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Publication Metadata only A reputation-based privacy management system for social networking sites(TÜBİTAK, 2013) Yüksel, Mehmet Erkan; Yüksel, Asım Sinan; Department of Computer Engineering; Faculty Member; Department of Computer Engineering; College of Engineering; 8693Social networking sites form a special type of virtual community where we share our personal information with people and develop new relationships on the Internet. These sites allow the users to share just about everything, including photos, videos, favorite music, and games, and record all user interactions and retain them for potential use in social data mining. This storing and sharing of large amounts of information causes privacy problems for the users of these websites. In order to prevent these problems, we have to provide strict privacy policies, data protection mechanisms, and trusted and built-in applications that help to protect user privacy by limiting the people who get access to a user's personal information. Thus, the privacy problem has prompted us to provide a solution that o ers the users of these social networking websites an opportunity to protect their information. In this paper, a social networking application and its system design, algorithm, and database structure are described. Our application o ers a reputation-based trusted architecture to social network users. It creates and monitors social reputations, nds social circles, and helps the users to group their friends easily, meaningfully, and automatically to protect their privacy. This system provides the grouping of users through an automated system into di erent social circles by analyzing the user's social connections depending on what common information or application they share that should not be accessed by other users.Publication Metadata only Access pattern-aware data placement for hybrid DRAM/NVM(TUBITAKScientific and Technical Research Council Turkey, 2017) Department of Computer Engineering; Erten, Didem Unat; Faculty Member; Department of Computer Engineering; College of Engineering; 219274in recent years, increased interest in data-centric applications has led to an increasing demand for large capacity memory systems. Nonvolatile memory (NVM) technologies enable new opportunities in terms of process-scaling and energy consumption, and have become an attractive memory technology that serves as a secondary memory at low cost. However, NVM has certain disadvantages for write references, due to its high dynamic energy consumption for writes and low bandwidth compared to DRaM writes. in this paper, we propose an access-aware placement of objects in the application code for two types of memories. Given the desired power savings and acceptable performance loss, our placement algorithm suggests candidate variables for NVM. We present an evaluation of the proposed technique on two applications and study the energy and performance consequences of different placements.Publication Open Access BlockSim-Net: a network-based blockchain simulator(TÜBİTAK, 2022) Ramachandran, Prashanthi; Agrawal, Nandini; Department of Computer Engineering; Biçer, Osman; Küpçü, Alptekin; Faculty Member; Department of Computer Engineering; College of Engineering; Graduate School of Sciences and Engineering; N/A; 168060Since its proposal by Eyal and Sirer (CACM '13), selfish mining attacks on proof-of-work blockchains have been studied extensively. The main body of this research aims at both studying the extent of its impact and defending against it. Yet, before any practical defense is deployed in a real world blockchain system, it needs to be tested for security and dependability. However, real blockchain systems are too complex to conduct any test on or benchmark the developed protocols. Instead, some simulation environments have been proposed recently, such as BlockSim (Maher et al., SIGMETRICS Perform. Eval. Rev. '19), which is a modular and easy-to-use blockchain simulator. However, BlockSim's structure is insufficient to capture the essence of a real blockchain network, as the simulation of an entire network happens over a single CPU. Such a lack of decentralization can cause network issues such as propagation delays being simulated in an unrealistic manner. In this work, we propose BlockSim-Net, a modular, efficient, high performance, distributed, network-based blockchain simulator that is parallelized to better reflect reality in a blockchain simulation environment.Publication Metadata only Large language models as a rapid and objective tool for pathology report data extraction(Federation Turkish Pathology Soc., 2024) Department of Computer Engineering; Bolat, Beyza; Eren, Özgür Can; Dur Karasayar, Ayşe Hümeyra; Meriçöz, Çisel Aydın; Demir, Çiğdem Gündüz; Kulaç, İbrahim; Department of Computer Engineering; Koç Üniversitesi İş Bankası Enfeksiyon Hastalıkları Uygulama ve Araştırma Merkezi (EHAM) / Koç University İşbank Center for Infectious Diseases (KU-IS CID); Koç Üniversitesi İş Bankası Yapay Zeka Uygulama ve Araştırma Merkezi (KUIS AI)/ Koç University İş Bank Artificial Intelligence Center (KUIS AI); Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); School of Medicine; Graduate School of Health Sciences; College of EngineeringMedical institutions continuously create a substantial amount of data that is used for scientific research. One of the departments with a great amount of archived data is the pathology department. Pathology archives hold the potential to create a case series of valuable rare entities or large cohorts of common entities. The major problem in creation of these databases is data extraction which is still commonly done manually and is highly laborious and error prone. For these reasons, we offer using large language models to overcome these challenges. Ten pathology reports of selected resection specimens were retrieved from electronic archives of Ko & ccedil; University Hospital for the initial set. These reports were de-identified and uploaded to ChatGPT and Google Bard. Both algorithms were asked to turn the reports in a synoptic report format that is easy to export to a data editor such as Microsoft Excel or Google Sheets. Both programs created tables with Google Bard facilitating the creation of a spreadsheet from the data automatically. In conclusion, we propose the use of AI-assisted data extraction for academic research purposes, as it may enhance efficiency and precision compared to manual data entry.Publication Metadata only Longitudinal attacks against iterative data collection with local differential privacy(Tubitak Scientific & Technological Research Council Turkey, 2024) Department of Computer Engineering; Gürsoy, Mehmet Emre; Department of Computer Engineering; College of EngineeringLocal differential privacy (LDP) has recently emerged as an accepted standard for privacy -preserving collection of users' data from smartphones and IoT devices. In many practical scenarios, users' data needs to be collected repeatedly across multiple iterations. In such cases, although each collection satisfies LDP individually by itself, a longitudinal collection of multiple responses from the same user degrades that user's privacy. To demonstrate this claim, in this paper, we propose longitudinal attacks against iterative data collection with LDP. We formulate a general Bayesian adversary model, and then individually show the application of this adversary model on six popular LDP protocols: GRR, BLH, OLR, RAPPOR, OUE, and SS. We experimentally demonstrate the effectiveness of our attacks using two metrics, three datasets, and various privacy and domain parameters. The effectiveness of our attacks highlights the privacy risks associated with longitudinal data collection in a practical and quantifiable manner and motivates the need for appropriate countermeasures.Publication Metadata only Network traffic properties of bimodal multicast protocol(TÜBİTAK, 2003) N/A; Department of Computer Engineering; Department of Mathematics; Özkasap, Öznur; Çağlar, Mine; Faculty Member; Faculty Member; Department of Computer Engineering; Department of Mathematics; College of Engineering; College of Sciences; 113507; 105131The popularity of large-scale distributed applications, such as videoconferencing, multimedia dissemination, electronic stock exchange and distributed cooperative work, has grown with the availability of high-speed networks and the expansion of the Internet. The key property of this type of applications is the need to distribute data among multiple participants together with an application-specific quality of service needs. This fact makes scalable multicast protocols an essential underlying communication structure. Although there exist several studies investigating the traffic characteristics of unicast communication, multicast traffic has not been examined extensively in previous studies. It is well known that the aggregate traffic properties of self-similarity and long-range dependence are ubiquitous in wide area networks and lead to adverse consequences in network performance. In this study, we analyze traffic characteristics of a novel scalable, reliable multicast protocol, Bimodal Multicast (Pbcast). In particular, our simulation studies demonstrate that epidemic approach of Bimodal Multicast generates short-range dependent traffic with low overhead traffic and transport delays. We elaborate on the protocol mechanisms as an underlying factor in our empirical results.