Unknown DDoS Attack Detection with Fuzzy C-Means Clustering and Spatial Location Constraint Prototype Loss

Since its inception,the Internet has been rapidly evolving.With the advancement of science and technology and the explosive growth of the population,the demand for the Internet has been on the rise.Many applications in education,healthcare,entertainment,science,and more are being increasingly deployed based on the internet.Concurrently,malicious threats on the internet are on the rise as well.Distributed Denial of Service(DDoS)attacks are among the most common and dangerous threats on the internet today.The scale and complexity of DDoS attacks are constantly growing.Intrusion Detection Systems(IDS)have been deployed and have demonstrated their effectiveness in defense against those threats.In addition,the research of Machine Learning(ML)and Deep Learning(DL)in IDS has gained effective results and significant attention.However,one of the challenges when applying ML and DL techniques in intrusion detection is the identification of unknown attacks.These attacks,which are not encountered during the system’s training,can lead to misclassification with significant errors.In this research,we focused on addressing the issue of Unknown Attack Detection,combining two methods:Spatial Location Constraint Prototype Loss(SLCPL)and Fuzzy C-Means(FCM).With the proposed method,we achieved promising results compared to traditional methods.The proposed method demonstrates a very high accuracy of up to 99.8%with a low false positive rate for known attacks on the Intrusion Detection Evaluation Dataset(CICIDS2017)dataset.Particularly,the accuracy is also very high,reaching 99.7%,and the precision goes up to 99.9%for unknown DDoS attacks on the DDoS Evaluation Dataset(CICDDoS2019)dataset.The success of the proposed method is due to the combination of SLCPL,an advanced Open-Set Recognition(OSR)technique,and FCM,a traditional yet highly applicable clustering technique.This has yielded a novel method in the field of unknown attack detection.This further expands the trend of applying DL and ML techniques in the development of intrusion detection systems and cybersecurity.Finally,implementing the proposed method in real-world systems can enhance the security capabilities against increasingly complex threats on computer networks.

An evaluation and query algorithm for the influence of spatial location based on RkNN

This paper is devoted to the investigation of the evaluation and query algorithm problem for the influence of spatial location based on RkNN(reverse k nearest neighbor).On the one hand,an object can make contribution to multiple locations.However,for the existing measures for evaluating the influence of spatial location,an object only makes contribution to one location,and its influence is usually measured by the number of spatial objects in the region.In this case,a new measure for evaluating the influence of spatial location based on the RkNN is proposed.Since the weight of the contribution is determined by the distance between the object and the location,the influence weight definition is given,which meets the actual applications.On the other hand,a query algorithm for the influence of spatial location is introduced based on the proposed measure.Firstly,an algorithm named INCH(INtersection’s Convex Hull)is applied to get candidate regions,where all objects are candidates.Then,kNN and Range-k are used to refine results.Then,according to the proposed measure,the weights of objects in RkNN results are computed,and the influence of the location is accumulated.The experimental results on the real data show that the optimized algorithms outperform the basic algorithm on efficiency.In addition,in order to provide the best customer service in the location problem and make the best use of all infrastructures,a location algorithm with the query is presented based on RkNN.The influence of each facility is calculated in the location program and the equilibrium coefficient is used to evaluate the reasonability of the location in the paper.The smaller the equilibrium coefficient is,the more reasonability the program is.The actual application shows that the location based on influence makes the location algorithm more reasonable and available.

Industrial Carbon Emission Distribution and Regional Joint Emission Reduction:A Case Study of Cities in the Pearl River Basin,China

China’s low-carbon development path will make significant contributions to achieving global sustainable development goals.Due to the diverse natural and economic conditions across different regions in China,there exists an imbalance in the distribution of car-bon emissions.Therefore,regional cooperation serves as an effective means to attain low-carbon development.This study examined the pattern of carbon emissions and proposed a potential joint emission reduction strategy by utilizing the industrial carbon emission intens-ity(ICEI)as a crucial factor.We utilized social network analysis and Local Indicators of Spatial Association(LISA)space-time trans-ition matrix to investigate the spatiotemporal connections and discrepancies of ICEI in the cities of the Pearl River Basin(PRB),China from 2010 to 2020.The primary drivers of the ICEI were determined through geographical detectors and multi-scale geographically weighted regression.The results were as follows:1)the overall ICEI in the Pearl River Basin is showing a downward trend,and there is a significant spatial imbalance.2)There are numerous network connections between cities regarding the ICEI,but the network structure is relatively fragile and unstable.3)Economically developed cities such as Guangzhou,Foshan,and Dongguan are in the center of the network while playing an intermediary role.4)Energy consumption,industrialization,per capita GDP,urbanization,science and techno-logy,and productivity are found to be the most influential variables in the spatial differentiation of ICEI,and their combination in-creased the explanatory power of the geographic variation of ICEI.Finally,through the analysis of differences and connections in urban carbon emissions under different economic levels and ICEI,the study suggests joint carbon reduction strategies,which are centered on carbon transfer,financial support,and technological assistance among cities.

Spatial heterogeneity of lake eutrophication caused by physiogeographic conditions:An analysis of 143 lakes in China

In order to identify the effect of geographic characteristics on the variations of nutrient concentrations and the utilization efficiency of nutrients by phytoplankton, data from 143 lakes, from 2008 to 2010, including three very different types of topography, i.e., the first topography ladder（FTL）, second topography ladder（STL）, and third topography ladder（TTL）, were statistically analyzed. Lakes in the FTL and STL, located at high elevation（above1000 m） and low longitudes（lower than 105° E）, were sporadically oligotrophic, whereas lakes in the TTL were almost all mesotrophic and eutrophic. The trophic level index（TLI）became higher with the rise of longitude. Two turning points（5 and 15°C） on the curve of TLI as function of the average annual temperature（AAT） corresponded with the AAT in different lake regions in the STL and TTL. Because the responses of TLI to AAT differ significantly, there were variations of nutrient and algal biomass concentrations in different lake regions in the same type of topography ladder. According to the differences in utilization efficiency of total nitrogen or total phosphorus by phytoplankton, China could be partitioned into six lake regions. Scientific nutrient criteria for each lake region shall be established considering these differences in China.

Uneven Distribution of Primary and Middle Schools:A Case Study of Changchun,China

Providing further knowledge to and refinement of public facility location theory,this paper focuses on the distribution of basic educational facilities in China.The aim towards an equilibrium in the distribution of education resources has captured widespread attention in recent years.The basis of an education equilibrium is the balanced distribution of teaching facilities.Using the spatial analysis function of ArcGIS,this article discusses the evolution characteristics of education equilibrium and explores its dynamics with reference to primary and middle schools in Changchun City,Jilin Province from 2007 to 2013.The study found the spatial distribution of primary and middle schools in Changchun was uneven and the characteristic of close internal but sparse external has not changed.Low-level equilibrium of primary and middle schools in Changchun has been basically realized,but high-level equilibrium is far from being realized.Although there has been a trend towards suburbanization of these schools in recent years,the high entrance threshold has determined that high-quality school opportunity(schools with high-level resource allocation)has not increased for people.The spatial distribution of primary and middle schools is related to the factors of population,real estate,transportation and the education system itself.Education space,living space,and traffic space all interact and together affect urban spatial structure.