Physical Layer Authentication Using Ensemble Learning Technique in Wireless Communications

Cyber-physical wireless systems have surfaced as an important data communication and networking research area.It is an emerging discipline that allows effective monitoring and efficient real-time communication between the cyber and physical worlds by embedding computer software and integrating communication and networking technologies.Due to their high reliability,sensitivity and connectivity,their security requirements are more comparable to the Internet as they are prone to various security threats such as eavesdropping,spoofing,botnets,man-in-the-middle attack,denial of service(DoS)and distributed denial of service(DDoS)and impersonation.Existing methods use physical layer authentication(PLA),themost promising solution to detect cyber-attacks.Still,the cyber-physical systems(CPS)have relatively large computational requirements and require more communication resources,thus making it impossible to achieve a low latency target.These methods perform well but only in stationary scenarios.We have extracted the relevant features from the channel matrices using discrete wavelet transformation to improve the computational time required for data processing by considering mobile scenarios.The features are fed to ensemble learning algorithms,such as AdaBoost,LogitBoost and Gentle Boost,to classify data.The authentication of the received signal is considered a binary classification problem.The transmitted data is labeled as legitimate information,and spoofing data is illegitimate information.Therefore,this paper proposes a threshold-free PLA approach that uses machine learning algorithms to protect critical data from spoofing attacks.It detects the malicious data packets in stationary scenarios and detects them with high accuracy when receivers are mobile.The proposed model achieves better performance than the existing approaches in terms of accuracy and computational time by decreasing the processing time.

Same day discharge after structural heart disease interventions in the era of the coronavirus-19 pandemic and beyond

With recent advancements in imaging modalities and techniques and increased recognition of the long-term impact of several structural heart disease interventions,the number of procedures has significantly increased.With the increase in procedures,also comes an increase in cost.In view of this,efficient and cost-effective methods to facilitate and manage structural heart disease interventions are a necessity.Same-day discharge(SDD)after invasive cardiac procedures improves resource utilization and patient satisfaction.SDD in appropriately selected patients has become the standard of care for some invasive cardiac procedures such as percutaneous coronary interventions.This is not the case for the majority of structural heart procedures.With the coronavirus disease 2019 pandemic,safely reducing the duration of time spent within the hospital to prevent unnecessary exposure to pathogens has become a priority.In light of this,it is prudent to assess the feasibility of SDD in several structural heart procedures.In this review we highlight the feasibility of SDD in a carefully selected population,by reviewing and summarizing studies on SDD among patients undergoing left atrial appendage occlusion,patent foramen ovale/atrial septal defect closure,Mitra-clip,and trans-catheter aortic valve replacement procedures.