Privacy Protection Based on Stream Cipher for Spatiotemporal Data in IoT

Liu, Tianen; Wang, Yingjie; Li, Yingshu; Tong, Xiangrong; Qi, Lianyong; Jiang, Nan

doi:10.1109/jiot.2020.2990428

Cited by 52 publications

(16 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the next step, current work will continue to be improved by considering security and privacy issues [24][25][26][27][28][29][30][31][32][33]. In addition, more complex multiobjective solutions with more context factors [34][35][36][37][38][39][40][41] will be considered.…”

Section: Resultsmentioning

confidence: 99%

NAAM-MOEA/D-Based Multitarget Firepower Resource Allocation Optimization in Edge Computing

Deng

Yang

Liu

et al. 2021

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

In the edge environment, the multiobjective evolutionary algorithm based on decomposition (MOEA/D) has been widely used in the research of multitarget firepower resource allocation. However, as the MOEA/D algorithm uses a fixed neighborhood update mechanism, it is impossible to rationally allocate computing resources based on the difficulty of each subproblem optimization, which results in some problems such as reduced population evolution efficiency and poor evolution quality during the calculation process. In order to solve these problems, a decision mechanism for subproblems and population evolution stages is designed, and on this basis, a MOEA/D algorithm based on the neighborhood adaptive adjustment mechanism is proposed to adapt to the edge environment. The optimization model of multiobjective firepower resource allocation based on the maximization of damage effect and the minimization of strike cost is constructed and solved. Using the ZDT series of test functions for comparative experiments, the simulation results show that the proposed algorithm can balance the distribution and convergence of population evolution and obtain satisfactory optimization results.

show abstract

Section: Resultsmentioning

confidence: 99%

NAAM-MOEA/D-Based Multitarget Firepower Resource Allocation Optimization in Edge Computing

Deng

Yang

Liu

et al. 2021

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

show abstract

“…In addition, we will take the time and space factors into consideration to improve the algorithm from many aspects, such as privacy [22][23][24][25]. We will also further improve the performance and effectiveness of the algorithm [26][27][28] by combining some new approaches such as Blockchain and Edge Computing [29][30][31][32].…”

Section: Discussionmentioning

confidence: 99%

Service Recommendation with High Accuracy and Diversity

Shengqi

Kou

et al. 2020

Wireless Communications and Mobile Computing

Self Cite

View full text Add to dashboard Cite

In recent years, the number of web services grows explosively. With a large amount of information resources, it is difficult for users to quickly find the services they need. Thus, the design of an effective web service recommendation method has become the key factor to satisfy the requirements of users. However, traditional recommendation methods often tend to pay more attention to the accuracy of the results but ignore the diversity, which may lead to redundancy and overfitting, thus reducing the satisfaction of users. Considering these drawbacks, a novel method called DivMTID is proposed to improve the effectiveness by achieving accurate and diversified recommendations. First, we utilize users’ historical scores of web services to explore the users’ preferences. And we use the TF-IDF algorithm to calculate the weight vector of each web service. Second, we utilize cosine similarity to calculate the similarity between candidate web services and historical web services and we also forecast the ranking scores of candidate web services. At last, a diversification method is used to generate the top- K recommended list for users. And through a case study, we show that DivMTID is an effective, accurate, and diversified web service recommendation method.

show abstract

“…It is more efficient in terms of encryption time than AES algorithm since it requires one iteration to provide the ciphertext. Liu et al [85] investigated the privacy-preserving in dynamic and real-time IoT environments. They proposed two algorithms to protect private data of resource-constrained IoT devices.…”

Section: Methodsmentioning

confidence: 99%

Recent Security Trends in Internet of Things: A Comprehensive Survey

et al. 2021

View full text Add to dashboard Cite

The Internet of Things (IoT) aims to transform everyday physical objects into an interconnected ecosystem with digital data accessible anywhere and anytime. "Things" in IoT are embedded with sensing, processing and actuating capabilities and cooperate in providing smart and innovative services autonomously. The rapid spread of IoT services arises different security vulnerabilities that need to be carefully addressed. Several emerging and promising technologies and techniques are introduced to improve the security of IoT. This paper aims to provide an up-to-date vision of the current research topics related to IoT security. Initially, we introduce common elements and protocols of IoT to demystify the origins of threats in IoT. Then, we propose a taxonomy of IoT attacks and analyze the security vulnerabilities of IoT at different layers. Subsequently, we povide a comparison of recent security schemes based on emerging solutions including fog computing, edge computing, software defined networking (SDN), blockchain, lightweight cryptography, homomorphic and searchable encryption, and machine learning. Finally, security challenges are discussed and future directions are highlighted for future interested researchers.INDEX TERMS Blockchain, edge computing, fog computing, IoT, lightweight cryptography, machine learning, SDN.

show abstract

Privacy Protection Based on Stream Cipher for Spatiotemporal Data in IoT

Cited by 52 publications

References 47 publications

NAAM-MOEA/D-Based Multitarget Firepower Resource Allocation Optimization in Edge Computing

NAAM-MOEA/D-Based Multitarget Firepower Resource Allocation Optimization in Edge Computing

Service Recommendation with High Accuracy and Diversity

Recent Security Trends in Internet of Things: A Comprehensive Survey

Contact Info

Product

Resources

About