65,125 research outputs found
A Fuzzy Hashing Approach Based on Random Sequences and Hamming Distance
Hash functions are well-known methods in computer science to map arbitrary large input to bit strings of a fixed length that serve as unique input identifier/fingerprints. A key property of cryptographic hash functions is that even if only one bit of the input is changed the output behaves pseudo randomly and therefore similar files cannot be identified. However, in the area of computer forensics it is also necessary to find similar files (e.g. different versions of a file), wherefore we need a similarity preserving hash function also called fuzzy hash function. In this paper we present a new approach for fuzzy hashing called bbHash. It is based on the idea to ârebuildâ an input as good as possible using a fixed set of randomly chosen byte sequences called building blocks of byte length l (e.g. l= 128 ). The proceeding is as follows: slide through the input byte-by-byte, read out the current input byte sequence of length l , and compute the Hamming distances of all building blocks against the current input byte sequence. Each building block with Hamming distance smaller than a certain threshold contributes the fileâs bbHash. We discuss (dis- )advantages of our bbHash to further fuzzy hash approaches. A key property of bbHash is that it is the first fuzzy hashing approach based on a comparison to external data structures.
Keywords: Fuzzy hashing, similarity preserving hash function, similarity digests, Hamming distance, computer forensics
Faster Base64 Encoding and Decoding Using AVX2 Instructions
Web developers use base64 formats to include images, fonts, sounds and other
resources directly inside HTML, JavaScript, JSON and XML files. We estimate
that billions of base64 messages are decoded every day. We are motivated to
improve the efficiency of base64 encoding and decoding. Compared to
state-of-the-art implementations, we multiply the speeds of both the encoding
(~10x) and the decoding (~7x). We achieve these good results by using the
single-instruction-multiple-data (SIMD) instructions available on recent Intel
processors (AVX2). Our accelerated software abides by the specification and
reports errors when encountering characters outside of the base64 set. It is
available online as free software under a liberal license.Comment: software at https://github.com/lemire/fastbase6
A Differential Cryptanalysis of Yen-Chen-Wu Multimedia Cryptography System (MCS)
At ISCAS'2005, Yen et al. presented a new chaos-based cryptosystem for
multimedia transmission named "Multimedia Cryptography System" (MCS). No
cryptanalytic results have been reported so far. This paper presents a
differential attack to break MCS, which requires only seven chosen plaintexts.
The complexity of the attack is O(N), where is the size of plaintext.
Experimental results are also given to show the real performance of the
proposed attack.Comment: 22 pages, 5 figure
Faster Base64 Encoding and Decoding Using AVX2 Instructions
Web developers use base64 formats to include images, fonts, sounds and other
resources directly inside HTML, JavaScript, JSON and XML files. We estimate
that billions of base64 messages are decoded every day. We are motivated to
improve the efficiency of base64 encoding and decoding. Compared to
state-of-the-art implementations, we multiply the speeds of both the encoding
(~10x) and the decoding (~7x). We achieve these good results by using the
single-instruction-multiple-data (SIMD) instructions available on recent Intel
processors (AVX2). Our accelerated software abides by the specification and
reports errors when encountering characters outside of the base64 set. It is
available online as free software under a liberal license.Comment: software at https://github.com/lemire/fastbase6
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