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Security and Safety in the Presence of Pervasive and Networked Devices

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (1 February 2020) | Viewed by 2256

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Department of Mathematics and Computer Science (DMI), University of Catania, 95125 Catania, Italy
Interests: software engineering; artificial intelligence; distributed systems; energy production
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the near future, many more devices will be deployed in urban infrastructures and connected to the ubiquitous Internet, thanks to the technological advances in 5G networks and in smart systems and sensors. Such connected devices will interact with the physical world to gather data and to regulate urban infrastructures.

The large-scale deployment of devices, including smartphones acquiring biometric signatures, city cameras, sensors, moving autonomous systems, etc., will be able to help detect human features and the identity of people, thereby affecting privacy. Moreover, such devices could leak data to external unknown agents, possibly having an impact on the privacy, security, and safety of people. Additionally, some devices (switches, cameras, microphones, small drones, etc.) could be compromised and programmed to annoy people and/or harm them.

The main goal of the proposed Special Issue is to provide a venue for contributions addressing correctness, privacy, security, and safety concerns of systems resulting from the communication of widely spread personal and industrial devices.

Papers are invited on methodologies, and applications of large complex systems consisting of a mix of personal, mostly thrusted devices, holding personal data, and other unknown parts, such as server hosts, sensors, and actuators, receiving data to carry out transactions, deliver messages, commands, etc.

Applications to the following areas are welcome:

- Security for smart personal devices;

- Cyber physical systems: IoT, smart cities;

- Safety, reliability of systems;

- Data analytics concerning privacy;

- Robustness and testability of systems;

- Detection of cyber-attacks and defense mechanisms;

- Privacy in sensor-rich urban environments;

- Safety in the presence of drones.

Prof. Emiliano Tramontana
Guest Editor

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Published Papers (1 paper)

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Research

25 pages, 2620 KiB  
Article
DGS-HSA: A Dummy Generation Scheme Adopting Hierarchical Structure of the Address
by Mingzhen Li, Yunfeng Wang, Guangcan Yang, Shoushan Luo, Yang Xin, Hongliang Zhu, Yixian Yang, Yuling Chen and Fugui Luo
Appl. Sci. 2020, 10(2), 548; https://doi.org/10.3390/app10020548 - 11 Jan 2020
Cited by 2 | Viewed by 1975
Abstract
With the increasing convenience of location-based services (LBSs), there have been growing concerns about the risk of privacy leakage. We show that existing techniques fail to defend against a statistical attack meant to infer the user’s location privacy and query privacy, which is [...] Read more.
With the increasing convenience of location-based services (LBSs), there have been growing concerns about the risk of privacy leakage. We show that existing techniques fail to defend against a statistical attack meant to infer the user’s location privacy and query privacy, which is due to continuous queries that the same user sends in the same location in a short time, causing the user’s real location to appear consecutively more than once and the query content to be the same or similar in the neighboring query. They also fail to consider the hierarchical structure of the address, so locations in an anonymous group may be located in the same organization, resulting in leaking of the user’s organization information and reducing the privacy protection effect. This paper presents a dummy generation scheme, considering the hierarchical structure of the address (DGS-HSA). In our scheme, we introduce a novel meshing method, which divides the historical location dataset according to the administrative region division. We also choose dummies from the historical location dataset with the two-level grid structure to realize the protection of the user’s location, organization information, and query privacy. Moreover, we prove the feasibility of the presented scheme by solving the multi-objective optimization problem and give the user’s privacy protection parameters recommendation settings, which balance the privacy protection level and system overhead. Finally, we evaluate the effectiveness and the correctness of the DGS-HSA through theoretical analysis and extensive simulations. Full article
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