Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries,especially in light of the growing number of cybersecurity threats.A major and ...Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries,especially in light of the growing number of cybersecurity threats.A major and everpresent threat is Ransomware-as-a-Service(RaaS)assaults,which enable even individuals with minimal technical knowledge to conduct ransomware operations.This study provides a new approach for RaaS attack detection which uses an ensemble of deep learning models.For this purpose,the network intrusion detection dataset“UNSWNB15”from the Intelligent Security Group of the University of New South Wales,Australia is analyzed.In the initial phase,the rectified linear unit-,scaled exponential linear unit-,and exponential linear unit-based three separate Multi-Layer Perceptron(MLP)models are developed.Later,using the combined predictive power of these three MLPs,the RansoDetect Fusion ensemble model is introduced in the suggested methodology.The proposed ensemble technique outperforms previous studieswith impressive performance metrics results,including 98.79%accuracy and recall,98.85%precision,and 98.80%F1-score.The empirical results of this study validate the ensemble model’s ability to improve cybersecurity defenses by showing that it outperforms individual MLPmodels.In expanding the field of cybersecurity strategy,this research highlights the significance of combined deep learning models in strengthening intrusion detection systems against sophisticated cyber threats.展开更多
Background Essential hypertension(EH)is a complex polygenic genetic disease,which is the result of the interaction of multiple genetic factors,environmental factors,and risk factors.The susceptibility of inherited gen...Background Essential hypertension(EH)is a complex polygenic genetic disease,which is the result of the interaction of multiple genetic factors,environmental factors,and risk factors.The susceptibility of inherited genes is an important risk factor for EH,and pathogenic genes and susceptibility loci can promote EH formation.It has been found that renin-angiotensin angiotensin aldosterone system(RAAS)genes are involved in most physiological regulation in humans,especially with EH.Its gene polymorphisms and EH susceptibility are current research hotspots.Therefore,this article reviewed the research on the correlation between angiotensinogen(AGT),angiotensin-converting enzyme(ACE),angiotensin II.receptor type 1(AGTR1),aldosterone synthetase(CYP11B2),and beta 1-adrenergic receptor(ADRB1)gene with EH,respectively.[S Chin J Cardiol 2024;25(3):193-199]展开更多
基金the Deanship of Scientific Research,Najran University,Kingdom of Saudi Arabia,for funding this work under the Research Groups Funding Program Grant Code Number(NU/RG/SERC/12/43).
文摘Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries,especially in light of the growing number of cybersecurity threats.A major and everpresent threat is Ransomware-as-a-Service(RaaS)assaults,which enable even individuals with minimal technical knowledge to conduct ransomware operations.This study provides a new approach for RaaS attack detection which uses an ensemble of deep learning models.For this purpose,the network intrusion detection dataset“UNSWNB15”from the Intelligent Security Group of the University of New South Wales,Australia is analyzed.In the initial phase,the rectified linear unit-,scaled exponential linear unit-,and exponential linear unit-based three separate Multi-Layer Perceptron(MLP)models are developed.Later,using the combined predictive power of these three MLPs,the RansoDetect Fusion ensemble model is introduced in the suggested methodology.The proposed ensemble technique outperforms previous studieswith impressive performance metrics results,including 98.79%accuracy and recall,98.85%precision,and 98.80%F1-score.The empirical results of this study validate the ensemble model’s ability to improve cybersecurity defenses by showing that it outperforms individual MLPmodels.In expanding the field of cybersecurity strategy,this research highlights the significance of combined deep learning models in strengthening intrusion detection systems against sophisticated cyber threats.
基金supported by the Scientific Research Project of Heilongjiang Provincial Department of Health(No.20230303010126)the Excellent Scientific Research Team Project of the First Affiliated Hospital of Jiamusi University(No.202302)。
文摘Background Essential hypertension(EH)is a complex polygenic genetic disease,which is the result of the interaction of multiple genetic factors,environmental factors,and risk factors.The susceptibility of inherited genes is an important risk factor for EH,and pathogenic genes and susceptibility loci can promote EH formation.It has been found that renin-angiotensin angiotensin aldosterone system(RAAS)genes are involved in most physiological regulation in humans,especially with EH.Its gene polymorphisms and EH susceptibility are current research hotspots.Therefore,this article reviewed the research on the correlation between angiotensinogen(AGT),angiotensin-converting enzyme(ACE),angiotensin II.receptor type 1(AGTR1),aldosterone synthetase(CYP11B2),and beta 1-adrenergic receptor(ADRB1)gene with EH,respectively.[S Chin J Cardiol 2024;25(3):193-199]
