With the introduction of 5G technology,the application of Internet of Things(IoT)devices is expanding to various industrial fields.However,introducing a robust,lightweight,low-cost,and low-power security solution to t...With the introduction of 5G technology,the application of Internet of Things(IoT)devices is expanding to various industrial fields.However,introducing a robust,lightweight,low-cost,and low-power security solution to the IoT environment is challenging.Therefore,this study proposes two methods using a data compression technique to detect malicious traffic efficiently and accurately for a secure IoT environment.The first method,compressed sensing and learning(CSL),compresses an event log in a bitmap format to quickly detect attacks.Then,the attack log is detected using a machine-learning classification model.The second method,precise re-learning after CSL(Ra-CSL),comprises a two-step training.It uses CSL as the 1st step analyzer,and the 2nd step analyzer is applied using the original dataset for a log that is detected as an attack in the 1st step analyzer.In the experiment,the bitmap rule was set based on the boundary value,which was 99.6%true positive on average for the attack and benign data found by analyzing the training data.Experimental results showed that the CSL was effective in reducing the training and detection time,and Ra-CSL was effective in increasing the detection rate.According to the experimental results,the data compression technique reduced the memory size by up to 20%and the training and detection times by 67%when compared with the conventional technique.In addition,the proposed technique improves the detection accuracy;the Naive Bayes model with the highest performance showed a detection rate of approximately 99%.展开更多
Neuro-oxidative stress mediated by reactive oxygen and nitrogen species has been widely implicated in the pathogenesis of Parkinson's disease(PD).Polydeoxyribonucleotide(PDRN),a DNA-derived biopolymer with reporte...Neuro-oxidative stress mediated by reactive oxygen and nitrogen species has been widely implicated in the pathogenesis of Parkinson's disease(PD).Polydeoxyribonucleotide(PDRN),a DNA-derived biopolymer with reported anti-inflammatory properties,has not been fully explored in the context of PD.In this study,PDRN purified from heat-inactivated Enterococcus faecium FBL1(HEF PDRN)was structurally characterized by electrophoresis and Fourier transform infrared spectroscopy.Its cytoprotective effects were evaluated in MPTPinduced SH-SY5Y and C2C12 cells,and its in vivo effects were examined in an MPTP-induced PD mouse model using behavioral assays,histological analysis,transcriptomics,and molecular profiling.HEF PDRN treatment was associated with improved motor performance in rotarod,grip strength,and wire-hanging tests,as well as reduced immobility in the forced swim test.Histological and immunohistochemical analyses indicated attenuation of MPTP-induced muscle damage,preservation of dopaminergic neurons,and reducedα-synuclein aggregation.Transcriptomic analysis revealed attenuation of MPTP-induced suppression of neuroprotective(Park7,and Sqstm1),myogenic(Myf5,MyoG,and Myh1),and osteogenic-associated(Bmp2,Runx2,and Wnt5b)gene expression,with enrichment of Wnt/β-catenin and BMP/SMAD signaling pathways.These effects were accompanied by modulation of MAPK signaling and activation of the adenosine A2A receptor,together with changes inβ-catenin levels.Overall,HEF PDRN may represent a food fermentation-derived bioactive compound associated with antioxidant and anti-inflammatory signaling responses,along with modulation of MAPKmediated BMP/SMAD/Wnt pathways,under neuro-oxidative stress.These findings suggest its potential relevance for the development of functional food ingredients targeting neuroprotective and neuromuscularassociated responses within an acute neurotoxicity model.展开更多
基金supported by a Korea Institute for Advancement of Technology(KIAT)Grant funded by theKorean Government(MOTIE)(P0008703,The Competency Development Program for Industry Specialists)the MSIT under the ICAN(ICT Challenge and Advanced Network ofHRD)program(No.IITP-2022-RS-2022-00156310)supervised by the Institute of Information Communication Technology Planning and Evaluation(IITP).
文摘With the introduction of 5G technology,the application of Internet of Things(IoT)devices is expanding to various industrial fields.However,introducing a robust,lightweight,low-cost,and low-power security solution to the IoT environment is challenging.Therefore,this study proposes two methods using a data compression technique to detect malicious traffic efficiently and accurately for a secure IoT environment.The first method,compressed sensing and learning(CSL),compresses an event log in a bitmap format to quickly detect attacks.Then,the attack log is detected using a machine-learning classification model.The second method,precise re-learning after CSL(Ra-CSL),comprises a two-step training.It uses CSL as the 1st step analyzer,and the 2nd step analyzer is applied using the original dataset for a log that is detected as an attack in the 1st step analyzer.In the experiment,the bitmap rule was set based on the boundary value,which was 99.6%true positive on average for the attack and benign data found by analyzing the training data.Experimental results showed that the CSL was effective in reducing the training and detection time,and Ra-CSL was effective in increasing the detection rate.According to the experimental results,the data compression technique reduced the memory size by up to 20%and the training and detection times by 67%when compared with the conventional technique.In addition,the proposed technique improves the detection accuracy;the Naive Bayes model with the highest performance showed a detection rate of approximately 99%.
基金supported by the National Research Foundation of the Republic of Korea(NRF)grant funded by the Republic of the Korean Government(MSIT)(RS-2023-NR077274).
文摘Neuro-oxidative stress mediated by reactive oxygen and nitrogen species has been widely implicated in the pathogenesis of Parkinson's disease(PD).Polydeoxyribonucleotide(PDRN),a DNA-derived biopolymer with reported anti-inflammatory properties,has not been fully explored in the context of PD.In this study,PDRN purified from heat-inactivated Enterococcus faecium FBL1(HEF PDRN)was structurally characterized by electrophoresis and Fourier transform infrared spectroscopy.Its cytoprotective effects were evaluated in MPTPinduced SH-SY5Y and C2C12 cells,and its in vivo effects were examined in an MPTP-induced PD mouse model using behavioral assays,histological analysis,transcriptomics,and molecular profiling.HEF PDRN treatment was associated with improved motor performance in rotarod,grip strength,and wire-hanging tests,as well as reduced immobility in the forced swim test.Histological and immunohistochemical analyses indicated attenuation of MPTP-induced muscle damage,preservation of dopaminergic neurons,and reducedα-synuclein aggregation.Transcriptomic analysis revealed attenuation of MPTP-induced suppression of neuroprotective(Park7,and Sqstm1),myogenic(Myf5,MyoG,and Myh1),and osteogenic-associated(Bmp2,Runx2,and Wnt5b)gene expression,with enrichment of Wnt/β-catenin and BMP/SMAD signaling pathways.These effects were accompanied by modulation of MAPK signaling and activation of the adenosine A2A receptor,together with changes inβ-catenin levels.Overall,HEF PDRN may represent a food fermentation-derived bioactive compound associated with antioxidant and anti-inflammatory signaling responses,along with modulation of MAPKmediated BMP/SMAD/Wnt pathways,under neuro-oxidative stress.These findings suggest its potential relevance for the development of functional food ingredients targeting neuroprotective and neuromuscularassociated responses within an acute neurotoxicity model.
