Social network generation and friend ranking based on mobile phone data

Akbaş, Mustafa İlhan; Avula, Raghu Nandan; Bassiouni, Mostafa A.; Turgut, Damla

doi:10.1109/icc.2013.6654714

Cited by 23 publications

(18 citation statements)

References 14 publications

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“…The results have shown strong ties between nodes in the 6-clique and 7-clique based communities. With the same principle, the authors in [12] have used kcliques to understand the structure of a hacker community called Shadowcrew. In addition, with a large scale dataset of offenses reported by law enforcement in Canada, the authors in [13] have applied k-clique with k 3 to identify what they refer to as "co-offending groups"; which is formed by one or more offenders who can be involved in a crime.…”

Section: B Criminal Network Analysismentioning

confidence: 99%

CISRI: A Crime Investigation System Using the Relative Importance of Information Spreaders in Networks Depicting Criminals Communications

Alzaabi

Taha

Martin

2015

IEEE Trans.Inform.Forensic Secur.

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In this paper we propose a forensic analysis system called CISRI that helps forensic investigators determine the most influential members of a criminal group, who are related to known members of the group, for the purposes of investigation. In the CISRI framework, we describe the structural relationships between the members of a criminal group in terms of a graph. In such a graph, a node represents a member of a criminal group, an edge connecting two nodes represents the relationship between two members of the group, and the weight of an edge represents the degree of the relationship between those two members. Using this representation, we propose a method that determines the relative importance of nodes in a graph with respect to a given set of query nodes. Most current approaches that study relative importance determine the relative importance of a node under consideration by estimating the contribution of each query node individually to the importance of this node while overlooking the contribution of the query nodes collectively to the importance of the node under consideration. This may lead to results with low precision. CISRI overcomes this limitation by: (1) computing the contribution of the overall set of query nodes to the importance of a node under consideration, and (2) adopting a tight constraint calculation that considers how much each query node contributes to the relative importance of a node under consideration. This leads to accurate identification of nodes in the graph that are important, in relation to the query nodes. In the framework of CISRI, a graph is constructed from mobile communication records (e.g., phone calls and messages), where a node represents a caller and the weight of an edge reflects the number of contacts between two callers. We evaluated the quality of CISRI by comparing it experimentally with three comparable methods. Our results showed marked improvement.

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Section: B Criminal Network Analysismentioning

confidence: 99%

CISRI: A Crime Investigation System Using the Relative Importance of Information Spreaders in Networks Depicting Criminals Communications

Alzaabi

Taha

Martin

2015

IEEE Trans.Inform.Forensic Secur.

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“…Akbas et al, proposed a friends ranking algorithm which assigns weights to the durations of the calls, video conferences, face-to-face meetings and the sizes of the emails and texts and then depending on the value it finds the friendship levels [16].…”

Section: Related Workmentioning

confidence: 99%

Rating Of The Relationship Between Users Using The Data From The Implemented Mobile Forensic Software

Berber¹,

Küçüksille²

2020

Pamukkale J Eng Sci

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ÖzDuring the digital forensic process, different software and hardware tools are used. The devices from which the digital evidences are collected have been varied in parallel with the developments in technology. The issue of identifying the mobile phone owner's friends and assessing his relationship with them with the help of digital evidences collected from the Android mobile phones has been studied in the literature and it is still under investigation. The software developed in this work enables accessing a variety of data that have evidential value in the court proceedings; these include physical and logical acquisition of images from mobile phones with Android operating system, extracting images for investigations, examining different file types in images, and databases. This software can collect and examine the evidences and then produce reports. At the same time, it can identify criminals or people with potentially have connections to those people whose accounts are under investigations by using developed analysis model which examines the relationships between social media applications` data, phone contacts and calling histories collected from the mobile devices. In this work, the evidences examined by using a novel software developed by the authors which performs multiple tasks using a single interface and the corresponding results are presented.Adli bilişim sürecinde çok çeşitli yazılımlar ve donanımlar kullanılmaktadır. Teknolojinin hızlı gelişimine paralel olarak dijital delillerin toplandığı cihazlar da hızla çeşitlenmektedir. Android mobil telefonlardan toplanan dijital deliller yardımı ile bu telefona sahip kişinin arkadaşlarının ve bu arkadaşları ile ilişkilerinin derecelendirilerek tespit edilmesi, literatürde çalışılmış ve üzerinde çalışılmaya devam eden konulardan biridir. Bu çalışmada geliştirilen yazılım, Android işletim sistemine sahip mobil cihazlardan fiziksel ve mantıksal imaj alma, imajın incelenmek üzere açılması, imaj içinde farklı dosya türlerinin incelenmesi, veri tabanı incelemeleri gibi dijital delil niteliği taşıyan birçok veriye erişilmesini sağlamaktadır. Delil elde etme, delilleri inceleme ve raporlama işlemlerini yapabilen bu yazılım aynı zamanda geliştirilen analiz modeliyle mobil cihazlardan elde edilen sosyal medya uygulama verileri, telefon rehberi ve görüşme kayıtları arasındaki ilişkileri inceleyerek suçlunun veya hesapları incelenen kişilerin, ilişkili olma ihtimali yüksek kişileri tespit edebilmektedir. Birçok işlemi tek bir ara yüzden yapabilmesi ve veri analiz yöntemi bakımından, özgün bir çalışma olarak gerçekleştirilen yazılımla incelenen deliller ve elde edilen bulgular bu çalışmada sunulmuştur.

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“…The authors demonstrated strong ties among vertices in each clique. Similarly, the authors of [30] employed the k-clique technique to investigate the relationships among a community of hackers called Shadowcrew.…”

Section: Ieee Transactions On Information Forensics and Securitymentioning

confidence: 99%

“…A large number of methods have been developed in recent years for determining the relative importance of vertices. Most of these methods employ standard network metrics techniques, k-clique techniques [20,23,30], or semantic similarities techniques [8].…”

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confidence: 99%

SIIMCO: A Forensic Investigation Tool for Identifying the Influential Members of a Criminal Organization

Taha

Yoo

2016

IEEE Trans.Inform.Forensic Secur.

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Abstract-Members of a criminal organization, who hold central positions in the organization, are usually targeted by criminal investigators for removal or surveillance. This is because they play key and influential roles by acting as commanders who issue instructions or serve as gatekeepers. Removing these central members (i.e., influential members) is most likely to disrupt the organization and put it out of business. Most often, criminal investigators are even more interested in knowing the portion of these influential members, who are the immediate leaders of lower-level criminals. These lower-level criminals are the ones who usually carry out the criminal works; therefore, they are easier to identify. The ultimate goal of investigators is to identify the immediate leaders of these lower-level criminals in order to disrupt future crimes. We propose in this paper a forensic analysis system called SIIMCO that can identify the influential members of a criminal organization. Given a list of lower-level criminals in a criminal organization, SIIMCO can also identify the immediate leaders of these criminals. SIIMCO first constructs a network representing a criminal organization from either Mobile Communication Data that belongs to the organization or from crime incident reports. It adopts the concept space approach to automatically construct a network from crime incident reports. In such a network, a vertex represents an individual criminal and a link represents the relationship between two criminals. SIIMCO employs formulas that quantify the degree of influence/importance of each vertex in the network relative to all other vertices. We present these formulas through a series of refinements. All the formulas incorporate novel-weighting schemes for the edges of networks. We evaluated the quality of SIIMCO by comparing it experimentally with two other systems. Results showed marked improvement.

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Social network generation and friend ranking based on mobile phone data

Cited by 23 publications

References 14 publications

CISRI: A Crime Investigation System Using the Relative Importance of Information Spreaders in Networks Depicting Criminals Communications

CISRI: A Crime Investigation System Using the Relative Importance of Information Spreaders in Networks Depicting Criminals Communications

Rating Of The Relationship Between Users Using The Data From The Implemented Mobile Forensic Software

SIIMCO: A Forensic Investigation Tool for Identifying the Influential Members of a Criminal Organization

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