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Computer Sciences

Electrical & Computer Engineering and Computer Science Faculty Publications

Hashing

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Full-Text Articles in Computer Engineering

An Empirical Comparison Of Widely Adopted Hash Functions In Digital Forensics: Does The Programming Language And Operating System Make A Difference?, Satyendra Gurjar, Ibrahim Baggili, Frank Breitinger, Alice E. Fischer Jan 2015

An Empirical Comparison Of Widely Adopted Hash Functions In Digital Forensics: Does The Programming Language And Operating System Make A Difference?, Satyendra Gurjar, Ibrahim Baggili, Frank Breitinger, Alice E. Fischer

Electrical & Computer Engineering and Computer Science Faculty Publications

Hash functions are widespread in computer sciences and have a wide range of applications such as ensuring integrity in cryptographic protocols, structuring database entries (hash tables) or identifying known files in forensic investigations. Besides their cryptographic requirements, a fundamental property of hash functions is efficient and easy computation which is especially important in digital forensics due to the large amount of data that needs to be processed when working on cases. In this paper, we correlate the runtime efficiency of common hashing algorithms (MD5, SHA-family) and their implementation. Our empirical comparison focuses on C-OpenSSL, Python, Ruby, Java on Windows and ...


Automated Evaluation Of Approximate Matching Algorithms On Real Data, Frank Breitinger, Vassil Roussev Jan 2014

Automated Evaluation Of Approximate Matching Algorithms On Real Data, Frank Breitinger, Vassil Roussev

Electrical & Computer Engineering and Computer Science Faculty Publications

Bytewise approximate matching is a relatively new area within digital forensics, but its importance is growing quickly as practitioners are looking for fast methods to screen and analyze the increasing amounts of data in forensic investigations. The essential idea is to complement the use of cryptographic hash functions to detect data objects with bytewise identical representation with the capability to find objects with bytewise similarrepresentations.

Unlike cryptographic hash functions, which have been studied and tested for a long time, approximate matching ones are still in their early development stages and evaluation methodology is still evolving. Broadly, prior approaches have ...


An Efficient Similarity Digests Database Lookup -- A Logarithmic Divide And Conquer Approach, Frank Breitinger, Christian Rathgeb, Harald Baier Jan 2014

An Efficient Similarity Digests Database Lookup -- A Logarithmic Divide And Conquer Approach, Frank Breitinger, Christian Rathgeb, Harald Baier

Electrical & Computer Engineering and Computer Science Faculty Publications

Investigating seized devices within digital forensics represents a challenging task due to the increasing amount of data. Common procedures utilize automated file identification, which reduces the amount of data an investigator has to examine manually. In the past years the research field of approximate matching arises to detect similar data. However, if n denotes the number of similarity digests in a database, then the lookup for a single similarity digest is of complexity of O(n). This paper presents a concept to extend existing approximate matching algorithms, which reduces the lookup complexity from O(n) to O(log(n)). Our ...


An Ad Hoc Adaptive Hashing Technique For Non-Uniformly Distributed Ip Address Lookup In Computer Networks, Christopher Martinez, Wei-Ming Lin Jan 2007

An Ad Hoc Adaptive Hashing Technique For Non-Uniformly Distributed Ip Address Lookup In Computer Networks, Christopher Martinez, Wei-Ming Lin

Electrical & Computer Engineering and Computer Science Faculty Publications

Hashing algorithms have been widely adopted for fast address look-up, which involves a search through a database to find a record associated with a given key. Hashing algorithms transforms a key into a hash value hoping that the hashing renders the database a uniform distribution with respect to the hash value. The closer to uniform hash values, the less search time required for a query. When the database is key-wise uniformly distributed, any regular hashing algorithm (bit-extraction, bit-group XOR, etc.) leads to a statistically perfect uniform hash distribution. When the database has keys with a non-uniform distribution, performance of regular ...