http://www.parkjonghyuk.net/lecture/2015-1st-lecture/networksecurity/Paper1.pdf

Security, privacy and trust in Internet of Things

This paper presents a comprehensive literature review on applications of deep reinforcement learning (DRL) in communications and networking. Modern networks, e.g., Internet of Things (IoT) and unmanned aerial vehicle (UAV) networks, become more decentralized and autonomous. In such networks, network entities need to make decisions locally to maximize the network performance under uncertainty of network environment. Reinforcement learning has been efficiently used to enable the network entities to obtain the optimal policy including, e.g., decisions or actions, given their states when the state and action spaces are small. However, in complex and large-scale networks, the state and action spaces are usually large, and the reinforcement learning may not be able to find the optimal policy in reasonable time. Therefore, DRL, a combination of reinforcement learning with deep learning, has been developed to overcome the shortcomings. In this survey, we first give a tutorial of DRL from fundamental concepts to advanced models. Then, we review DRL approaches proposed to address emerging issues in communications and networking. The issues include dynamic network access, data rate control, wireless caching, data offloading, network security, and connectivity preservation which are all important to next generation networks, such as 5G and beyond. Furthermore, we present applications of DRL for traffic routing, resource sharing, and data collection. Finally, we highlight important challenges, open issues, and future research directions of applying DRL.

Applications of Deep Reinforcement Learning in Communications and Networking: A Survey

Mobile Edge Computing, Fog et al.: A Survey and Analysis of Security Threats and Challenges

A survey on trust management for Internet of Things

Internet of Things security

Ad hoc networks are new paradigm of networks offering unrestricted mobility without any underlying infrastructure. The ad hoc networks have salient characteristics that are totally different from conventional networks. These cause extra challenges on security. In an ad hoc network, each node should not trust any peer. However, traditional cryptographic solution is useless against threats from internal compromised nodes. Thus, new mechanisms are needed to provide effective security solution for the ad hoc networks. In this paper, a trust evaluation based security solution is proposed to provide effective security decision on data protection, secure routing and other network activities. Logical and computational trust analysis and evaluation are deployed among network nodes. Each node's evaluation of trust on other nodes should be based on serious study and inference from such trust factors as experience statistics, data value, intrusion detection result, and references of other nodes, as well as node owner's preference and policy. In order to prove the applicability of the proposed solution, authors further present a routing protocol and analyze its security over several active attacks.

/pdf/trust-evaluation-based-security-solution-in-ad-hoc-networks-pl55aqy4i2.pdf

Trust Evaluation Based Security Solution in Ad Hoc Networks

With the great success of the second-generation wireless telephone technology and the third-generation mobile telecommunications technology, and the fast development of the fourth-generation mobile telecommunications technology, the phase of fifth-generation mobile networks or fifth-generation wireless systems 5G is coming. In this article, we indicate the open research issues of 5G security and trust in the context of virtualized networking and software-defined networking. We further propose a framework of security and trust focusing on solving 5G network security issues. The proposed framework applies adaptive trust evaluation and management technologies and sustainable trusted computing technologies to ensure computing platform trust and achieve software-defined network security. It adopts cloud computing to securely deploy various trustworthy security services over the virtualized networks. We analyze that the framework can support and satisfy all security requirements specified in standardization. We also suggest future research work according to the proposed framework and discuss the advantages of our framework in terms of practical deployment. Copyright © 2015 John Wiley & Sons, Ltd.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/sec.1243

A security and trust framework for virtualized networks and software-defined networking

Mobile applications are software packages that can be installed and executed in a mobile device. Which mobile application is trustworthy for a user to purchase, download, install, execute or recommend becomes a crucial issue that impacts its final success. This paper proposes TruBeRepec, a trust-behavior-based reputation and recommender system for mobile applications. We explore a model of trust behavior for mobile applications based on the result of a large-scale user survey. We further develop a number of algorithms that are used to evaluate individual user's trust in a mobile application through trust behavior observation, generate the application's reputation by aggregating individual trust and provide application recommendations based on the correlation of trust behaviors. We show the practical significance of TruBeRepec through simulations and analysis with regard to effectiveness, robustness, and usability, as well as privacy.

http://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=2626&context=sis_research

TruBeRepec: a trust-behavior-based reputation and recommender system for mobile applications

Wireless sensor network (WSN) is widely applied in many fields since its emergence. However, the limited resources of a sensor, especially limited battery life, limited bandwidth and limited processing power, are the main challenges for deploying and operating WSNs. This paper proposes a novel architecture based on cloud computing for wireless sensor network, which can improve the performance of WSN. Based on this architecture, a cloud acts as a virtual sink with many sink points that collect sensing data from sensors. Each sink point is responsible for collecting data from the sensors within a zone. Sensing data are stored and processed in distributed manner in cloud. Our simulation results show that the proposed architecture improves the performance of WSN, e.g., reduced packet transmission error rate, decreased number of end-to-end hops, and improved efficiency of energy consumption.

/pdf/a-novel-architecture-based-on-cloud-computing-for-wireless-58cdjjj3nf.pdf

Peng Zhang

Papers

A survey on trust management for Internet of Things

Trust Evaluation Based Security Solution in Ad Hoc Networks

A security and trust framework for virtualized networks and software-defined networking

TruBeRepec: a trust-behavior-based reputation and recommender system for mobile applications

A Novel Architecture Based on Cloud Computing for Wireless Sensor Network