scholarly journals An Improved Bytewise Approximate Matching Algorithm Suitable for Files of Dissimilar Sizes

Mathematics ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 503
Author(s):  
Víctor Gayoso Martínez ◽  
Fernando Hernández-Álvarez ◽  
Luis Hernández Encinas
Keyword(s):  
Digital Forensics ◽  
Ad Hoc ◽  
Full Description ◽  
Matching Algorithm ◽  
Approximate Matching ◽  
Digital Devices ◽  
Signature Generation ◽  
Actual Content ◽  
Similarity Preserving ◽  
Generation Procedure

The goal of digital forensics is to recover and investigate pieces of data found on digital devices, analysing in the process their relationship with other fragments of data from the same device or from different ones. Approximate matching functions, also called similarity preserving or fuzzy hashing functions, try to achieve that goal by comparing files and determining their resemblance. In this regard, ssdeep, sdhash, and LZJD are nowadays some of the best-known functions dealing with this problem. However, even though those applications are useful and trustworthy, they also have important limitations (mainly, the inability to compare files of very different sizes in the case of ssdeep and LZJD, the excessive size of sdhash and LZJD signatures, and the occasional scarce relationship between the comparison score obtained and the actual content of the files when using the three applications). In this article, we propose a new signature generation procedure and an algorithm for comparing two files through their digital signatures. Although our design is based on ssdeep, it improves some of its limitations and satisfies the requirements that approximate matching applications should fulfil. Through a set of ad-hoc and standard tests based on the FRASH framework, it is possible to state that the proposed algorithm presents remarkable overall detection strengths and is suitable for comparing files of very different sizes. A full description of the multi-thread implementation of the algorithm is included, along with all the tests employed for comparing this proposal with ssdeep, sdhash, and LZJD.

Privacy Concerns with Digital Forensics

2016 ◽  
pp. 145-162
Author(s):  
Neil C. Rowe
Keyword(s):  
Digital Forensics ◽  
Digital Data ◽  
Commercial Software ◽  
Privacy Concerns ◽  
Digital Space ◽  
Digital Devices ◽  
Privacy Laws ◽  
Private Spaces ◽  
Detailed Search

Digital forensics is a rapidly growing technology for examining the contents of computers and digital devices. It raises many challenges to conventional notions of privacy because it involves a considerably more detailed search of digital data than is possible with other techniques, and it can be done surreptitiously. However, there are analogies to homes and the rights of individuals to be free from unwarranted searches and seizures in their private spaces. Even though commercial software and data comprises most of digital space, there are clearly enclaves of data that deserves to be kept private. We discuss the techniques of digital forensics and investigative targets. We identify key challenges to privacy, and outline both the legal protections and the technical protections available. Unfortunately, privacy laws are ineffective in most countries, and users need to take their own measures to protect themselves.

User profiling via application usage pattern on digital devices for digital forensics

2021 ◽  
Vol 168 ◽  
pp. 114488
Author(s):  
Hongkyun Kwon ◽  
Sangjin Lee ◽  
Doowon Jeong
Keyword(s):  
Digital Forensics ◽  
User Profiling ◽  
Usage Pattern ◽  
Digital Devices

Development and Various Critical Testing Operational Frameworks in Data Acquisition for Cyber Forensics

2020 ◽  
pp. 88-102
Author(s):  
Abhineet Anand ◽  
M. Arvindhan
Keyword(s):  
Data Acquisition ◽  
Digital Forensics ◽  
Digital Data ◽  
Court Cases ◽  
Cyber Forensics ◽  
Digital Devices ◽  
Private Lives ◽  
Or Methodology ◽  
Crime Detection ◽  
Operational Frameworks

Digital forensics is the science of preserving and analyzing digital data; this data can then be used in court cases as well as for crime detection and prevention. Digital forensics began in the 1970s and was initially used as a tool for fighting financial crime. Today, with computers and digital devices being an integral part of our professional and private lives, digital forensics are used/needed in a wide variety of disputes. Data Acquisitions is described and discuss different techniques or methodology obtain the data, facts, and figures from different resource and at a different level of the system.

The Influence of the Nature of Material and of Mental Operations on the Occurrence of the Bizarreness Effect

1988 ◽  
Vol 40 (1) ◽  
pp. 73-85 ◽  
Author(s):  
Cesare Cornoldi ◽  
Adele Cavedon ◽  
Rossana De Beni ◽  
Alvaro Pra Baldi
Keyword(s):  
Free Recall ◽  
Ad Hoc ◽  
Cued Recall ◽  
Bizarreness Effect ◽  
Memory Advantage ◽  
The Subject ◽  
Common Items ◽  
Generation Procedure

In the literature, a memory advantage for bizarre items over common ones has been found only in a few studies, especially with materials prepared ad hoc by the experimenter and with free recall rather than cued recall tests. These results contrast with the widespread conviction that bizarreness helps recall. The present paper explores the role of some variables involved in the “bizarreness” effect: (1) It examines the typical self-generation procedure in which the subject is asked to create an interaction between a pair of nouns, as well as the case in which only one noun is given. Higher freedom in generating sentences appears to correspond to higher free recall of bizarre items. (2) It is shown that bizarre items must be distinguished from “unusual” ones, which have different effects on memory. (3) By contrasting groups instructed to use either imagery or verbal elaboration, it is shown that the bizarreness effect is linked to the use of imagery. Instructions to use imagery without the possibility of creating bizarre representations do not improve the recall of common items. (4) The classification of parts of sentences generated reveals that, under common instructions, one subject's choice of verb and noun is more likely to be shared by other subjects. This fact may explain the different effects found by previous research in cued and free recall. (5) The overestimation of the recallability of bizarre items appears less evident than in previous research, probably because subjects had direct experience of the difficulties met in generating bizarre images.

Data Handling of Digital Forensics Cloud Computing

2013 ◽  
Vol 756-759 ◽  
pp. 1739-1743
Author(s):  
Gang Zeng
Keyword(s):  
Cloud Computing ◽  
Digital Forensics ◽  
Data Handling ◽  
Digital Devices

With development of network and digital devices, traditional digital forensics tools show their drawbacks, and investigators need new forensics tools to deal with enormous digital evidences. Therefore, this paper introduces digital forensics and cloud computing, then lists the advantages of private forensics cloud computing, proposes a model of Data Handling of Digital Forensics Cloud Computing.

An error-tolerant approximate matching algorithm for labeled combinatorial maps

2015 ◽  
Vol 156 ◽  
pp. 211-220 ◽  
Author(s):  
Tao Wang ◽  
Hua Yang ◽  
Congyan Lang ◽  
Songhe Feng
Keyword(s):  
Matching Algorithm ◽  
Approximate Matching ◽  
Combinatorial Maps

scholarly journals An Adaptive Lossly Quantization Technique for Key Extraction Applied in Vehicular Communication

2021 ◽  
Author(s):  
Ibraheem Abdelazeem Ibraheem Ali ◽  
Zhang Weibin ◽  
Zhenping Zeng ◽  
Abdeldime mohamed saleh
Keyword(s):  
Ad Hoc Network ◽  
Ad Hoc ◽  
Vehicular Communications ◽  
Vehicular Communication ◽  
Secret Key ◽  
Velocity Difference ◽  
Privacy Amplification ◽  
Security Services ◽  
Key Extraction ◽  
Generation Procedure

Abstract Security in Vehicular Ad Hoc Network (VANET) is one of the major challenging topics and the secure key interchange between two legitimate vehicles is an important issue. The multi-environment of VANET has been exploited to extract the secret key and employed security services in VANET. However, it offered more excellence randomness owed to fading, noise multi-path, and velocity difference. Some of the factors like Bit-rate, complication and memory requests are reduced by using a process known as quantization. This paper proposes a new quantization method to extract the secret key for vehicular communications that uses a lossy quantizer in combination with information reconciliation and privacy amplification. Our work focuses on the quantization phase for the secret generation procedure. The comprehensive simulations display the propose method increases the zone and number of the quantization levels to utilize the maximum number of measurements to reduce reasonably the wasted measurements.

scholarly journals Understanding the effects of removing common blocks on Approximate Matching scores under different scenarios for digital forensic investigations

2019 ◽  
Author(s):  
Vitor Hugo Moia ◽  
Frank Breitinger ◽  
Marco Aurélio Henriques
Keyword(s):  
Data Structures ◽  
Digital Forensics ◽  
Similarity Score ◽  
Approximate Matching ◽  
Similarity Detection ◽  
Digital Forensic ◽  
Compact Representations ◽  
Forensic Investigations ◽  
New Interpretation ◽  
Digital Forensic Investigations

Finding similarity in digital forensics investigations can be assisted with the use of Approximate Matching (AM) functions. These algorithms create small and compact representations of objects (similar to hashes) which can be compared to identify similarity. However, often results are biased due to common blocks (data structures found in many different files regardless of content). In this paper, we evaluate the precision and recall metrics for AM functions when removing common blocks. In detail, we analyze how the similarity score changes and impacts different investigation scenarios. Results show that many irrelevant matches can be filtered out and that a new interpretation of the score allows a better similarity detection.

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