In the information era,the core business and confidential information of enterprises/organizations is stored in information systems.However,certain malicious inside network users exist hidden inside the organization;t...In the information era,the core business and confidential information of enterprises/organizations is stored in information systems.However,certain malicious inside network users exist hidden inside the organization;these users intentionally or unintentionally misuse the privileges of the organization to obtain sensitive information from the company.The existing approaches on insider threat detection mostly focus on monitoring,detecting,and preventing any malicious behavior generated by users within an organization’s system while ignoring the imbalanced ground-truth insider threat data impact on security.To this end,to be able to detect insider threats more effectively,a data processing tool was developed to process the detected user activity to generate information-use events,and formulated a Data Adjustment(DA)strategy to adjust the weight of the minority and majority samples.Then,an efficient ensemble strategy was utilized,which applied the extreme gradient boosting(XGBoost)model combined with the DA strategy to detect anomalous behavior.The CERT dataset was used for an insider threat to evaluate our approach,which was a real-world dataset with artificially injected insider threat events.The results demonstrated that the proposed approach can effectively detect insider threats,with an accuracy rate of 99.51%and an average recall rate of 98.16%.Compared with other classifiers,the detection performance is improved by 8.76%.展开更多
During the prediction of software defect distribution, the data redundancy caused by the multi-dimensional measurement will lead to the decrease of prediction accuracy. In order to solve this problem, this paper propo...During the prediction of software defect distribution, the data redundancy caused by the multi-dimensional measurement will lead to the decrease of prediction accuracy. In order to solve this problem, this paper proposed a novel software defect prediction model based on neighborhood preserving embedded support vector machine(NPESVM) algorithm. The model uses SVM as the basic classifier of software defect distribution prediction model, and the NPE algorithm is combined to keep the local geometric structure of the data unchanged in the process of dimensionality reduction. The problem of precision reduction of SVM caused by data loss after attribute reduction is avoided. Compared with single SVM and LLE-SVM prediction algorithm, the prediction model in this paper improves the F-measure in aspect of software defect distribution prediction by 3%~4%.展开更多
Language detection models based on system calls suffer from certain false negatives and detection blind spots.Hence,the normal behavior sequences of some malware applications for a short period can become malicious be...Language detection models based on system calls suffer from certain false negatives and detection blind spots.Hence,the normal behavior sequences of some malware applications for a short period can become malicious behavior within a certain time window.To detect such behaviors,we extract a multidimensional time distribution feature matrix on the basis of statistical analysis.This matrix mainly includes multidimensional time distribution features,multidimensional word pair correlation features,and multidimensional word frequency distribution features.A multidimensional time distribution model based on neural networks is built to detect the overall abnormal behavior within a given time window.Experimental evaluation is conducted using the ADFA-LD dataset.Accuracy,precision,and recall are used as the measurement indicators of the model.An accuracy rate of 95.26%and a recall rate of 96.11%are achieved.展开更多
A method was developed on a gas chromatograph coupled to a triple quadrupole mass spectrometer(GC-MS/MS) for trace level determination of polychlorinated dibenzo-p-dioxins/dibenzofurans(PCDD/Fs) and dioxin-like polych...A method was developed on a gas chromatograph coupled to a triple quadrupole mass spectrometer(GC-MS/MS) for trace level determination of polychlorinated dibenzo-p-dioxins/dibenzofurans(PCDD/Fs) and dioxin-like polychlorinated biphenyls(DL-PCBs) in food and feed. The results demonstrated good sensitivity and repeatability for PCDD/Fs and DL-PCBs at an extremely low level(10 pg mL^(-1) for 2,3,7,8-TCDD/F), as well as wide linear response of over 3 or 4 orders of magnitude in concentration ranges; 0.5–200 ng mL^(-1) for PeCDD/F and 0.2–2000 ng mL^(-1) for DL-PCBs. The method detection limits for PCDD/Fs and DL-PCBs were in the range from 0.018–0.17 pg g^(-1) to 0.13–0.36 pg g^(-1), respectively. The performance of the GC-MS/MS for food and feed sample analysis showed high precision and accuracy compared to the high resolution gas chromatograph/high resolution mass spectrometer. The results indicated the feasibility of GC-MS/MS as a confirmatory method for the measurement of PCDD/Fs and DL-PCBs in food and feed as required by European Union legislation.展开更多
Atmospheric concentrations of Dechlorane Plus(DP)were investigated in Taizhou,an electronic-waste(E-waste)dismantling region in East China.Passive air samplers with polyurethane foam(PUF)disks were deployed every thre...Atmospheric concentrations of Dechlorane Plus(DP)were investigated in Taizhou,an electronic-waste(E-waste)dismantling region in East China.Passive air samplers with polyurethane foam(PUF)disks were deployed every three months during the sampling period of September 2009-August 2010.The total DP(syn-and anti-DP)concentrations in air ranged from not detected to 277 pg/m^3,with a mean concentration of 53.9 pg/m^3.A generally declining trend of DP levels was found from the E-waste dismantling region to the peripheral areas.The median values of total DP concentrations in autumn,winter,spring and summer were 52.2,28.8,39.7 and 30.1 pg/m^3,respectively.The seasonal variations of DP concentrations were mainly associated with the intensity of E-waste dismantling activities and meteorological conditions.The mean value of anti-DP fractional abundance(f_(anti))was 0.74±0.08,which was consistent with those in the commercial DP products.This study confirmed a significant emission source related to the distribution of atmospheric DP in the E-waste dismantling area and supplied information for the seasonal variation of DP in the atmosphere.展开更多
Quartz particles are a toxic component of airborne paniculate matter（PM）.Quartz concentrations were analyzed by X-ray diffraction in eighty-seven airborne PM samples collected from three locations in Beijing before,...Quartz particles are a toxic component of airborne paniculate matter（PM）.Quartz concentrations were analyzed by X-ray diffraction in eighty-seven airborne PM samples collected from three locations in Beijing before,during,and after the Asia-Pacific Economic Cooperation（APEC） Leaders＇ Meeting in 2014.The results showed that the mean concentrations of quartz in PM samples from the two urban sites were considerably higher than those from the rural site.The quartz concentrations in samples collected after the APEC meeting,when the pollution restriction lever was lifted,were higher than those in the samples collected before or during the APEC meeting.The quartz concentrations ranged from 0.97 to 13.2 μg/m^3,which were among the highest values amid those reported from other countries.The highest quartz concentration exceeded the Californian Office of Environmental Health Hazard Assessment reference exposure level and was close to the occupational threshold limit values for occupational settings.Moreover,a correlation analysis showed that quartz concentrations were positively correlated with concentrations of pollution parameters PM10,PM2.5,SO2 and NOx,but were negatively correlated with O3 concentration.The results suggest that the airborne quartz particles may potentially pose health risks to the general population of Beijing.展开更多
基金This work was financially supported by“the National Key R&D Program of China”(No.2018YFB0803602)exploration and practice on the education mode for engineering students based on technology,literature and art interdisciplinary integration with the Internet+background(No.022150118004/001)。
文摘In the information era,the core business and confidential information of enterprises/organizations is stored in information systems.However,certain malicious inside network users exist hidden inside the organization;these users intentionally or unintentionally misuse the privileges of the organization to obtain sensitive information from the company.The existing approaches on insider threat detection mostly focus on monitoring,detecting,and preventing any malicious behavior generated by users within an organization’s system while ignoring the imbalanced ground-truth insider threat data impact on security.To this end,to be able to detect insider threats more effectively,a data processing tool was developed to process the detected user activity to generate information-use events,and formulated a Data Adjustment(DA)strategy to adjust the weight of the minority and majority samples.Then,an efficient ensemble strategy was utilized,which applied the extreme gradient boosting(XGBoost)model combined with the DA strategy to detect anomalous behavior.The CERT dataset was used for an insider threat to evaluate our approach,which was a real-world dataset with artificially injected insider threat events.The results demonstrated that the proposed approach can effectively detect insider threats,with an accuracy rate of 99.51%and an average recall rate of 98.16%.Compared with other classifiers,the detection performance is improved by 8.76%.
基金supported by the National Natural Science Foundation of China(Grant No.U1636115)the PAPD fund+1 种基金the CICAEET fundthe Open Foundation of Guizhou Provincial Key Laboratory of Public Big Data(2017BDKFJJ017)
文摘During the prediction of software defect distribution, the data redundancy caused by the multi-dimensional measurement will lead to the decrease of prediction accuracy. In order to solve this problem, this paper proposed a novel software defect prediction model based on neighborhood preserving embedded support vector machine(NPESVM) algorithm. The model uses SVM as the basic classifier of software defect distribution prediction model, and the NPE algorithm is combined to keep the local geometric structure of the data unchanged in the process of dimensionality reduction. The problem of precision reduction of SVM caused by data loss after attribute reduction is avoided. Compared with single SVM and LLE-SVM prediction algorithm, the prediction model in this paper improves the F-measure in aspect of software defect distribution prediction by 3%~4%.
基金supported by the National Key Research and Development Program of China(No.2017YFB0801900).
文摘Language detection models based on system calls suffer from certain false negatives and detection blind spots.Hence,the normal behavior sequences of some malware applications for a short period can become malicious behavior within a certain time window.To detect such behaviors,we extract a multidimensional time distribution feature matrix on the basis of statistical analysis.This matrix mainly includes multidimensional time distribution features,multidimensional word pair correlation features,and multidimensional word frequency distribution features.A multidimensional time distribution model based on neural networks is built to detect the overall abnormal behavior within a given time window.Experimental evaluation is conducted using the ADFA-LD dataset.Accuracy,precision,and recall are used as the measurement indicators of the model.An accuracy rate of 95.26%and a recall rate of 96.11%are achieved.
基金supported by the National Natural Science Foundation of China(21477156,21477155,41276195)Chinese Academy of Sciences(XDB14010100)the National Basic Research Program of China(2015CB453101)
文摘A method was developed on a gas chromatograph coupled to a triple quadrupole mass spectrometer(GC-MS/MS) for trace level determination of polychlorinated dibenzo-p-dioxins/dibenzofurans(PCDD/Fs) and dioxin-like polychlorinated biphenyls(DL-PCBs) in food and feed. The results demonstrated good sensitivity and repeatability for PCDD/Fs and DL-PCBs at an extremely low level(10 pg mL^(-1) for 2,3,7,8-TCDD/F), as well as wide linear response of over 3 or 4 orders of magnitude in concentration ranges; 0.5–200 ng mL^(-1) for PeCDD/F and 0.2–2000 ng mL^(-1) for DL-PCBs. The method detection limits for PCDD/Fs and DL-PCBs were in the range from 0.018–0.17 pg g^(-1) to 0.13–0.36 pg g^(-1), respectively. The performance of the GC-MS/MS for food and feed sample analysis showed high precision and accuracy compared to the high resolution gas chromatograph/high resolution mass spectrometer. The results indicated the feasibility of GC-MS/MS as a confirmatory method for the measurement of PCDD/Fs and DL-PCBs in food and feed as required by European Union legislation.
基金supported by the National Natural Science Foundation of China(21477156,21277165)the National Basic Research Program of China(2015CB453101)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB14010100)
文摘Atmospheric concentrations of Dechlorane Plus(DP)were investigated in Taizhou,an electronic-waste(E-waste)dismantling region in East China.Passive air samplers with polyurethane foam(PUF)disks were deployed every three months during the sampling period of September 2009-August 2010.The total DP(syn-and anti-DP)concentrations in air ranged from not detected to 277 pg/m^3,with a mean concentration of 53.9 pg/m^3.A generally declining trend of DP levels was found from the E-waste dismantling region to the peripheral areas.The median values of total DP concentrations in autumn,winter,spring and summer were 52.2,28.8,39.7 and 30.1 pg/m^3,respectively.The seasonal variations of DP concentrations were mainly associated with the intensity of E-waste dismantling activities and meteorological conditions.The mean value of anti-DP fractional abundance(f_(anti))was 0.74±0.08,which was consistent with those in the commercial DP products.This study confirmed a significant emission source related to the distribution of atmospheric DP in the E-waste dismantling area and supplied information for the seasonal variation of DP in the atmosphere.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (No. XDB14010100)the "One-Three-Five" Strategic Planning program of the Chinese Academy of Sciences (No. YSW2013B01)the National Natural Science Foundation of China (Nos. 21321004, 21307148)
文摘Quartz particles are a toxic component of airborne paniculate matter（PM）.Quartz concentrations were analyzed by X-ray diffraction in eighty-seven airborne PM samples collected from three locations in Beijing before,during,and after the Asia-Pacific Economic Cooperation（APEC） Leaders＇ Meeting in 2014.The results showed that the mean concentrations of quartz in PM samples from the two urban sites were considerably higher than those from the rural site.The quartz concentrations in samples collected after the APEC meeting,when the pollution restriction lever was lifted,were higher than those in the samples collected before or during the APEC meeting.The quartz concentrations ranged from 0.97 to 13.2 μg/m^3,which were among the highest values amid those reported from other countries.The highest quartz concentration exceeded the Californian Office of Environmental Health Hazard Assessment reference exposure level and was close to the occupational threshold limit values for occupational settings.Moreover,a correlation analysis showed that quartz concentrations were positively correlated with concentrations of pollution parameters PM10,PM2.5,SO2 and NOx,but were negatively correlated with O3 concentration.The results suggest that the airborne quartz particles may potentially pose health risks to the general population of Beijing.
