Cyber-security and reinforcement learning—a brief survey
AMK Adawadkar, N Kulkarni - Engineering Applications of Artificial …, 2022 - Elsevier
This paper presents a comprehensive literature review on Reinforcement Learning (RL)
techniques used in Intrusion Detection Systems (IDS), Intrusion Prevention Systems (IPS) …
techniques used in Intrusion Detection Systems (IDS), Intrusion Prevention Systems (IPS) …
A bibliometric analysis of blockchain technology research using VOSviewer
Blockchain technology remains popular for several reasons. The main one is that it has
facilitated the rise of digital currencies over the past several years and many other uses of …
facilitated the rise of digital currencies over the past several years and many other uses of …
New challenges in reinforcement learning: a survey of security and privacy
Reinforcement learning is one of the most important branches of AI. Due to its capacity for
self-adaption and decision-making in dynamic environments, reinforcement learning has …
self-adaption and decision-making in dynamic environments, reinforcement learning has …
GPDS: A multi-agent deep reinforcement learning game for anti-jamming secure computing in MEC network
Abstract The openness of Mobile Edge Computing (MEC) networks makes them vulnerable
to interference attacks by malicious jammers, which endangers the communication quality of …
to interference attacks by malicious jammers, which endangers the communication quality of …
DLFTI: A deep learning based fast truth inference mechanism for distributed spatiotemporal data in mobile crowd sensing
Abstract The paradigm of Mobile Crowd Sensing (MCS) allows for numerous applications
with distributed spatiotemporal data, where great attention is drawn to the fundamental …
with distributed spatiotemporal data, where great attention is drawn to the fundamental …
DTD: An intelligent data and bid dual truth discovery scheme for MCS in IIoT
Mobile crowdsensing (MCS) is a crucial component in the Industrial Internet of Things (IIoT),
mainly due to its role in collecting data and enhancing applications. Nonetheless, it faces …
mainly due to its role in collecting data and enhancing applications. Nonetheless, it faces …
SCTD: A spatiotemporal correlation truth discovery scheme for security management of data platform
The continuous development of mobile sensing devices enables them to quickly perceive a
large amount of data, forming a promising mobile crowd sensing (MCS) platform for large …
large amount of data, forming a promising mobile crowd sensing (MCS) platform for large …
TVD-RA: A truthful data value discovery based reverse auction incentive system for mobile crowd sensing
Emerging crowdsensing paradigm enables a large number of sensing applications, where
much attention is drawn to the fundamental problems for maximizing the system utility and …
much attention is drawn to the fundamental problems for maximizing the system utility and …
Differentially private crowdsourcing with the public and private blockchain
As a result of the rapid development of Internet of Things (IoT) systems, an increasing
number of academics are focusing on finding new applications for IoT systems. For IoT …
number of academics are focusing on finding new applications for IoT systems. For IoT …
A decentralized trust inference approach with intelligence to improve data collection quality for mobile crowd sensing
Abstract Mobile Crowd Sensing (MCS) has been recognized as a promising param to
construct numerous applications by employing enormous workers to perceive and collect …
construct numerous applications by employing enormous workers to perceive and collect …