Advancing 5G Network Applications Lifecycle Security:An ML-Driven Approach

As 5th Generation(5G)and Beyond 5G(B5G)networks become increasingly prevalent,ensuring not only networksecurity but also the security and reliability of the applications,the so-called network applications,becomesof paramount importance.This paper introduces a novel integrated model architecture,combining a networkapplication validation framework with an AI-driven reactive system to enhance security in real-time.The proposedmodel leverages machine learning(ML)and artificial intelligence(AI)to dynamically monitor and respond tosecurity threats,effectively mitigating potential risks before they impact the network infrastructure.This dualapproach not only validates the functionality and performance of network applications before their real deploymentbut also enhances the network’s ability to adapt and respond to threats as they arise.The implementation ofthis model,in the shape of an architecture deployed in two distinct sites,demonstrates its practical viability andeffectiveness.Integrating application validation with proactive threat detection and response,the proposed modeladdresses critical security challenges unique to 5G infrastructures.This paper details the model,architecture’sdesign,implementation,and evaluation of this solution,illustrating its potential to improve network securitymanagement in 5G environments significantly.Our findings highlight the architecture’s capability to ensure boththe operational integrity of network applications and the security of the underlying infrastructure,presenting asignificant advancement in network security.

Current trends in access to treatment for hepatitis B in immigrants vs non-immigrants

Background:Universal vaccination for hepatitis B virus(HBV)and migratory movements have changed the demographic characteristics of this disease in Spain and in Europe.Therefore,we evaluated the characteristics of the disease and the possible differences according to origin(immigrants vs non-immigrants)and access to treatment.Methods:This is a multicenter cross-sectional study(June 2014 to May 2015)in which outpatients with a positive HBsAg were seen and followed in four Hepatology units.Demographic and clinical data and indication and access to treatment were collected in two different regions of Catalonia(Spain)where there are no barriers to treatment due to a comprehensive coverage under the National Health System.Results:A total of 951 patients were evaluated(48.1%men).Of these,46.6%were immigrants(58.7%of them were born in Africa)and were significantly younger compared to non-immigrants.The proportions of patients with alcohol consumption,being overweight,and other indicators of metabolic co-morbidities were significantly higher in non-immigrants.Among the 937 patients receiving HBeAg examination,91.7%were HBeAg-negative.Chronic HBeAg-positive infection was significantly higher in immigrants(3.9%vs 0.6%,P=0.001)and chronic HBeAg-negative hepatitis was higher non-immigrants(31.7%vs 21.4%,P<0.001).Not only was the proportion of patients who met treatment criteria significantly higher among nonimmigrants(38.4%vs 29.2%,P=0.003),but also the proportion of those with indication of effectively receiving therapy at the time of data collection(83.2%vs 57.8%,P<0.001).Conclusions:The immigrant population with HBV is younger and has a lower prevalence of metabolic co-morbidities and a higher frequency of chronic HBeAg infection.Despite having access to care and an indication for treatment,some do not get adequately treated due to several factors including local adaptation that precludes access to treatment.