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The purpose of this paper is to model and study the effectiveness of an attack on the anonymity of Internet users by a group of collaborating eavesdroppers.

The paper is based on an analysis of the Internet topology. The study is based on two methods for choosing nodes that contribute the most to the detection of as many communicating Internet users as possible.

The paper illustrates that it is possible to compromise the anonymity of many Internet users when eavesdropping on a relatively small number of nodes, even when the most central ones are protected from eavesdropping.

It is assumed that the Internet users under attack are not using any anonymity enhancing technologies, but nodes can be protected from eavesdropping. It proposes a measure of the success of an attack on Internet users' anonymity, for a given deployment of collaborating eavesdroppers in the Internet.

The paper shows that several, and not necessarily the most prominent, collaborating nodes can compromise the anonymity of a considerable portion of Internet users. This study also emphasizes that when trying to completely compromise the anonymity of Internet users, an eavesdroppers' deployment strategy that considers eavesdroppers' collaboration can result in substantial resource saving compared to choosing a set of the most prominent nodes.

The paper proposes a new measure of anonymity level in the network, based on the linkability of the Internet users. This paper is the first to present results of a non‐trivial Group Betweenness optimization strategy in large complex networks.

In the era of industry 4.0, managing the design is a challenging mission. Within a dynamic environment, several disciplines have adopted the complex adaptive system (CAS) perspective. Therefore, this paper aims to explore how we may deepen our understanding of the design process as a CAS. In this respect, the key complexity drivers of the design process are discussed and an organizational decomposition for the simulation of the design process as CAS is conducted.

The proposed methodology comprises three steps. First, the complexity drivers of the design process are presented and are matched with those of CAS. Second, an analysis of over 111 selected papers is presented to choose the appropriate model for the design process from the CAS theory. Third, the paper provides methodological guidelines to develop an organizational decision support system that supports the complexity of the design process.

An analysis of the key drivers of design process complexity shows the need to adopt the CAS theory. In addition to that, a comparative analysis between all the organizational methodologies developed in the literature leads the authors to conclude that agent-oriented Software Process for engineering complex System is the appropriate methodology for simulating the design process. In this respect, a system requirements phase of the decision support system is conducted.

The originality of this paper lies in the fact of analysing the complexity of the design process as a CAS. In doing so, all the richness of the CAS theory can be used to meet the challenges of those already existing in the theory of the design.

Regarding the magnitude of the impact caused by money laundering, the size of the organization and the many parties involved, this paper aims to explore the methods used in detecting money laundering, especially the use of technology.

This research is a literature review from various research sources originating from Pro-Quest, Emerald, Science Direct and Google Scholar.

The researchers found that the most widely used methods for detecting money laundering were artificial intelligence, machine learning, data mining and social network analysis.

This research is expected to help the government or institutions such as the police, forensic accountants and investigative auditors in the fight against money laundering. This research is limited to only a few sources, and it is hoped that further research can explore more deeply related to other methods for detecting money laundering.

This paper discusses the methods that are widely used in detecting money laundering.