Privacy ◽  
Completion Rate ◽  
Task Completion ◽  
Mobile Edge Computing ◽  
Computing Environment ◽  
Internet Of Vehicles ◽  
Scheduling Strategy ◽  
Collaborative Scheduling ◽  
Location Privacy Protection

Abstract This paper proposes a collaborative scheduling strategy for computing resources of the Internet of vehicles considering location privacy protection in the mobile edge computing environment. Firstly, a multi area multi-user multi MEC server system is designed, in which a MEC server is deployed in each area, and multiple vehicle user equipment in an area can offload computing tasks to MEC servers in different areas by a wireless channel. Then, considering the mobility of users in Internet of vehicles, a vehicle distance prediction based on Kalman filter is proposed to improve the accuracy of vehicle-to-vehicle distance. However, when the vehicle performs the task, it needs to submit the real location, which causes the problem of the location privacy disclosure of vehicle users. Finally, the total cost of communication delay, location privacy of vehicles and energy consumption of all users is formulated as the optimization goal, which take into account the system state, action strategy, reward and punishment function and other factors. Moreover, Double DQN algorithm is used to solve the optimal scheduling strategy for minimizing the total consumption cost of system. Simulation results show that proposed algorithm has the highest computing task completion rate and converges to about 80% after 8000 iterations, and its performance is more ideal compared with other algorithms in terms of system energy cost and task completion rate, which demonstrates the effectiveness of our proposed scheduling strategy.

scholarly journals Permutation Matrix Encryption Based Ultralightweight Secure RFID Scheme in Internet of Vehicles

Sensors ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 152 ◽  
Author(s):  
Kai Fan ◽  
Junbin Kang ◽  
Shanshan Zhu ◽  
Hui Li ◽  
Yintang Yang
Keyword(s):  
Radio Frequency Identification ◽  
High Speed ◽  
Location Privacy ◽  
Authentication Scheme ◽  
Permutation Matrix ◽  
The Internet ◽  
Automatic Identification ◽  
Personal Privacy ◽  
Internet Of Vehicles ◽  
Rfid System

Radio frequency identification (RFID) is a kind of non-contact automatic identification technology. The Internet of Vehicles (IoV) is a derivative of the Internet of Things (IoT), and RFID technology has become one of the key technologies of IoV. Due to the open wireless communication environment in RFID system, the RFID system is easy to be exposed to various malicious attacks, which may result in privacy disclosure. The provision of privacy protection for users is a prerequisite for the wide acceptance of the IoV. In this paper, we discuss the privacy problem of the RFID system in the IoV and present a lightweight RFID authentication scheme based on permutation matrix encryption, which can resist some typical attacks and ensure the user’s personal privacy and location privacy. The fast certification speed of the scheme and the low cost of the tag is in line with the high-speed certification requirement in the Internet of vehicles. In this thesis, the specific application scenarios of the proposed RFID authentication scheme in the IoV is also discussed.

scholarly journals Multilevel Privacy Controlling Scheme to Protect Behavior Pattern in Smart IoT Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Asad Khan ◽  
Muhammad Mehran Arshad Khan ◽  
Muhammad Awais Javeed ◽  
Muhammad Umar Farooq ◽  
Adeel Akram ◽  
...  
Keyword(s):  
Location Privacy ◽  
Pattern Mining ◽  
Behavior Pattern ◽  
Design Model ◽  
Sensor Nodes ◽  
Frequent Pattern ◽  
Time Duration ◽  
Four Levels ◽  
Traditional Approaches ◽  
Privacy Level

Traditional approaches generally focus on the privacy of user’s identity in a smart IoT environment. Privacy of user’s behavior pattern is an important research issue to address smart technology towards improving user’s life. User’s behavior pattern consists of daily living activities in smart IoT environment. Sensor nodes directly interact with activities of user and forward sensing data to service provider server (SPS). While availing the services provided by a server, users may lose privacy since the untrusted devices have information about user’s behavior pattern and it may share data with adversary. In order to resolve this problem, we propose a multilevel privacy controlling scheme (MPCS) which is different from traditional approaches. MPCS is divided into two parts: (i) behavior pattern privacy degree (BehaviorPrivacyDeg), which works as follows: firstly, frequent pattern mining-based time-duration algorithm (FPMTA) finds the normal pattern of activity by adopting unsupervised learning. Secondly, patterns compact algorithm (PCA) is proposed to store and compact the mined pattern in each sensor device. Then, abnormal activity detection time-duration algorithm (AADTA) is used by current triggered sensors, in order to compare the current activity with normal activity by computing similarity among them; (ii) multilevel privacy design model: we have divided privacy of users into four levels in smart IoT environment, and by using these levels, the server can configure privacy level for users according to their concern. Multilevel privacy design model consists of privacy-level configuration protocol (PLCP) and activity design model. PLCP provides fine privacy controls to users while enabling users to set privacy level. In PLCP, we introduce level concern privacy algorithm (LCPA) and location privacy algorithm (LPA), so that adversary could not damage the data of user’s behavior pattern. Experiments are performed to evaluate the accuracy and feasibility of MPCS in both simulation and real-case studies. Results show that our proposed scheme can significantly protect the user’s behavior pattern by detecting abnormality in real time.

scholarly journals Incorporating IEEE 1609.2-2016 Standard with Internet of Things-Based Low Power WAVE Devices

2020 ◽  
Vol 55 (1) ◽  
Author(s):  
Yaarob Al-Nidawi ◽  
Mahmood Zaki Abdullah
Keyword(s):  
Internet Of Things ◽  
Low Power ◽  
Wireless Access ◽  
The Internet ◽  
Power Devices ◽  
Internet Of Vehicles ◽  
Power Wave ◽  
The Impact ◽  
The Internet Of Things ◽  
Access Security

The integration of low-power devices in different aspects of life has increased the challenges of mitigating the impact of the heterogeneity of different related technologies. Accordingly, the Internet of Things context is an umbrella that diffuses different proprietary protocols into standardized forms to overcome the heterogeneity problem. The recent IEEE 1609.2-2016 standard is tackling the issue of wireless access security in the vehicular environment. An obstacle arose by which Internet of Things-based, low-power devices are integrated into the Internet of Vehicles cloud. In turn, the overhead of Internet of Vehicles-based protocols must be analyzed regarding the adaptability of low-power devices in the vehicular environment. This paper investigates the burden of the IEEE 1609.2 security stack on Internet of Things-based, limited-capability devices and defines the possible approaches to incorporate these low-power devices within the vehicular network under the IEEE 1609.2 standard. The proposed methodology, through the conducted simulations, demonstrates low security overhead with a 40% reduction in consumed energy over the default WAVE stack. In addition, the results show that including low-power devices within the Internet of Vehicles paradigm is possible, but still more enhancements and contributions are required to minimize the overhead of the WAVE security stack.

scholarly journals Location privacy preserving scheme based on dynamic pseudonym swap zone for Internet of Vehicles

2019 ◽  
Vol 15 (7) ◽  
pp. 155014771986550 ◽  
Author(s):  
Min Yang ◽  
Yong Feng ◽  
Xiaodong Fu ◽  
Qian Qian
Keyword(s):  
Location Privacy ◽  
Privacy Preserving ◽  
Communication Cost ◽  
Vehicle Dynamic ◽  
Internet Of Vehicles ◽  
On Demand ◽  
Vehicle Density ◽  
Simulation Results

In Internet of Vehicles, establishing swap zones in which vehicles can exchange pseudonyms is an effective method to enhance vehicles’ location privacy. In this article, we propose a new scheme based on dynamic pseudonym swap zone, to protect location privacy of vehicles. For each vehicle, dynamic pseudonym swap zone allows it dynamically to establish a temporary pseudonym swap zone on demand to exchange the pseudonym with another random vehicle in the just formed zone. This randomness of choosing the pseudonym exchanging vehicles prevents dynamic pseudonym swap zone from the secure risk that the information of exchanging participants exposes to their group manager in some existing works in which each pair of pseudonym exchanging participants is assigned by the manager. To avoid the high communication and computation overhead of frequently swapping pseudonyms, dynamic pseudonym swap zone adopts a combination of swap and update to achieve the unlinkability between new and previous pseudonyms. Moreover, dynamic pseudonym swap zone can self-adapt to the varying surroundings to reduce the communication cost of forming pseudonym swap zones in high vehicle density areas. The analysis and simulation results show that our proposed dynamic pseudonym swap zone is a high location privacy preserving, secure, auditable scheme.

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