Low-rate DDoS attacks detection method using data compression and behavior divergence measurement

2021 ◽  
Vol 100 ◽  
pp. 102107
Author(s):  
Xinqian Liu ◽  
Jiadong Ren ◽  
Haitao He ◽  
Qian Wang ◽  
Chen Song
Keyword(s):  
Data Compression ◽  
Detection Method ◽  
Ddos Attacks ◽  
Using Data ◽  
And Behavior ◽  
Low Rate

Influence of Confucian culture on entrepreneurial decision making using data from China's floating population

2020 ◽  
Vol 48 (7) ◽  
pp. 1-12
Author(s):  
Ran Xiong ◽  
Ping Wei
Keyword(s):  
Decision Making ◽  
Floating Population ◽  
Positive Role ◽  
Confucian Culture ◽  
Chinese Nation ◽  
Using Data ◽  
Entrepreneurial Decision ◽  
And Behavior ◽  
The Relationship

Confucian culture has had a deep-rooted influence on Chinese thinking and behavior for more than 2,000 years. With a manually created Confucian culture database and the 2017 China floating population survey, we used empirical analysis to test the relationship between Confucian culture and individual entrepreneurial choice using data obtained from China's floating population. After using the presence and number of Confucian schools and temples, and of chaste women as instrumental variables to counteract problems of endogeneity, we found that Confucian culture had a significant role in promoting individuals' entrepreneurial decision making among China's floating population. The results showed that, compared with those from areas of China not strongly influenced by Confucian culture, individuals from areas that are strongly influenced by Confucian culture were more likely to choose entrepreneurship as their occupation choice. Our findings reveal cultural factors that affect individual entrepreneurial behavior, and also illustrate the positive role of Confucianism as a representative of the typical cultures of the Chinese nation in the 21st century.

scholarly journals Testing Common Knowledge: Are Northern Europeans and Millennials More Concerned about the Environment?

2020 ◽  
Vol 13 (1) ◽  
pp. 45
Author(s):  
Cristina Gómez-Román ◽  
Maria Luisa Lima ◽  
Gloria Seoane ◽  
Mónica Alzate ◽  
Marcos Dono ◽  
...  
Keyword(s):  
Generation X ◽  
Common Knowledge ◽  
European Social Survey ◽  
Common Belief ◽  
Environmentally Conscious ◽  
Personal Norms ◽  
Northern European ◽  
Using Data ◽  
And Behavior ◽  
North And South

This study explores whether there are differences in several environmental dimensions, when the European Region and Generation cohort are considered. In doing so, this study compares millennials in North and South Europe with members of Generation X in three environmental dimensions: attitudes, personal norms, and behavior. Using data from the European Social Survey (n = 6.216), the researchers tested the hypothesis that Northern Europeans and millennials have more pro-environmental standing than southerners and Generation Xers. The findings challenge the common belief that millennials are more committed to being environmentally conscious, showing that many millennials do not feel responsible for their climate footprint, nor do they behave in a way that shows more concern than previous generations to improve their environmental performance. Furthermore, contrary to expectations, Northern European participants are not the most committed, in all environmental dimensions, compared to Southern Europeans.

scholarly journals Adaptive DDoS Attack Detection Method Based on Multiple-Kernel Learning

2018 ◽  
Vol 2018 ◽  
pp. 1-19 ◽  
Author(s):  
Jieren Cheng ◽  
Chen Zhang ◽  
Xiangyan Tang ◽  
Victor S. Sheng ◽  
Zhe Dong ◽  
...  
Keyword(s):  
Detection Method ◽  
Denial Of Service ◽  
Multiple Kernel Learning ◽  
Attack Detection ◽  
Kernel Learning ◽  
Economic Losses ◽  
Ddos Attacks ◽  
Ddos Attack ◽  
Multiple Kernel ◽  
Ddos Attack Detection

Distributed denial of service (DDoS) attacks has caused huge economic losses to society. They have become one of the main threats to Internet security. Most of the current detection methods based on a single feature and fixed model parameters cannot effectively detect early DDoS attacks in cloud and big data environment. In this paper, an adaptive DDoS attack detection method (ADADM) based on multiple-kernel learning (MKL) is proposed. Based on the burstiness of DDoS attack flow, the distribution of addresses, and the interactivity of communication, we define five features to describe the network flow characteristic. Based on the ensemble learning framework, the weight of each dimension is adaptively adjusted by increasing the interclass mean with a gradient ascent and reducing the intraclass variance with a gradient descent, and the classifier is established to identify an early DDoS attack by training simple multiple-kernel learning (SMKL) models with two characteristics including interclass mean squared difference growth (M-SMKL) and intraclass variance descent (S-SMKL). The sliding window mechanism is used to coordinate the S-SMKL and M-SMKL to detect the early DDoS attack. The experimental results indicate that this method can detect DDoS attacks early and accurately.

scholarly journals The reduction of Crosstalk in VLSI due to parallel bus structure using Data Compression Bus Encoding technique implemented on Artix 7 FPGA Architecture

2021 ◽  
Vol 9 (1) ◽  
pp. 456-460
Author(s):  
Syamala Yarlagadda, Srilakshmi Kaza, Anil chowdary Tummala, E Vijaya Babu, R. Prabhakar
Keyword(s):  
Power Consumption ◽  
Data Compression ◽  
Huge Amount ◽  
Significant Time ◽  
Planar Structures ◽  
Fpga Architecture ◽  
Bus Encoding ◽  
Bus Structure ◽  
Using Data ◽  
Encoding Method

In this work, a bus encoding method is proposed that reduces the effect of crosstalk. The crosstalk usually occurs when the data is in parallel communicated. In planar structures, the crosstalk effect is large due to the usage of parallel communication and wide data patterns. In bus technique, the huge amount of wires is laid in equal over a significant time. One way to reduce crosstalk without changing the parallel communicating data lines is to reduce the wideband data patterns so as to reduce the power utilization. The proposed encoding method can minimize the crosstalk by reducing wide data patterns without degrading the performance. The architecture is implemented on Artix 7 FPGA at a 28nm technology node. The simulation is done using the HDL tool and the results are compared with the existing FPGA architecture. With the proposed method, the wire density and the power consumption are reduced by 57.4% and 50% respectively as compared with existing 45 nm technologies.

scholarly journals SOFT COMPUTING BASED AUTONOMOUS LOW RATE DDOS ATTACK DETECTION AND SECURITY FOR CLOUD COMPUTING

2019 ◽  
Vol 2019 (2) ◽  
pp. 80-90 ◽  
Author(s):  
Mugunthan S. R.
Keyword(s):  
Cloud Computing ◽  
Soft Computing ◽  
High Speed ◽  
Denial Of Service ◽  
Attack Detection ◽  
Ddos Attacks ◽  
Counter Measures ◽  
Cloud Architecture ◽  
Ddos Attack Detection ◽  
Low Rate

The fundamental advantage of the cloud environment is its instant scalability in rendering the service according to the various demands. The recent technological growth in the cloud computing makes it accessible to people from everywhere at any time. Multitudes of user utilizes the cloud platform for their various needs and store their complete details that are personnel as well as confidential in the cloud architecture. The storage of the confidential information makes the cloud architecture attractive to its hackers, who aim in misusing the confidential/secret information’s. The misuse of the services and the resources of the cloud architecture has become a common issue in the day to day usage due to the DDOS (distributed denial of service) attacks. The DDOS attacks are highly mature and continue to grow at a high speed making the detecting and the counter measures a challenging task. So the paper uses the soft computing based autonomous detection for the Low rate-DDOS attacks in the cloud architecture. The proposed method utilizes the hidden Markov Model for observing the flow in the network and the Random forest in classifying the detected attacks from the normal flow. The proffered method is evaluated to measure the performance improvement attained in terms of the Recall, Precision, specificity, accuracy and F-measure.

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