Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Institution Author: search.filters.institutionAuthor.Şahin, Serap

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Now showing 1 - 7 of 7
  • Data Paper
    Citation - WoS: 15
    Citation - Scopus: 20
    Database Covering the Prayer Movements Which Were Not Available Previously
    (Nature Publishing Group, 2023) Mihçin, Şenay; Şahin, Ahmet Mert; Yılmaz, Mehmet; Alpkaya, Alican Tuncay; Tuna, Merve; Akdeniz, Sevinç; Can, Nuray Korkmaz; Tosun, Aliye; Şahin, Serap
    Lower body implants are designed according to the boundary conditions of gait data and tested against. However, due to diversity in cultural backgrounds, religious rituals might cause different ranges of motion and different loading patterns. Especially in the Eastern part of the world, diverse Activities of Daily Living (ADL) consist of salat, yoga rituals, and different style sitting postures. A database covering these diverse activities of the Eastern world is non-existent. This study focuses on data collection protocol and the creation of an online database of previously excluded ADL activities, targeting 200 healthy subjects via Qualisys and IMU motion capture systems, and force plates, from West and Middle East Asian populations with a special focus on the lower body joints. The current version of the database covers 50 volunteers for 13 different activities. The tasks are defined and listed in a table to create a database to search based on age, gender, BMI, type of activity, and motion capture system. The collected data is to be used for designing implants to allow these sorts of activities to be performed.
  • Article
    Citation - WoS: 3
    Citation - Scopus: 4
    A Novel Efficient Method for Tracking Evolution of Communities in Dynamic Networks
    (Institute of Electrical and Electronics Engineers Inc., 2022) Karataş, Arzum; Şahin, Serap
    Tracking community evolution can provide insights into significant changes in community interaction patterns, promote the understanding of structural changes, and predict the evolutionary behavior of networks. Therefore, it is a fundamental component of decision-making mechanisms in many fields such as marketing, public health, criminology, etc. However, in this problem domain, it is an open challenge to capture all possible events with high accuracy, memory efficiency, and reasonable execution times under a single solution. To address this gap, we propose a novel method for tracking the evolution of communities (TREC). TREC efficiently detects similar communities through a combination of Locality Sensitive Hashing and Minhashing. We provide experimental evidence on four benchmark datasets and real dynamic datasets such as AS, DBLP, Yelp, and Digg and compare them with the baseline work. The results show that TREC achieves an accuracy of about 98%, has a minimal space requirement, and is very close to the best performing work in terms of time complexity. Moreover, it can track all event types in a single solution.
  • Conference Object
    Citation - WoS: 38
    Citation - Scopus: 57
    Application Areas of Community Detection: a Review
    (Institute of Electrical and Electronics Engineers Inc., 2019) Karatas, A.; Sahin, S.
    In the realm of today's real world, information systems are represented by complex networks. Complex networks contain a community structure inherently. Community is a set of members strongly connected within members and loosely connected with the rest of the network. Community detection is the task of revealing inherent community structure. Since the networks can be either static or dynamic, community detection can be done on both static and dynamic networks as well. In this study, we have talked about taxonomy of community detection methods with their shortages. Then we examine and categorize application areas of community detection in the realm of nature of complex networks (i.e., static or dynamic) by including sub areas of criminology such as fraud detection, criminal identification, criminal activity detection and bot detection. This paper provides a hot review and quick start for researchers and developers in community detection area. © 2018 IEEE.
  • Article
    Citation - WoS: 2
    Privacy Issues in Post Dissemination on Facebook
    (Türkiye Klinikleri Journal of Medical Sciences, 2019) Sayın, Burcu; Şahin, Serap; Kogias, Dimitrios G.; Patrikakis, Charalampos Z.
    With social networks (SNs) being populated by a still increasing numbers of people who take advantage of the communication and collaboration capabilities that they offer, the probability of the exposure of people's personal moments to a wider than expected audience is also increasing. By studying the functionalities and characteristics that modern SNs offer, along with the people's habits and common behaviors in them, it is easy to understand that several privacy risks may exist, many of which people may be unaware of. In this paper, we focus on users' interactions with posts in a social network (SN), using Facebook as our research domain, and we emphasize some privacy leakages currently existing in Facebook's privacy policy. We also propose a solution to detected privacy issues, featuring a reference implementation of a tool based on a simulation, which visualizes the effect of potential privacy risks on Facebook and directs users to control their privacy. The proposed and simulated tool allows a post owner to observe the spreading area of his or her post depending on the selected privacy settings. Moreover, it provides preliminary feedback for all Facebook users that have interacted with this post, to make them aware of the possible privacy changes, aiming to give them a chance to protect the privacy of their interaction on this post by deleting it when an unwanted privacy change takes place. Finally, an online survey to increase privacy awareness in Facebook usage with over 500 volunteer participants has illuminated the need for such a tool or solution.
  • Conference Object
    Citation - Scopus: 2
    A Comparative Study of Modularity-Based Community Detection Methods for Online Social Networks
    (CEUR Workshop Proceedings, 2018) Karataş, Arzum; Şahin, Serap
    Digital data represent our daily activities and tendencies. One of its main source is Online Social Networks (OSN) such as Facebook, YouTube etc. OSN are generating continuously high volume of data and define a dynamic virtual environment. This environment is mostly represented by graphs. Analysis of OSN data (i.e.,extracting any kind of relations and tendencies) defines valuable information for economic, socio-cultural and politic decisions. Community detection is important to analyze and understand underlying structure and tendencies of OSNs. When this information can be analysed successfully, software engineering tools and decision support systems can produce more successful results for end users. In this study, we present a survey of selected outstanding modularity-based static community detection algorithms and do comparative analysis among them in terms of modularity, running time and accuracy. We use different real-world OSN test beds selected from SNAP dataset collection such as Facebook Ego network, Facebook Pages network (Facebook gemsec), LiveJournal, Orkut and YouTube networks.
  • Article
    Comparison of Group Key Establishment Protocols
    (Türkiye Klinikleri Journal of Medical Sciences, 2017) Şahin, Serap; Aslanoğlu, Rabia
    Recently group-oriented applications over unsecure open networks such as Internet or wireless networks have become very popular. Thus, group communication security over unsecure open networks has become a vital concern. Group key establishment (GKE) protocols are used to satisfy the confidentiality requirement of a newly started communication session by the generation or sharing of an ephemeral common key between the group members. In this study, we analyze the computation and communication efficiency of GKE protocols. Besides confidentiality, the security characteristics of identification and integrity control are also required for all steps of the protocol implementations. Thus, the main contribution of this work is to provide the computation and communication efficiency analysis of the same GKE protocols along with the identification of the group entities and integrity control of messages during the protocol steps. The specific implementation and analysis of GKE protocols are performed by group key agreement (GKA) with pairing- based cryptography and group key distribution (GKD) with verifiable secret sharing, respectively. Finally, a comparison of GKA and GKD protocols on the basis of their strong points and cost characteristics are also provided to inform potential users.
  • Conference Object
    Citation - WoS: 2
    Citation - Scopus: 5
    On Current Trends in Security and Privacy of Cloud Computing
    (Institute of Electrical and Electronics Engineers Inc., 2013) Şahin, Serap
    One of the major components of the Cloud Computing is 'Security and Privacy'. These concerns about security and privacy directly address the trustworthy and reliability levels of a system. The researches and studies about security and privacy on cloud computing are continuing. The aim of this paper is to analyze the privacy and security requirements and highlight new tools and open research topics for cloud computing systems. © 2013 IEEE.