Publications with Fulltext

Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/6

Browse

Filters

20223

Advanced Search

Filter by

Settings

Quartile: search.filters.quartile.Q4Subject: search.filters.subject.Artificial intelligence

Search Results

Now showing 1 - 3 of 3
  • Thumbnail Image
    PublicationOpen Access
    Tri-op redactable blockchains with block modification, removal, and insertion
    (TÜBİTAK, 2022) Dousti, Mohammad Sadeq; Department of Computer Engineering; Küpçü, Alptekin; Faculty Member; Department of Computer Engineering; College of Engineering; 168060
    In distributed computations and cryptography, it is desirable to record events on a public ledger, such that later alterations are computationally infeasible. An implementation of this idea is called blockchain, which is a distributed protocol that allows the creation of an immutable ledger. While such an idea is very appealing, the ledger may be contaminated with incorrect, illegal, or even dangerous data, and everyone running the blockchain protocol has no option but to store and propagate the unwanted data. The ledger is bloated over time, and it is not possible to remove redundant information. Finally, missing data cannot be inserted later. Redactable blockchains were invented to allow the ledger to be mutated in a controlled manner. To date, redactable blockchains support at most two types of redactions: block modification and removal. The next logical step is to support block insertions. However, we show that this seemingly innocuous enhancement renders all previous constructs insecure. We put forward a model for blockchains supporting all three redaction operations and construct a blockchain that is provably secure under this formal definition.
  • Thumbnail Image
    PublicationOpen Access
    Stressed or just running? differentiation of mental stress and physical activity by using machine learning
    (TÜBİTAK, 2022) Department of History; Can, Yekta Said; Department of History; College of Social Sciences and Humanities
    Recently, modern people have excessive stress in their daily lives. With the advances in physiological sensors and wearable technology, people's physiological status can be tracked, and stress levels can be recognized for providing beneficial services. Smartwatches and smartbands constitute the majority of wearable devices. Although they have an excellent potential for physiological stress recognition, some crucial issues need to be addressed, such as the resemblance of physiological reaction to stress and physical activity, artifacts caused by movements and low data quality. This paper focused on examining and differentiating physiological responses to both stressors and physical activity. Physiological data are collected in the laboratory environment, which contain relaxed, stressful and physically active states and they are differentiated successfully by using machine learning.
  • Thumbnail Image
    PublicationOpen 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; 168060
    Since 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.