A taxonomy-based model of security and privacy in online social networks

Caviglione, Luca; Coccoli, Mauro; Merlo, Alessio

doi:10.1504/ijcse.2014.060717

Cited by 20 publications

(9 citation statements)

References 37 publications

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“…It is imperative to recognize social engineering attempts in their early stages with a proactive security and contingency plan. From a management perspective, multifactor authentication security policies strengthen defense mechanisms for the firm [40][41][42]. A defense mechanism against social engineering attacks is comprised of detection systems in various devices, adjustment of browser settings, and usage of anti-spyware in the network [43].…”

Section: Defense Mechanismsmentioning

confidence: 99%

“…Social engineering attacks in the form of malware that links to the operating system also have the ability to impact the performance of the devices, as in the case of battery draining attacks. Furthermore, attackers through gaming applications on mobile devices also have the capability to conduct traffic flooding attacks in the form of messages and pings or even crashing the system to prevent legitimate users from conducting their work [41].…”

Section: Mobilementioning

confidence: 99%

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A Taxonomy for Social Engineering Attacks via Personal Devices

Aldawood¹,

Skinner²

2019

IJCA

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Social engineering attacks are a major threat to organizations and individuals as digitization and connectivity through the internet increase. This study aims to review scholarly research analyzing the topic of social engineering and further chart the evolution of the threat. The review identifies methods of such attacks on various platforms and devices and discusses motivations behind social engineering attacks. Finally, the paper analyzes the nature and impact of social engineering attacks and presents a taxonomy on socially engineered attacks by analyzing their anatomy.

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Section: Defense Mechanismsmentioning

confidence: 99%

Section: Mobilementioning

confidence: 99%

A Taxonomy for Social Engineering Attacks via Personal Devices

Aldawood¹,

Skinner²

2019

IJCA

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“…The main purpose of this web application is mining contents of the most popular SNSs (e.g., Facebook and Twitter, also exploiting their known privacy flaws [22], [23]) investigating possible threatening messages, in order to recognize the profile of a bully and report it to the community. This concept is already implemented in the popular application ReThink, which keeps trace of outgoing messages.…”

Section: B Sbulloniamocimentioning

confidence: 99%

Teaching Computer Programming Through Hands-on Labs on Cognitive Computing

Coccoli

Maresca

Stanganelli

2016

International Conferences on Distributed Multimedia Systems

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Abstract-In this work we report more recent results of a longlasting educational project that we have been carrying on for several years and is evolving continuously. The objective of the mentioned project is making students work on the production of small, yet full featured, software prototypes with a collaborative approach, in a dedicated development environment with suited tools and facilities. At the same time, we seek to lay the foundations to build a pragmatic model to teach cognitive computing programming. We conducted such experience in a programming course at the University of Naples "Federico II" exploiting a software development environment based on the Platform as a Service (PaaS). This made possible to perform a set of cooperative learning activities that we used to demonstrate practically some theoretical concepts, also stressing the use of cognitive computing tools, which introduce a new way of thinking the software design process. From its inception, this educational project has involved a relevant number of students, which has been growing continuously, year after year. At our first attempts, students were assigned a specific activity, which was expected to be concluded within one year. Then, as new classes arrived, we have seen that it was possible to start new activities starting from the precedent achievements, thus requiring further evolutions of the available prototypes. This allowed creating more complex and complete projects, as new tools and services were made available, carrying new opportunities. In the present release, such evolutionary path has led to using the IBM Bluemix platform with its wide range of components, including Watson that is devoted to cognitive computing. This work goes in the direction of developing the smart university model, by using innovative and intelligent services to help raising a new generation of software engineers but also to promote and disseminate a new way for designing and building innovative applications.

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“…Online Social Networks (OSNs) enable users to have more freedom and proximity in keeping in touch with their friends and in expanding their social contacts. However, they also create serious privacy concerns given the personal nature of information users share over them on almost a daily basis [7] [3]. Users publish their personal stories and updates, as they might also express their opinion by interacting on information shared by others, but, in most cases, they are not fully aware of the size of the audience that gets access to their information.…”

Section: Introductionmentioning

confidence: 99%

LAMP - Label-Based Access-Control for More Privacy in Online Social Networks

Bahri¹,

Carminati²,

Ferrari³

et al. 2016

Information Security Theory and Practice

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Access control in Online Social Networks (OSNs) is generally approached with a relationship-based model. This limits the options in expressing privacy preferences to only the types of relationships users establish in the OSN. Moreover, current proposals do not address the privacy of dependent information types, such as comments or likes, at their atomic levels of ownership. Rather, the privacy of these data elements is holistically dependent on the aggregate object they belong to. To overcome this, we propose LAMP, a model that deploys fine grained labelbased access control for information sharing in OSNs. Users in LAMP assign customized labels to their friends and to all types of their information; whereas access requests are evaluated by security properties carefully designed to establish orders between requestor's and information's labels. We prove the correctness of the suggested model, and we perform performance experiments based on different access scenarios simulated on a real OSN graph. We also performed a preliminary usability study that compared LAMP to Facebook privacy settings. Walt Mike Dima Javier Lina Family colleagues  Only family members (but all of them) will access photos  Only colleagues (but all of them) will access the video

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A taxonomy-based model of security and privacy in online social networks

Cited by 20 publications

References 37 publications

A Taxonomy for Social Engineering Attacks via Personal Devices

A Taxonomy for Social Engineering Attacks via Personal Devices

Teaching Computer Programming Through Hands-on Labs on Cognitive Computing

LAMP - Label-Based Access-Control for More Privacy in Online Social Networks

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