Abnormal traffic detection system in SDN based on deep learning hybrid models

Software defined network (SDN) provides technical support for network construction in smart cities, However, the openness of SDN is also prone to more network attacks. Traditional abnormal traffic detection methods have complex algorithms and find it difficult to detect abnormalities in the network promptly, which cannot meet the demand for abnormal detection in the SDN environment. Therefore, we propose an abnormal traffic detection system based on deep learning hybrid model. The system adopts a hierarchical detection technique, which first achieves rough detection of abnormal traffic based on port information. Then it uses wavelet transform and deep learning techniques for fine detection of all traffic data flowing through suspicious switches. The experimental results show that the proposed detection method based on port information can quickly complete the approximate localization of the source of abnormal traffic. the accuracy, precision, and recall of the fine detection are significantly improved compared with the traditional method of abnormal traffic detection in SDN

Green innovation drives globalization: a longitudinal case study of Angel Yeast’s evolution from a start-up to a world-class manufacturer

In the increasingly competitive global market, emerging market companies, represented by China, have shown mixed performance during their development process. Many companies grow rapidly in the early stages of development but cannot maintain long-term growth. How to achieve sustainable development has become a major challenge for emerging market companies, and green innovation is considered an effective way to address this issue. Based on the resource-based view, this paper conducts a longitudinal case study on Angel Yeast as the research subject, dividing the development process of Angel Yeast into three stages: the start-up period (1986-2000), the growth period (2000-2010), and the maturity period (2010-present), discussing how Angel Yeast has grown from a small start-up company to a world-class manufacturer. The study finds that Angel Yeast has utilized its unique resources at different stages of development for green technology innovation, green product innovation, green management innovation, green marketing innovation, green supply chain management, and green organizational culture construction, enabling Angel Yeast to gain a sustained competitive advantage and grow into a global leader in the yeast industry. This paper expands the research on the evolution of emerging market companies under the resource-based view theory and enriches the understanding of the role of green innovation in the growth process of enterprises

SIGL:Securing Software Installations Through Deep Graph Learning

Many users implicitly assume that software can only be exploited after it is installed. However, recent supply-chain attacks demonstrate that application integrity must be ensured during installation itself. We introduce SIGL, a new tool for detecting malicious behavior during software installation. SIGL collects traces of system call activity, building a data provenance graph that it analyzes using a novel autoencoder architecture with a graph long short-term memory network (graph LSTM) for the encoder and a standard multilayer perceptron for the decoder. SIGL flags suspicious installations as well as the specific installation-time processes that are likely to be malicious. Using a test corpus of 625 malicious installers containing real-world malware, we demonstrate that SIGL has a detection accuracy of 96%, outperforming similar systems from industry and academia by up to 87% in precision and recall and 45% in accuracy. We also demonstrate that SIGL can pinpoint the processes most likely to have triggered malicious behavior, works on different audit platforms and operating systems, and is robust to training data contamination and adversarial attack. It can be used with application-specific models, even in the presence of new software versions, as well as application-agnostic meta-models that encompass a wide range of applications and installers.Comment: 18 pages, to appear in the 30th USENIX Security Symposium (USENIX Security '21

Application of a nerve stereoscopic reconstruction technique based on ultrasonic images in the diagnosis of neuralgic amyotrophy

Objective: To propose a nerve stereoscopic reconstruction technique based on ultrasound imaging for site diagnosis, intuitive reflection of disease severity, and classification of neuralgic amyotrophy (NA).Methods: We enrolled 44 patients with NA who underwent high-frequency ultrasonography examination. Multiple sites on the normal side and the affected side were scanned to calculate the ratio of the cross-section area (CSA) of the affected side to the normal side at each location measured, i.e., the cross-section area swelling ratio (CSASR). The CSASR of 44 patients and 30 normal controls was analyzed to determine their threshold value for the diagnosis of NA. Then, ultrasound images of the cross-section were used to reconstruct the stereoscopic model of the nerve on the affected side and the normal side. Using the CSASR values in each measurement location, a CSASR stereoscopic model was developed.Results: The threshold value of CSASR for ultrasound diagnosis of NA was 1.55. The average diseased segments per patient was 2.49 ± 1.97, with an average overall length of 10.03 ± 7.95 cm. Nerve stereoscopic reconstruction could be conducted for swelling, torsion, incomplete constriction, and complete constriction.Conclusion: The ultrasound image reconstruction method proposed in this study can accurately determine the site, range, and type of neuropathies in patients with NA, and simultaneously provide complete and accurate data information and intuitive morphological information

Late Paleozoic adakites and Nb-enriched basalts from northern Xinjiang, northwest China: evidence for the southward subduction of the Paleo-Asian Oceanic Plate

Abstract Volcanic rocks consisting of adakite and Nb-enriched basalt are found in the early Devonian Tuoranggekuduke Group in the northern margin of the KazakhstanJunggar Plate, northern Xinjiang, northwest China. The geochemical characteristics of the andesitic and dacitic rocks in this area resemble that of adakites. The relatively high Al 2 O 3 , Na 2 O and MgO content and Mg # values indicate that the adakites were generated in relation to oceanic slab subduction rather than the partial melting of basaltic crust. A slightly higher SrI and a lower e Nd (t = 375 Ma) compared to adakites of mid-oceanic ridge basalt (MORB) imply that slab sediments were incorporated into these adakites during slab melting. The Nb-enriched basalt lavas, which are intercalated in adakite lava suite, are silica saturated and are distinguished from the typical arc basalts by their higher Nb and Ti content (high field strength element enrichment). They are derived from the partial melting of the slab melt-metasomatized mantle wedge peridotite. Apparently, positive Sr anomalies and a slightly higher heavy rare earth element content in these adakites compared to their Cenozoic counterparts indicate that the geothermal gradient in the PaleoAsian Oceanic subduction zone and the depth of the Paleo-Asian Oceanic slab melting are between those of their Archean and Cenozoic counterparts. The distribution of the adakites and Nb-enriched basalts in the northern margin of the Kazakhstan-Junggar Plate, northern Xinjiang, indicates that the Paleo-Asian Oceanic Plate subducted southward beneath the Kazakhstan-Junggar Plate in the early Devonian period

Efficient Luminescence from CsPbBr₃ Nanoparticles Embedded in Cs₄PbBr₆

This work was financially supported by the “Advanced Research Center of Green Materials Science and Technology” from The Featured Area Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (107L9006) and the Ministry of Science and Technology in Taiwan (MOST 107-2113-M-002-008-MY3, MOST 107-2923-M-002-004-MY3, and MOST 107-3017-F-002-001), the National Centre for Research and Development Poland Grant (No. PL-TW/V/1/2018), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB20000000), the CAS/SAFEA International Partnership Program for Creative Research Teams, and the NSFC (Nos. U1805252 and 11774345). J.P.A. acknowledges financial support from EPSRC, U.K.Cs4PbBr6 is regarded as an outstanding luminescent material with good thermal stability and optical performance. However, the mechanism of green emission from Cs4PbBr6 has been controversial. Here we show that isolated CsPbBr3 nanoparticles embedded within a Cs4PbBr6 matrix give rise to a “normal” green luminescence while superfluorescence at longer wavelengths is suppressed. High-resolution transmission electron microscopy shows that the embedded CsPbBr3 nanoparticles are around 3.8 nm in diameter and are well-separated from each other, perhaps by a strain-driven mechanism. This mechanism may enable other efficient luminescent composites to be developed by embedding optically active nanoparticles epitaxially within inert host lattices.PostprintPeer reviewe

Preventive Effects of Collagen Peptide from Deer Sinew on Bone Loss in Ovariectomized Rats

Deer sinew (DS) has been used traditionally for various illnesses, and the major active constituent is collagen. In this study, we assessed the effects of collagen peptide from DS on bone loss in the ovariectomized rats. Wister female rats were randomly divided into six groups as follows: sham-operated (SHAM), ovariectomized control (OVX), OVX given 1.0 mg/kg/week nylestriol (OVX + N), OVX given 0.4 g/kg/day collagen peptide (OVX + H), OVX given 0.2 g/kg/day collagen peptide (OXV + M), and OVX given 0.1 g/kg/day collagen peptide (OXV + L), respectively. After 13 weeks of treatment, the rats were euthanized, and the effects of collagen peptide on body weight, uterine weight, bone mineral density (BMD), serum biochemical indicators, bone histomorphometry, and bone mechanics were observed. The data showed that BMD and concentration of serum hydroxyproline were significantly increased and the levels of serum calcium, phosphorus, and alkaline phosphatase were decreased. Besides, histomorphometric parameters and mechanical indicators were improved. However, collagen peptide of DS has no effect on estradiol level, body weight, and uterine weight. Therefore, these results suggest that the collagen peptide supplementation may also prevent and treat bone loss