Worldwide analysis of crimes by the traces of their online media coverage: the case of jewellery store robberies

This empirical study aims to determine whether online media coverage can be used to gather intelligence on specific crimes worldwide. The quality of online news is evaluated as an indicator of the worldwide distribution of jewelry store robberies. This phenomenon was selected because evaluating the risk of criminal events at the global level is a challenge for private companies, who need to settle and prioritize protection strategies to determine the actual risk within each country. Online media coverage is thus scrutinized for its ability to reveal spatiotemporal trends of this phenomenon. Based upon a dataset of online news gathered between 2015 and 2017 from the news aggregator website EMM (Europa Media Monitor – NewsBrief), the results show that online news may be a cost-effective method to analyze risks worldwide — though a cross-check with different data sources is still necessary to validate its accuracy. The developed approach shows that (1) while a multilingual approach is required, (2) cases can be detected and automatically classified with good accuracy; (3) moreover, dates and countries of published news articles are generally reliable indicators of the actual times and places of the events, which reduce the need for complex text analysis methods. This study demonstrates how a simple monitoring approach can be used to support the worldwide spatiotemporal analysis of serious crimes such as jewelry store robberies

Using computed similarity of distinctive digital traces to evaluate non-obvious links and repetitions in cyber-investigations

This work addresses the challenge of discerning non-exact or non-obvious similarities between cyber-crimes, proposing a new approach to finding linkages and repetitions across cases in a cyber-investigation context using near similarity calculation of distinctive digital traces. A prototype system was developed to test the proposed approach, and the system was evaluated using digital traces collected during actual cyber-investigations. The prototype system also links cases on the basis of exact similarity between technical characteristics. This work found that the introduction of near similarity helps to confirm already existing links, and exposes additional linkages between cases. Automatic detection of near similarities across cybercrimes gives digital investigators a better understanding of the criminal context and the actual phenomenon, and can reveal a series of related offenses. Using case data from 207cyber-investigations, this study evaluated the effectiveness of computing similarity between cases by applying string similarity algorithms to email addresses. The Levenshtein algorithm was selected as the best algorithm to segregate similar email addresses from non-similar ones. This work can be extended to other digital traces common in cybercrimes such as URLs and domain names. In addition to finding linkages between related cybercrime at a technical level, similarities in patterns across cases provided insights at a behavioral level such as modus operandi (MO). This work also addresses the step that comes after the similarity computation, which is the linkage verification and the hypothesis formation. For forensic purposes, it is necessary to confirm that a near match with the similarity algorithm actually corresponds to a real relation between observed characteristics, and it is important to evaluate the likelihood that the disclosed similarity supports the hypothesis of the link between cases. This work recommends additional information, including certain technical, contextual and behavioral characteristics that could be collected routinely in cyber-investigations to support similarity computation and link evaluation

Chronological independently verifiable electronic chain of custody ledger using blockchain technology

As evidence in digital form becomes more prevalent in all kinds of investigations, there is a pressing need for a trustworthy and transparent way to maintain electronic chain of custody (e-CoC) and integrity information that is independently verifiable. Generally, a hash value of digital evidence is calculated and documented with the acquired data to prove that it has not been altered. However, the hash value alone does not prove that digital evidence is the same as when it was obtained, only that the contents has not been modified since the time when the hash was calculated. This work responds to the need for a chronological independently verifiable e-CoC ledger using blockchain technology. Employing this approach, each e-CoC record is stored in a block, each block being connected to the previous one with the hash value of the block. This e-CoC ledger, the blockchain, can be hosted by a trusted entity and accessed by any party to verify e-CoC details. For privacy reasons, sensitive information is not stored inside the e-CoC record in the blockchain. Moreover, to prove that the e-CoC ledger itself has not been modified, information is periodically sent to a public blockchain, where the integrity is guaranteed by its decentralization and the structure of such a secure ledger. Not all of the blocks are sent into a public blockchain which allows different levels of verification. Proof-of-work examples are provided using AFF4 and dc3dd to demonstrate how this e-CoC ledger can be used by different parties in a legal context, including digital forensic practitioners, attorneys and judges

Learning multi-class classification problems

A multi-class perceptron can learn from examples to solve problems whose answer may take several different values. Starting from a general formalism, we consider the learning of rules by a Hebbian algorithm and by a Monte-Carlo algorithm at high temperature. In the benchmark “prototype-problem” we show that a simple rule may be more than an order of magnitude more efficient than the well-known solution, and in the conventional limit is in fact optimal. A multi-class perceptron is significantly more efficient than a more complicated architecture of binary perceptrons

Forum: Visual Studies—The Art Historians’ View

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