Popular Matching for Security-Enhanced Resource Allocation in Social Internet of Flying Things

Abstract

As the Internet of Things (IoT) is maturing and acquires its social flavor, the Social IoT enables smart devices to build inter-thing social networks without human intervention. As a new form of smart devices, unmanned aerial vehicles (UAVs) are finding their way into IoT applications. The integrated Social Internet of Flying Things (SIoFT) can provide the socialaware UAV-assisted services. However, the broadcast nature of air-to-ground (A2G) channels makes them vulnerable to being eavesdropped by terrestrial malicious users due to their strong line-of-sight (LoS) links. In this paper, we investigate to ensure the security of A2G communications when the location information of multiple potential eavesdroppers cannot be perfectly estimated. Following the "no pain no gain" principle, the terrestrial users who reuse the UAV cellular spectrum will act as friendly jammers to realize "win-win" situation. Hence, joint trajectory design, power control, and channel allocation optimization problem is formulated to maximize the average secrecy rate of UAVs in worst case. In the first stage, we utilize the block coordinate descent method and successive convex optimization method to solve the trajectory design and power control problems in an iterative manner. In the second stage, we convert the user pairing problem into a popular matching problem with externalities. Two distributed algorithms are proposed to maintain the popular matching under dynamics. Moreover, we conduct detailed analysis of the popularity, convergence, and computational complexity. Simulation results demonstrate the superiority of our proposed method in terms of different performance metrics.

The Theoretical Topology and Implementation of Enterprise Social Security in the Digital Age Based on Big Data and Artificial Intelligence

“…Since entering the 21st century, a variety of intelligent technologies have also developed vigorously, especially the wide application of big data analysis and artificial intelligence technology, which has been applied on a large scale in many industries and has been able to solve some practical problems [2]. Therefore, how to combine big data and artificial intelligence technology to realize the iterative upgrading of enterprise social security methods has become the mainstream research direction [3]. At present, although the existing enterprise social security system has many high relevance application rules, there are still many deficiencies, such as inability to ensure the comprehensiveness of enterprise employee social security and low processing efficiency of enterprise employee social security [4].…”

Energy and spectral efficient resource allocation in 5G HetNet using optimized deep bi‐BRLSTM model

“…Here, the exploitation of diversity takes place among different interfaces for an every MT. The final one is the security based RA in multi technology in HetNet 17 . The optimization objectives includes SE, EE and cross layer design.…”

“…The final one is the security based RA in multi technology in HetNet. 17 The optimization objectives includes SE, EE and cross layer design. Various sub channel and power allocation algorithms are developed to maximize the objectives in HetNet.…”

Internet of Flying Things security: A systematic review

“…IoFT integrates Unmanned Aerial Vehicles (UAVs) with the Internet of Things (IoT) to serve a variety of applications 1 . On the other hand, recently, some researchers have started to study the integration of Flying Adhoc Network (FANET) into IoT, leading to the IoFT 2 . In IoFT, drones can broaden the boundaries of their missions, expand connectivity, improve collaboration and cooperation between systems, and provide updated data 3 .…”