Wireless Communications and Mobile Computing

Security and Privacy Challenges for Internet-of-Things and Fog Computing


Publishing date
01 Jul 2018
Status
Published
Submission deadline
09 Mar 2018

Lead Editor

1Singapore Management University, Singapore

2Fuzhou University, Fuzhou, China

3The University of Texas at San Antonio, San Antonio, USA

4Nanjing University of Posts and Telecommunications, Nanjing, China


Security and Privacy Challenges for Internet-of-Things and Fog Computing

Description

Internet-of-Things (IoT) has profound impacts on our daily life by offering advanced connectivity of devices, systems, and services that go beyond machine-to-machine (M2M) communications and covers a variety of protocols, domains, and applications. Billions of IoT devices (embedded with electronics, software, sensors, actuators, and network connectivity) collect data through wireless technology and are able to interoperate within the existing Internet infrastructure. Traditional cloud computing framework stores and processes these massive amounts of data, which requires vast amounts of bandwidth, storage, and computation resources. Unfortunately, it leaves near-user fog devices (such as smart meters, smart traffic lights) as dumb portals and negatively impacts the performance of the cloud-centric system. The new fog/edge computing paradigm allows data storing and processing being implemented at the network edge or anywhere along the cloud-to-endpoint continuum, rather than completely in a relatively small number of clouds, which can meet users’ requirements to a maximum. It also overcomes IoT devices’ limited processing and storage capabilities and battery life and network bandwidth constraints and allows us to design a far more capable architecture. However, this new IoT-Fog paradigm brings many security and privacy issues such as information confidentiality, authentication and authorization, and secure communication. With nearly unlimited computation and storage resources, the traditional cloud-based platform can even use heavyweight lattice-based cryptosystem to enhance the system security, which cannot be performed by the resource constrained edge devices. Moreover, different from the tradition IoT-cloud architectures, millions of smart fog devices are wildly distributed and located in different areas, which can be easily compromised by some malicious parties. These compromised fog devices may temper the data collected by smart health IoT devices, and these fake data may mislead the data user or even threat people’s lives. To address these arising challenges and opportunities different from traditional cloud based architecture, this special issue is interested in inviting and gathering recent advanced security and privacy techniques relevant to the convergence of Internet-of-Things with fog computing.

Potential topics include but are not limited to the following:

  • Authentication in crowdsourcing of IoT and fog computing
  • Lightweight data protection scheme for smart IoT devices
  • Secure machine learning technique on edge devices for IoT data analysis
  • Hardware security and privacy issues for IoT and edge devices
  • Secure data integrity and validation techniques for smart IoT devices
  • Privacy computation and processing protocols on edge-cloud platform
  • Secure M2M communication for smart IoT and edge devices
  • Formal security model for cryptographic protocols for fog computing
  • Future and smart fog-based vulnerability assessment interfaces
  • Design and tune intrusion detection systems for distributed IoT and fog devices
  • Secure programming models and toolkits for fog computing in IoT
  • Virtualization security and management for mobile and fog computing
  • Experiment prototype for secure and trusted IoT-Fog framework
  • Blockchains and smart contracts for IoT and fog computing
  • New privacy challenges in IoT and fog-cloud computing

Articles

  • Special Issue
  • - Volume 2018
  • - Article ID 7218061
  • - Research Article

Multitask Allocation to Heterogeneous Participants in Mobile Crowd Sensing

Weiping Zhu | Wenzhong Guo | ... | Haoyi Xiong
  • Special Issue
  • - Volume 2018
  • - Article ID 1701675
  • - Research Article

Traceable Ciphertext-Policy Attribute-Based Encryption with Verifiable Outsourced Decryption in eHealth Cloud

Qi Li | Hongbo Zhu | ... | Tao Zhang
  • Special Issue
  • - Volume 2018
  • - Article ID 9437936
  • - Research Article

A Rational Exchange Protocol under Asymmetric Information in Wireless Sensor Networks

Zhen Lv | Changgen Peng | ... | Junwei Zhang
  • Special Issue
  • - Volume 2018
  • - Article ID 4746020
  • - Research Article

Reliable Ant Colony Routing Algorithm for Dual-Channel Mobile Ad Hoc Networks

YongQiang Li | Zhong Wang | ... | BaiSong Chen
  • Special Issue
  • - Volume 2018
  • - Article ID 7805408
  • - Research Article

Gleer: A Novel Gini-Based Energy Balancing Scheme for Mobile Botnet Retopology

Yichuan Wang | Yefei Zhang | ... | Yanxiao Liu
  • Special Issue
  • - Volume 2018
  • - Article ID 4392524
  • - Research Article

Mining the Relationship between Spatial Mobility Patterns and POIs

Liping Huang | Yongjian Yang | ... | Limin Yu
  • Special Issue
  • - Volume 2018
  • - Article ID 5401890
  • - Research Article

An Efficient Identity-Based Proxy Blind Signature for Semioffline Services

Hongfei Zhu | Yu-an Tan | ... | Yuanzhang Li
  • Special Issue
  • - Volume 2018
  • - Article ID 4627108
  • - Research Article

Niffler: A Context-Aware and User-Independent Side-Channel Attack System for Password Inference

Benxiao Tang | Zhibo Wang | ... | Lina Wang
Wireless Communications and Mobile Computing
 Journal metrics
Acceptance rate34%
Submission to final decision80 days
Acceptance to publication38 days
CiteScore1.470
Impact Factor1.396
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