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Information Filtering and Information Retrieval: Two Sides of the Same Coin
 COMMUNICATIONS OF THE ACM
, 1992
"... Information filtering systems are designed for unstructured or semistructured data, as opposed to database applications, which use very structured data. The systems also deal primarily with textual information, but they may also entail images, voice, video or other data types that are part of multim ..."
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Cited by 441 (6 self)
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Information filtering systems are designed for unstructured or semistructured data, as opposed to database applications, which use very structured data. The systems also deal primarily with textual information, but they may also entail images, voice, video or other data types that are part
Cipher
"... We consider a simple and secure way to realize a synchronous stream cipher from iterated hash functions. It is similar to the OFB mode where the underlying block cipher algorithm is replaced with the keyed hash function, adopting the secret suffix method[20]. We analyzed the key, the keystream and t ..."
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We consider a simple and secure way to realize a synchronous stream cipher from iterated hash functions. It is similar to the OFB mode where the underlying block cipher algorithm is replaced with the keyed hash function, adopting the secret suffix method[20]. We analyzed the key, the keystream
Algebraic Attacks on Stream Ciphers with Linear Feedback
, 2003
"... A classical construction of stream ciphers is to combine several LFSRs and a highly nonlinear Boolean function f . Their security is usually studied in terms of correlation attacks, that can be seen as solving a system of multivariate linear equations, true with some probability. At ICISC'0 ..."
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Cited by 264 (21 self)
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A classical construction of stream ciphers is to combine several LFSRs and a highly nonlinear Boolean function f . Their security is usually studied in terms of correlation attacks, that can be seen as solving a system of multivariate linear equations, true with some probability. At ICISC
Stream ciphers
, 2010
"... Symmetrickey encryption schemes are often characterised as stream ciphers or block ciphers, but the distinction can be fuzzy. ◮ A stream cipher is an encryption scheme which treats the plaintext symbolbysymbol (e.g., by bit or byte); ◮ security in a stream cipher lies in a changing keystream rath ..."
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Symmetrickey encryption schemes are often characterised as stream ciphers or block ciphers, but the distinction can be fuzzy. ◮ A stream cipher is an encryption scheme which treats the plaintext symbolbysymbol (e.g., by bit or byte); ◮ security in a stream cipher lies in a changing keystream
Stream ciphers
, 2011
"... Symmetrickey encryption schemes are often characterised as stream ciphers or block ciphers, but the distinction can be fuzzy. ◮ A stream cipher is an encryption scheme which treats the plaintext symbolbysymbol (e.g., by bit or byte); ◮ security in a stream cipher lies in a changing keystream rath ..."
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Symmetrickey encryption schemes are often characterised as stream ciphers or block ciphers, but the distinction can be fuzzy. ◮ A stream cipher is an encryption scheme which treats the plaintext symbolbysymbol (e.g., by bit or byte); ◮ security in a stream cipher lies in a changing keystream
A framework for clustering evolving data streams. In:
 Proc of VLDB’03,
, 2003
"... Abstract The clustering problem is a difficult problem for the data stream domain. This is because the large volumes of data arriving in a stream renders most traditional algorithms too inefficient. In recent years, a few onepass clustering algorithms have been developed for the data stream proble ..."
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Cited by 360 (35 self)
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Abstract The clustering problem is a difficult problem for the data stream domain. This is because the large volumes of data arriving in a stream renders most traditional algorithms too inefficient. In recent years, a few onepass clustering algorithms have been developed for the data stream
STREAM CIPHERS
"... Abstract—A divideandconquer cryptanalysis can often be mounted against some keystream generators composed of several (nonlinear) independent devices combined by a Boolean function. In particular, any paritycheck relation derived from the periods of some constituent sequences usually leads to a di ..."
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Abstract—A divideandconquer cryptanalysis can often be mounted against some keystream generators composed of several (nonlinear) independent devices combined by a Boolean function. In particular, any paritycheck relation derived from the periods of some constituent sequences usually leads to a distinguishing attack whose complexity is determined by the bias of the relation. However, estimating this bias is a difficult problem since the pilingup lemma cannot be used. Here, we give two exact expressions for this bias. Most notably, these expressions lead to a new algorithm for computing the bias of a paritycheck relation, and they also provide some simple formulae for this bias in some particular cases which are commonly used in cryptography. I. DIVIDEANDCONQUER ATTACKS AGAINST SOME
2. Block Cipher and Stream Cipher
"... The two main characteristics that identify and differentiate one encryption algorithm from another are its ability to secure the protected data against attacks and its speed and efficiency in doing so. This paper provides a performance comparison between four of the most common encryption algorithms ..."
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The two main characteristics that identify and differentiate one encryption algorithm from another are its ability to secure the protected data against attacks and its speed and efficiency in doing so. This paper provides a performance comparison between four of the most common encryption algorithms: DES, 3DES, Blowfish and AES (Rijndael). The comparison has been conducted by running several encryption settings to process different sizes of data blocks to evaluate the algorithm's encryption/decryption speed. Simulation has
Sampling signals with finite rate of innovation
 IEEE Transactions on Signal Processing
, 2002
"... Abstract—Consider classes of signals that have a finite number of degrees of freedom per unit of time and call this number the rate of innovation. Examples of signals with a finite rate of innovation include streams of Diracs (e.g., the Poisson process), nonuniform splines, and piecewise polynomials ..."
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Cited by 351 (67 self)
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Abstract—Consider classes of signals that have a finite number of degrees of freedom per unit of time and call this number the rate of innovation. Examples of signals with a finite rate of innovation include streams of Diracs (e.g., the Poisson process), nonuniform splines, and piecewise
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