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Exploring behavioral information security networks in an organizational context: An empirical case study
بررسی شبکه های امنیتی اطلاعات رفتاری در یک زمینه سازمانی: مطالعه موردی تجربی-2017
Article history:Available online 14 July 2016Keywords:Social network analysis Security behavior Security compliance Security inﬂuence Organizational behaviorThe purpose of this research is to propose network research as an alternative approach in the behavioral security ﬁeld. A case study was conducted in a large interior contractor to explore eight organizational networks, four of which focus on security behaviors. The researchers employed social network analysis methods, including quantitative and qualitative ones, to analyze the case study’s data and demonstrate the analytical capability of the network analysis approach in the behavioral security ﬁeld. Key features of the security networks’ structures include high transitivity, hierarchy, and centralization, whereas reci- procity and density are lower than other organizational networks. Moreover, work-related interactions were found to impact security inﬂuence, among which giving IT advice increases signiﬁcantly one’s in- ﬂuential status in security matters. Practical implications include suggestions about the use of network analysis methods as a tool for security managers to monitor their behavioral security networks and de- vise appropriate strategies. Potential research directions are also elaborated, which future research can employ and promote the novel and practical use of network analysis techniques.© 2016 Elsevier Ltd. All rights reserved.
Keywords: Social network analysis | Security behavior | Security compliance | Security influence | Organizational behavior
A structured methodology for deploying log management in WANs
یک روش ساخت یافته برای استقرار مدیریت ورود به سیستم در شبکه های WAN-2017
Article history:Available online 6 March 2017Keywords:Log management Security monitoring SIEMSocial network analysisThe collection of log data is a challenging operation for organizations that wish to monitor their infras- tructure for security reasons. In this paper a methodology for the implementation of a log management infrastructure for real-time security monitoring on a large scale infrastructure is proposed. Related meth- ods are adjusted and adopted to compose parts of the proposed methodology, avoiding to “re-invent the wheel” where possible. Social network analysis is employed to make and justify decisions that were for- merly performed either intuitively or based on experience and vendors’ best practices. The methodology concludes with the creation of a repository of the necessary data. The result is an innovative methodol- ogy that can be used as a step-by-step guide for the implementation of a log management infrastructure in an organization. The proposed methodology is applied to a real WAN.© 2017 Elsevier Ltd. All rights reserved.
Keywords: Log management | Security monitoring | SIEM | Social network analysis
Feasibility Study of Social Network Analysis on Loosely Structured Communication Networks
امکان سنجی تحلیل شبکه اجتماعی بر روی شبکه های ارتباطی ساختاریافته آزاد-2017
Organised criminal groups are moving more of their activities from traditionally physical crime into the cyber domain; where they form online communities that are used as marketplaces for illegal materials, products and services. The trading of illicit goods drives an underground economy by providing services that facilitate almost any type of cyber crime. The challenge for law enforcement agencies is to know which individuals to focus their efforts on, in order to effectively disrupting the services provided by cyber criminals. This paper present our study to assess graph-based centrality measures’ performance for identifying important individuals within a criminal network. These measures has previously been used on small and structured general social networks. In this study, we are testing the measures on a new dataset that is larger, loosely structured and resembles a network within cyber criminal forums. Our result Organised criminal groups are moving more of their activities from traditionally physical crime into the cyber domain; where they form online communities that are used as marketplaces for illegal materials, products and services. The trading of illicit goods drives an underground economy by providing services that facilitate almost any type of cyber crime. The challenge for law enforcement agencies is to know which individuals to focus their efforts on, in order to effectively disrupting the services provided by cyber criminals. This paper present our study to assess graph-based centrality measures’ performance for identifying important individuals within a criminal network. These measures has previously been used on small and structured general social networks. In this study, we are testing the measures on a new dataset that is larger, loosely structured and resembles a network within cyber criminal forums. Our result shows that well established measures have weaknesses when applied to this challenging dataset.
Keywords: Digital forensics | Social network analysis | Centrality measures | Criminal networks
Egocentric social network correlates of physical activity
شبکه اجتماعی خود محور وابسته به فعالیت فیزیکی-2017
Background: The social environment might play an important role in explaining people’s physical activity (PA) behavior. However, little is known regarding whether personal networks differ between physically active and physically inactive people. This study aimed to examine the relationship between personal network characteristics and adults’ physical (in)activity. Methods: An egocentric social network study was conducted in a random sample in Switzerland (n = 529, mean age of 53 years, 54% females). Individual and personal network measures were compared between regular exercisers and non-exercisers. The extent of these factors’ association with PA levels was also examined. Results: Non-exercisers (n = 183) had 70% non-exercising individuals in their personal networks, indicating homogeneity, whereas regular exercisers (n = 346) had 57% regularly exercising individuals in their networks, meaning more heterogeneous personal networks. Additionally, having more regular exercisers in personal networks was associated with higher PA levels, over and above individual factors. Respondents with an entirely active personal network reported, on average, 1 day of PA more per week than respondents who had a completely inactive personal network. Other personal network characteristics, such as network size or gender composition, were not associated with PA. Conclusion: Non-exercisers seem to be clustered in inactive networks that provide fewer opportunities and resources, as well as less social support, for PA. To effectively promote PA, both individuals and personal networks need to be addressed, particularly the networks of inactive people (e.g., by promoting group activities).
Keywords: Egocentric network | Exercise | Inactivity | Personal network | Physical activity | Questionnaire | Similarity/Homogeneity
Evaluation of an integrated mobile payment, route planner and social network solution for public transport
ارزیابی یک پرداخت یکپارچه تلفن همراه، برنامه ریز مسیر و راه حل شبکه های اجتماعی برای حمل و نقل عمومی-2017
The proliferation of new technologies is revolutionizing the public transport sector, allowing Operators to replace complex and expensive infrastructures by travellers’ mobile devices and online management channels and platforms. This paper aims to present the Seamless Mobility platform, a disruptive solution based on these new channels, which main goal is to facilitate and promote public transport usage for travellers, as well as reducing operational costs for public transport companies. The Seamless Mobility platform integrates three main components: (i) mobile payments, (ii) route planner, and (iii) social network. The payment component is based on the pay-as-you-go concept with check-in and check-out requiring the reading of the corresponding QR Code station. The route planner combines information from published schedules with real-time information to identify the nearest stops, the next departures, or the best route for a scheduled trip. The social network component allows real time sharing among travellers of public transport information, related to several aspects of the service (e.g. noise, skilfulness of drivers). To test the concept, a mobile application, called OneRide, was developed. This application was tested by users in real environment, in the city of Porto, Portugal. The results show that users considered the system extremely useful, since it is more convenient than traditional systems. It was also clear that users valued the integration of additional and complementary services with mobile payments, such as information about their journey, maps and schedules. Regarding the social component some users found it difficult to understand the concept, but once they understood they considered it very useful. The use of the QR Codes to perform the payment has shown to be one of the main challenges to be addressed, since lighting conditions, position and distance to the QR Code influences the reading process.
Keywords: Mobile payments | journey planner | social network | public transport | seamless mobility
From frequency of use to social integration: The mediation of routinization and infusion in Tuenti community
از فرکانس استفاده به ادغام اجتماعی: میانجیگری روتینیزاسیون و تزریق در جامعه Tuenti-2017
This study examines post-adoption behaviors (i.e., frequency of use, routinization and infusion) and their effects on the sense of community in the domain of social network sites. In particular, this contribution formulates mediation hypotheses, which posit how frequency of use affects social integration via rou tinization and infusion. The data was collected from 278 users of Tuenti, a highly-popular social network site among the Spanish college student population during the period 2006–2012. Results from partial least squares structural equation modeling (PLS-SEM) show these sophisticated types of usage are inter related in such a way that routinization and infusion (a) fully mediate the effect of frequency of use on social integration; and (b) exert significant influences on social integration, as an active sense of belong ingness to a social network site. In order to attain social integration, it is therefore essential for managers to devise strategies to foster advanced post-adoption behaviors.
Keywords: Frequency of use | Routinization | Infusion | Social integration | Social network sites | Partial least squares
The Social Relation Key: A new paradigm for security
کلید ارتباط اجتماعی: یک نمونه جدید برای امنیت-2017
Article history:Received 23 June 2017Revised 7 July 2017Accepted 7 July 2017Available online 18 July 2017Keywords:Online social network Security keySMSTwitter SpamAuthenticationFor the last decade, online social networking services have consistently shown explosive annual growth, and have become some of the most widely used applications and services. Large amounts of social re- lation information accumulate on these platforms, and advanced services, such as targeted advertising and viral marketing, have been introduced to exploit this social information. Although many prior social relation-based services have been commerce oriented, we propose employing social relations to improve online security. Speciﬁcally, we propose that real social networks possess unique characteristics that are diﬃcult to imitate through random or artiﬁcial networks. Also, the social relations of each individual are unique, like a ﬁngerprint or an iris. These observations thus lead to the development of the Social Rela- tion Key (SRK) concept. We applied the SRK concept in different use cases in the real world, including in the detection of spam SMSes, and another in pinpointing fraud in Twitter followers. Since spammers multicast the same SMS to multiple, randomly-selected receivers and normal users multicast an SMS to friends or acquaintances who know each other, we devise a detection scheme that makes use of a clustering coeﬃcient. We conducted a large scale experiment using an SMS log obtained from a major cellular network operator in Korea, and observed that the proposed scheme performs signiﬁcantly better than the conventional content-based Naive Bayesian Filtering (NBF). To detect fraud in Twitter followers, we use different social network signatures, namely isomorphic triadic counts, and the property of social status. The experiment based on a Twitter dataset again conﬁrmed the feasibility of the SRK. Our codes are available on a website1 .© 2017 Published by Elsevier Ltd.
Keywords: Online social network | Security key | SMS | Twitter | Spam | Authentication
Applying network analysis to investigate interpersonal influence of information security behaviours in the workplace
با استفاده از تجزیه و تحلیل شبکه برای بررسی نفوذ بین فردی رفتارهای امنیتی اطلاعات در محل کار-2017
As organisations are developing people-centric security workplaces, where proactive security behaviours are fostered, it is important to understand more about the sources of security inﬂuence. This research applied social network analysis methods to investigate security inﬂuence within a large interior contractor in Vietnam. The ﬁndings revealed that security inﬂuence occurs between employees in the same department, particularly those in senior positions, have longer tenure or younger age. Engagement in daily work and security-related activities can also increase the likelihood of inﬂuencing security behaviours. Moreover, the security inﬂuence network is transitive and has a hierarchical structure.© 2016 Elsevier B.V. All rights reserved.
Keywords:Security compliance | Security behaviour | Security management | Interpersonal influence | Social network analysis | Exponential random graph modelling
Real-time event detection for online behavioral analysis of big social data
تشخیص رویداد زمان واقعی برای تجزیه و تحلیل رفتار آنلاین از داده های اجتماعی بزرگ-2017
Social networking services are becoming increasingly popular during the daily lives of Internet citizens, especially since the advent of smart mobile devices with integrated utility modules such as 4G/WIFI connectivity, global positioning services, cameras, and heart beat sensors. Many devices are available for sharing information at any time, which can be listed by posting a photo, sharing a status, or narrating an event. The behavior of users means that the flow of data (or a social data stream) has real-time characteristics, which actually comprise notifications about your friends’ posts after a short delay for diffusion over the network. The data stream contains news pieces related to real social facts as well as unfocused information. In addition, important information (or events) attracts more public attention, which is demonstrated by the number of relevant messages or communication interactions between people interested in specific topics. From a technical perspective, the characteristics of data in the aforementioned scenario provide us with an opportunity to construct a model that can automatically determine the occurrence of events based on a social data stream. In this study, we propose an approach to solve the problem of early event identification, which requires appropriate approaches for processing incoming data in terms of the processing performance and number of data.
Keywords:Event detection | Real-time event detection | Social network analysis
Teenage peer-to-peer knowledge sharing through social network sites in secondary schools
به اشتراک گذاری دانش نظیر به نظیر بین نوجوانان از طریق سایت های شبکه اجتماعی در مدارس متوسطه-2017
The promise of social network technology for learning purposes has been heavily debated, with proponents highlighting its transformative and opponents its distracting potential. However, little is known about the actual, everyday use of ubiquitous social network sites for learning and study purposes in secondary schools. In the present work, we present findings from two survey studies on representative samples of Israeli, Hebrew-speaking teenagers (N1 ¼ 206 and N2 ¼ 515) which explored the scope, characteristics and rea sons behind such activities. Study 1 shows that these can be described best as online knowledge sharing, that is: the up- and downloading of knowledge and knowledge sources to social network-based peer groups. Findings were replicated in study 2 to further support the claim that school-related knowledge sharing is common and widespread and entails different types of knowledge. Findings from study 2 furthermore show that sharing is mainly motivated by prosocial motives, as well as expectations for future reciprocation. Sharing is predicted by individual differences, such as gender, collectivist values, mastery goal orientations and academic self-efficacy. Relations between competitive-individualist values and sharing are more complex, and are, among others, moderated by expecta tions for future benefits. Implications for educational practices and for learning are discussed.
Keywords: Knowledge sharing | Secondary schools | Social network sites | Motivations | Peer collaboration