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Complex networks obtained from the real-world networks are often characterized by incompleteness and noise, consequences of limited sampling as well as artifacts in the acquisition process. Because the characterization, analysis and…

Physics and Society · Physics 2008-06-24 P. R. Villas Boas , F. A. Rodrigues , G. Travieso , L. da F. Costa

Community detection in social networks is a problem with considerable interest, since, discovering communities reveals hidden information about networks. There exist many algorithms to detect inherent community structures and recently few…

Social and Information Networks · Computer Science 2019-11-21 Waqas Nawaz

Many real-world networks are known to exhibit facts that counter our knowledge prescribed by the theories on network creation and communication patterns. A common prerequisite in network analysis is that information on nodes and links will…

Physics and Society · Physics 2018-04-03 Guy Kelman , Eran Manes , Marco Lamieri , David Breé

Missing data has the potential to affect analyses conducted in all fields of scientific study, including healthcare, economics, and the social sciences. Several approaches to unbiased inference in the presence of non-ignorable missingness…

Methodology · Statistics 2020-09-01 Razieh Nabi , Rohit Bhattacharya , Ilya Shpitser

We study social networks and focus on covert (also known as hidden) networks, such as terrorist or criminal networks. Their structures, memberships and activities are illegal. Thus, data about covert networks is often incomplete and…

Social and Information Networks · Computer Science 2021-11-29 Amr Elsisy , Aamir Mandviwalla , Boleslaw Szymanski , Thomas Sharkey

Information on cyber-related crimes, incidents, and conflicts is abundantly available in numerous open online sources. However, processing the large volumes and streams of data is a challenging task for the analysts and experts, and entails…

Cryptography and Security · Computer Science 2022-08-03 Tuomas Takko , Kunal Bhattacharya , Martti Lehto , Pertti Jalasvirta , Aapo Cederberg , Kimmo Kaski

Two models are introduced to investigate graph matching in the presence of corrupt nodes. The weak model, inspired by biological networks, allows one or both networks to have a positive fraction of molecular entities interact randomly with…

Statistics Theory · Mathematics 2023-11-02 Taha Ameen , Bruce Hajek

It is estimated that Italian Mafias registered 135 billion euros in profits only in 2010. Part of this huge amount of money, coming mostly from the drugs, prostitution and arms illicit markets, is often used to invest into legitimate…

Computers and Society · Computer Science 2014-03-21 Stefano Gurciullo

Machine learning models are shown to face a severe threat from Model Extraction Attacks, where a well-trained private model owned by a service provider can be stolen by an attacker pretending as a client. Unfortunately, prior works focus on…

Machine Learning · Computer Science 2021-12-02 Bang Wu , Xiangwen Yang , Shirui Pan , Xingliang Yuan

Spreading of either information or matter can often be treated as a network problem. It can be of great importance to be able to estimate the likelihood that spreading through a network reaches essentially the entire network while still not…

Disordered Systems and Neural Networks · Physics 2009-03-09 Tomas Alarcon , Henrik Jeldtoft Jensen

To capture the systemic complexity of international financial systems, network data is an important prerequisite. However, dyadic data is often not available, raising the need for methods that allow for reconstructing networks based on…

Applications · Statistics 2019-09-05 Michael Lebacher , Samantha Cook , Nadja Klein , Göran Kauermann

We model the hierarchical evolution of an organized criminal network via antagonistic recruitment and pursuit processes. Within the recruitment phase, a criminal kingpin enlists new members into the network, who in turn seek out other…

Physics and Society · Physics 2016-03-23 Charles Z. Marshak , M. Puck Rombach , Andrea L. Bertozzi , Maria R. D'Orsogna

The goal of this note is to assess whether simple machine learning algorithms can be used to determine whether and how a given network has been attacked. The procedure is based on the $k$-Nearest Neighbor and the Random Forest…

Physics and Society · Physics 2023-08-30 Davide Coppes , Paolo Cermelli

Large networked systems are constantly exposed to local damages and failures that can alter their functionality. The knowledge of the structure of these systems is however often derived through sampling strategies whose effectiveness at…

Physics and Society · Physics 2015-06-18 Fabio Ciulla , Nicola Perra , Andrea Baronchelli , Alessandro Vespignani

Identifying threats in a network traffic flow which is encrypted is uniquely challenging. On one hand it is extremely difficult to simply decrypt the traffic due to modern encryption algorithms. On the other hand, passing such an encrypted…

Cryptography and Security · Computer Science 2020-11-10 Syed Muhammad Kumail Raza , Juan Caballero

This survey paper presents a comprehensive analysis of crime prediction methodologies, exploring the various techniques and technologies utilized in this area. The paper covers the statistical methods, machine learning algorithms, and deep…

Machine Learning · Computer Science 2024-03-05 Kamal Taha

Purpose of our work is to obtain a basic understanding and comparison of the performance and structure of real Knowledge Networks, to identify strengths and weaknesses and to highlight guidelines for improvements. We selected 18 Knowledge…

Social and Information Networks · Computer Science 2014-12-30 Stavroglou Stavros , Antoniou Ioannis

Complex systems, ranging from soft materials to wireless communication, are often organised as random geometric networks in which nodes and edges evenly fill up the volume of some space. Studying such networks is difficult because they…

Probability · Mathematics 2022-07-19 Ivan Kryven , Rik Versendaal

Currently, criminals profile (CP) is obtained from investigators or forensic psychologists interpretation, linking crime scene characteristics and an offenders behavior to his or her characteristics and psychological profile. This paper…

Artificial Intelligence · Computer Science 2010-02-11 Ramesh Kumar Gopala Pillai , Dr. Ramakanth Kumar . P

In general, anomaly detection is the problem of distinguishing between normal data samples with well defined patterns or signatures and those that do not conform to the expected profiles. Financial transactions, customer reviews, social…

Machine Learning · Computer Science 2022-06-10 Paul Irofti , Andrei Patrascu , Andra Baltoiu