We report a GaSb-based type-I quantum well cascade diode laser emitting at nearly 2-μm wavelength.The recycling of carriers is realized by the gradient AlGaAsSb barrier and chirped GaSb/AlSb/InAs electron injector.Th...We report a GaSb-based type-I quantum well cascade diode laser emitting at nearly 2-μm wavelength.The recycling of carriers is realized by the gradient AlGaAsSb barrier and chirped GaSb/AlSb/InAs electron injector.The growth of quaternary digital alloy with a gradually changed composition by short-period superlattices is introduced in detail in this paper.And the quantum well cascade laser with 100-μm-wide,2-mm-long ridge generates an about continuous-wave output of 0.8 W at room temperature.The characteristic temperature T_(0) is estimated at above 60 K.展开更多
Malware homology identification is important in attacking event tracing, emergency response scheme generation, and event trend prediction. Current malware homology identification methods still rely on manual analysis,...Malware homology identification is important in attacking event tracing, emergency response scheme generation, and event trend prediction. Current malware homology identification methods still rely on manual analysis, which is inefficient and cannot respond quickly to the outbreak of attack events. In response to these problems, we propose a new malware homology identification method from a gene perspective. A malware gene is represented by the subgraph, which can describe the homology of malware families. We extract the key subgraph from the function dependency graph as the malware gene by selecting the key application programming interface(API) and using the community partition algorithm. Then, we encode the gene and design a frequent subgraph mining algorithm to find the common genes between malware families. Finally, we use the family genes to guide the identification of malware based on homology. We evaluate our method with a public dataset, and the experiment results show that the accuracy of malware classification reaches 97% with high efficiency.展开更多
基金Project supported by the Major Program of the National Natural Science Foundation of China(Grant No.61790581)the Key Area Research and Development Program of Guangdong Province,China(Grant No.2020B0303020001).
文摘We report a GaSb-based type-I quantum well cascade diode laser emitting at nearly 2-μm wavelength.The recycling of carriers is realized by the gradient AlGaAsSb barrier and chirped GaSb/AlSb/InAs electron injector.The growth of quaternary digital alloy with a gradually changed composition by short-period superlattices is introduced in detail in this paper.And the quantum well cascade laser with 100-μm-wide,2-mm-long ridge generates an about continuous-wave output of 0.8 W at room temperature.The characteristic temperature T_(0) is estimated at above 60 K.
基金the National Natural Science Foundation of China (Nos. 61472447 and 61802435).
文摘Malware homology identification is important in attacking event tracing, emergency response scheme generation, and event trend prediction. Current malware homology identification methods still rely on manual analysis, which is inefficient and cannot respond quickly to the outbreak of attack events. In response to these problems, we propose a new malware homology identification method from a gene perspective. A malware gene is represented by the subgraph, which can describe the homology of malware families. We extract the key subgraph from the function dependency graph as the malware gene by selecting the key application programming interface(API) and using the community partition algorithm. Then, we encode the gene and design a frequent subgraph mining algorithm to find the common genes between malware families. Finally, we use the family genes to guide the identification of malware based on homology. We evaluate our method with a public dataset, and the experiment results show that the accuracy of malware classification reaches 97% with high efficiency.
