Data stream methods look at each new item of the stream, perform a small number of operations while keeping a small amount of memory, and still perform muchneeded analyses. Howeve...
Current research on data stream classification mainly focuses on certain data, in which precise and definite value is usually assumed. However, data with uncertainty is quite natu...
In 1980 Hellman introduced a general technique for breaking arbitrary block ciphers with N possible keys in time T and memory M related by the tradeoff curve TM2 = N2 for 1 T N. ...
Data stream processing systems have become ubiquitous in academic and commercial sectors, with application areas that include financial services, network traffic analysis, battlef...
Random sampling is an appealing approach to build synopses of large data streams because random samples can be used for a broad spectrum of analytical tasks. Users are often inter...