Security and Privacy in Internet of Things with Crowd-Sensing

Liangmin Wang, Zhuo Lu, Hongjian Sun, Yantian Hou, Mengxing Huang
2017 Journal of Electrical and Computer Engineering  
e rapid proliferation of mobile sensing devices, such as smartphones, wearable devices, and mobile vehicles, has promoted the emergence of a novel sensing paradigm for Internet of ings (IoTs). Crowd-sensing, known as a promising data collection method, is becoming increasingly popular in IoTs due to its low deployment cost and large-scale spatial coverage. Crowd-sensing-based IoTs interconnects various physical objects, including human, sensors, and smart devices, to collect data through the
more » ... anced communication technology and process and share information with the assistance of cloud servers. Currently, a wide range of crowdsensing applications are fostered in various domains such as environmental monitoring, assistive healthcare, social network, business, and intelligent transportation. Numerous research challenges arise in the crowd-sensing-based IoTs, among which security and privacy are two critical issues that hinder the ubiquitous deployment of relevant applications. For data sensing in the front-end IoTs, sensed data may contain some sensitive information of mobile users. Moreover, data can be falsi ed and tampered with by external attackers or even be polluted by internal attackers (i.e., malicious users). For data storage and processing in the back-end IoTs, cloud servers may be curious to infer private information of data owners and query users or even maliciously modify some query results. In these circumstances, many factors, including user privacy, data con dentiality, integrity, reliability, and access control, should be taken into consideration in a holistic perspective. is special issue provides the opportunity for researchers, practitioners, and application developers to discuss the recent technical advances and future challenges in security and privacy protection for crowd-sensing-based IoTs. e topic of accepted papers pertains to security and privacy issues from di erent aspects, ranging from secure network architecture, secure and privacy-preserving data sensing, and data transmission to data processing in IoTs with crowd-sensing. Over the numerous submissions, six papers have been accepted a er the rigorous review process. We now list and give a brief summary of these papers as below. e paper "A Student Information Management System Based on Fingerprint Identi cation and Data Security Transmission" by P. Yang et al. studies the secure and reliable data transmission in the student information management system. Based on an improved AES algorithm, the authors propose a novel data encryption method and design a new S-box, which signi cantly reduces the encryption time. Experimental results also validate the e ciency of their algorithm. e paper "Vulnerability Analysis of Interdependent Scale-Free Networks with Complex Coupling" by C. Cao et al. mainly analyzes the vulnerability of interdependent scale-free networks with complex coupling based on the BA model. e results indicate that these networks have the same vulnerability against the maximum node attack, the load of the maximum node attack, and the random node attack, indicating that the coupling relationship between network nodes is an important factor in network design.
doi:10.1155/2017/2057965 fatcat:3i6d5hvfbjdbzjsn2y3k6uefwa