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Computer Sciences

Electrical & Computer Engineering and Computer Science Faculty Publications

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Full-Text Articles in Computer Engineering

Bytewise Approximate Matching: The Good, The Bad, And The Unknown, Vikram S. Harichandran, Frank Breitinger, Ibrahim Baggili Jan 2016

Bytewise Approximate Matching: The Good, The Bad, And The Unknown, Vikram S. Harichandran, Frank Breitinger, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

Hash functions are established and well-known in digital forensics, where they are commonly used for proving integrity and file identification (i.e., hash all files on a seized device and compare the fingerprints against a reference database). However, with respect to the latter operation, an active adversary can easily overcome this approach because traditional hashes are designed to be sensitive to altering an input; output will significantly change if a single bit is flipped. Therefore, researchers developed approximate matching, which is a rather new, less prominent area but was conceived as a more robust counterpart to traditional hashing. Since the ...


On The Database Lookup Problem Of Approximate Matching, Frank Breitinger, Harald Baier, Douglas White May 2014

On The Database Lookup Problem Of Approximate Matching, Frank Breitinger, Harald Baier, Douglas White

Electrical & Computer Engineering and Computer Science Faculty Publications

Investigating seized devices within digital forensics gets more and more difficult due to the increasing amount of data. Hence, a common procedure uses automated file identification which reduces the amount of data an investigator has to look at by hand. Besides identifying exact duplicates, which is mostly solved using cryptographic hash functions, it is also helpful to detect similar data by applying approximate matching.

Let x denote the number of digests in a database, then the lookup for a single similarity digest has the complexity of O(x). In other words, the digest has to be compared against all digests ...


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 ...


File Detection On Network Traffic Using Approximate Matching, Frank Breitinger, Ibrahim Baggili Jan 2014

File Detection On Network Traffic Using Approximate Matching, Frank Breitinger, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

In recent years, Internet technologies changed enormously and allow faster Internet connections, higher data rates and mobile usage. Hence, it is possible to send huge amounts of data / files easily which is often used by insiders or attackers to steal intellectual property. As a consequence, data leakage prevention systems (DLPS) have been developed which analyze network traffic and alert in case of a data leak. Although the overall concepts of the detection techniques are known, the systems are mostly closed and commercial. Within this paper we present a new technique for network traffic analysis based on approximate matching (a.k ...


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 ...