coherence detection
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2021 ◽  
pp. 2100040
Author(s):  
Kang‐Da Wu ◽  
Alexander Streltsov ◽  
Bartosz Regula ◽  
Guo‐Yong Xiang ◽  
Chuan‐Feng Li ◽  
...  

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Zhijun Wu ◽  
Yue Yin ◽  
Guang Li ◽  
Meng Yue

Low-rate denial-of-service (LDoS) attacks are characterized by low average rate and periodicity. Under certain conditions, the high concealment of LDoS attacks enables them to transfer the attack stream to the network without being detected at all before the end. In this article, plenty of LDoS attack traffic is spread to the victim end to detect LDoS attacks. Through experimental analysis, it is found that the attack pulses at the victim end have sequence correlation, so the coherence detection technology in spread spectrum communication is proposed to detect LDoS attacks. Therefore, this paper proposes an attack detection method based on coherent detection, which adopts bivariate cyclic convolution algorithm. Similar to the generation of receiving terminal phase dry detection code in spread spectrum communication, we construct a local detection sequence to complete the extraction of LDoS attack stream from the background traffic of the victim terminal, that is, the coherent detection of LDoS attacks. When predicting the features of an LDoS attack, how to construct the parameters of the detection sequence (such as period, pulse duration, amplitude, and so on) is very important. In this paper, we observe the correlation of LDoS attacks and use coherence detection to detect LDoS attacks. By comparing calculated cross-correlation values with designed double threshold rules, the existence of attacks can be determined. The simulation platform and experiments show that this method has high detection performance.


IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Swagata Duari ◽  
Vasudha Bhatnagar

Author(s):  
Mohammad M. Al-Khaldi ◽  
Joel T. Johnson ◽  
Scott Gleason ◽  
Clara C. Chew ◽  
Cynthia Gerlein-Safdi ◽  
...  

2020 ◽  
Vol 2 (4) ◽  
Author(s):  
Carina Remmers ◽  
Johannes Zimmermann ◽  
Sascha Topolinski ◽  
Christoph Richter ◽  
Thea Zander-Schellenberg ◽  
...  

Background Recent preliminary evidence indicates that depression is associated with impaired intuitive information processing. The current study aimed at replicating these findings and to move one step further by exploring whether factors known as triggering intuition (positivity, processing fluency) also affect intuition in patients with depression. Method We pre-registered and tested five hypotheses using data from 35 patients with depression and 35 healthy controls who performed three versions of the Judgment of Semantic Coherence Task (JSCT, Bowers et al., 1990). This task operationalizes intuition as the inexplicable and sudden detection of semantic coherence. Results Results revealed that depressed patients and healthy controls did not differ in their general intuitive performance (Hypothesis 1). We further found that fluency did not significantly affect depressed patients’ coherence judgments (H2a) and that the assumed effect of fluency on coherence judgments was not moderated by depression (H2b). Finally, we found that triads positive in valence were more likely to be judged as coherent as compared to negative word triads in the depressed sample (H3a), but this influence of positive (vs. negative) valence on coherence judgments did not significantly differ between the two groups (H3b). Conclusion Overall the current study did not replicate findings from previous research regarding intuitive semantic coherence detection deficits in depression. However, our findings suggest that enhancing positivity in depressed patients may facilitate their ability to see meaning in their environment and to take intuitive decision.


2019 ◽  
Vol 48 (12) ◽  
pp. 1203008
Author(s):  
蒋 杉 Jiang Shan ◽  
孙东松 Sun Dongsong ◽  
韩於利 Han Yuli ◽  
韩 飞 Han Fei ◽  
周安然 Zhou Anran ◽  
...  

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