Analysis of malicious behaviors in peer-to-peer trust model;
Peer-to-Peer信任模型中的恶意行为分析
Each dimension of the vector stood for a malicious behavior event represented by corresponding Win32 API calls and their certain parameters.
特征向量的每一维用于表示一种恶意行为事件,每一事件由相应的Win32应用程序编程接口(API)调用及其参数表示,并实现了一个自动化行为追踪系统(Argus)用于行为特征的提取。
This paper introduced several typical trust models and malicious behavior patterns, then analyzed the characters of these trust models and their resistance to difference malicious behaviors by simulations.
在目前已广泛应用的P2P网络中,由于缺乏严格的身份验证和信任机制,存在着许多欺诈等恶意行为,系统的有效性和可用性难以保证。
scraping of bones [offensive trade]
刮骨〔厌恶性行业〕
crushing of bones [offensive trade]
磨骨〔厌恶性行业〕
burning of bones [offensive trade]
烧骨〔厌恶性行业〕
boiling of bones [offensive trade]
煮骨〔厌恶性行业〕
storing of bones [offensive trade]
贮存骨〔厌恶性行业〕
storing of feathers [offensive trade]
贮存羽毛〔厌恶性行业〕
boiling of lard [offensive trade]
煮猪油〔厌恶性行业〕
tanning of leather [offensive trade]
制炼皮革〔厌恶性行业〕
fell-mongery [offensive trade]
毛皮加工〔厌恶性行业〕
manufacture of chloride of lime [offensive trade]
制造漂白粉〔厌恶性行业〕
boiling of fat [offensive trade]
煮脂肪〔厌恶性行业〕
boiling of resin [offensive trade]
煮树脂〔厌恶性行业〕
sorting of feathers [offensive trade]
拣羽毛〔厌恶性行业〕
manufacture of glue [offensive trade]
制造胶水〔厌恶性行业〕
dressing of leather [offensive trade]
打磨皮革〔厌恶性行业〕
cleaning of hair [offensive trade]
清洗毛发〔厌恶性行业〕
cleaning of feathers [offensive trade]
清洗羽毛〔厌恶性行业〕
melting of tallow [offensive trade]
融解固体脂肪〔厌恶性行业〕