WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Conference Object Citation - WoS: 1Citation - Scopus: 2Integrated Space Domain Awareness and Communication System(IEEE, 2023) Geçgel Çetin, Selen; Özbek, Berna; Karabulut Kurt, GüneşSpace has been reforming and this evolution brings new threats that, together with technological developments and malicious intent, can pose a major challenge. Space domain awareness (SDA), a new conceptual idea, has come to the forefront. It aims sensing, detection, identification and countermeasures by providing autonomy, intelligence and flexibility against potential threats in space. In this study, we first present an insightful and clear view of the new space. Secondly, we propose an integrated SDA and communication (ISDAC) system for attacker detection. We assume that the attacker has advanced communication capabilities to vary attack scenarios, such as random attacks on some receiver antennas. To track random patterns and meet SDA requirements, a lightweight convolutional neural network architecture is developed. The proposed ISDAC system shows superior and robust performance under 12 different super-attacker configurations with a detection accuracy of over 97.8%. © 2023 IEEE.Article Link Prediction for Completing Graphical Software Models Using Neural Networks(IEEE, 2023) Leblebici, Onur; Tuğlular, Tuğkan; Belli, FevziDeficiencies and inconsistencies introduced during the modeling of software systems may result in high costs and negatively impact the quality of all developments performed using these models. Therefore, developing more accurate models will aid software architects in developing software systems that match and exceed expectations. This paper proposes a graph neural network (GNN) method for predicting missing connections, or links, in graphical models, which are widely employed in modeling software systems. The proposed method utilizes graphs as allegedly incomplete, primitive graphical models of the system under consideration (SUC) as input and proposes links between its elements through the following steps: (i) transform the models into graph-structured data and extract features from the nodes, (ii) train the GNN model, and (iii) evaluate the performance of the trained model. Two GNN models based on SEAL and DeepLinker are evaluated using three performance metrics, namely cross-entropy loss, area under curve, and accuracy. Event sequence graphs (ESGs) are used as an example of applying the approach to an event-based behavioral modeling technique. Examining the results of experiments conducted on various datasets and variations of GNN reveals that missing connections between events in an ESG can be predicted even with relatively small datasets generated from ESG models. AuthorConference Object Citation - WoS: 1Citation - Scopus: 1Görgül kip ayrıştırması kullanılarak optik faz kırınımında hassasiyet iyileştirilmesi(IEEE, 2023) Ataç, Enes; Dinleyici, Mehmet SalihPhase diffraction is a potent property used in transparent dielectric film characterization. The measured diffraction pattern on the camera is evaluated by matching numerically computed diffraction patterns to determine the optical properties of the ultra-thin films (refractive index, thickness, etc.). However, the obtained diffraction data is not only a nonlinear and non-stationary signal but also exhibits micron-scale variations, thus limiting the measurement accuracy. Therefore, it is challenging to identify shifts in minima and deviations in amplitude on diffraction data to extract information about the optical properties of phase objects. In this study, it is aimed to improve the thickness sensitivity of the system by applying Empirical Mode Decomposition (EMD) to plane wave-based near-field phase diffraction data. Since EMD is very sensitive to abrupt changes in the signal due to the spatial frequency components, the nanoscale variations in the film thickness become more observable and detectable. Experimental outputs and numerical simulations show that the decomposition increases the thickness sensitivity comparing the classical matching technique.Conference Object Citation - Scopus: 2Parkinson hastalığı sınıflandırmasına yönelik ivmeölçer tabanlı zamanlama analizi(IEEE, 2023) Karaçalı, Bilge; Onay, FatihParkinson's disease is a neurodegenerative disorder caused by dopamine deficiency in the basal ganglia, resulting in cognitive and motor impairments. In this study, accelerometer signals were used to estimate the delay time between the command to start pedaling and the actual movement onset in three groups: healthy individuals (n=13), Parkinson's disease patients (n=13), and patients with freezing of gait symptoms (n=13). Features were extracted from the delay time distributions for each participant and subjected to a triple classification. Linear support vector machine achieved a classification accuracy of 69.2% for all participants. Notably, the average time to start pedaling was found to be significantly different among the three groups, and accelerometer-based timing analysis could be used as a diagnostic tool to assist clinical tests.Conference Object Dalgacık gürültü giderme yöntemiyle mikrodalga bileşen karakterizasyonunun iyileştirilmesi(IEEE, 2023) Karatay, Anıl; Olcay, Bilal Orkan; Yaman, FatihIn this study, an efficient approach is presented to improve the characterization of various microwave components commonly used in communication and radar applications, such as antennas and power dividers. The components were initially simulated and then fabricated using the Computer Simulation Technology (CST) software. Vector Network Analyzer (VNA) measurements of the fabricated components were performed using a low-cost but noisy coaxial cable, and the measurement results were processed using a wavelet-based noise reduction method. For comparison purposes, the Haar and Daubechies-4 (DB4) wavelet functions were applied separately, and the results were examined. It was observed that the correlation and root mean square error between the ideal and measurement results improved in a positive direction with the noise reduction application. This approach provides significant cost and labor advantages, particularly when expensive elements such as gold and silver are used in coaxial cables that are physically free from noise. The experimental and numerical results show good agreement between the ideal simulation results and the filtered measurement results.Conference Object Kurt saldırıları için sentetik irislerde örnek seçilimi(IEEE, 2023) Akdeniz, Eyüp Kaan; Erdoğmuş, NesliIn this study, samples with higher potential to succeed in wolf attacks are picked among synthetically generated iris images, and the composed subset is shown to pose a more significant threat toward an iris recognition system backed by a Presentation Attack Detection (PAD) module with respect to randomly selected samples. Iris images generated by Deep Convolutional Generative Adversarial Networks (DCGAN) are firstly filtered by rejection sampling on PAD score distribution of real iris image PAD scores. Next, the probability of zero success in all attack attempts is calculated for each synthetic iris image, using real iris images in the training set, and match and non-match score distributions are calculated on those. Synthetic images with the lowest probabilities of zero success are included in the final set. Our hypothesis that this set would be more successful in wolf attacks is tested by comparing its spoofing performances with randomly selected sample sets.Conference Object Algıda gecikme ve kısa-ömürlü senkronizasyon temelli yeni bir hayali motor aktivite tanıma yaklaşımı(IEEE, 2023) Olcay, B. Orkan; Karaçalı, BilgeThis study proposes a novel approach for investigating a brain-computer interface that considers the temporal organization of brain activity, explicitly accounting for perception latency. To this end, we aligned the onset of task periods with the concurrence of left parietal and parieto-occipital electrodes to obtain the timings of perception latencies. Then, activity-specific synchronization timings between channel pairs were calculated using the time-aligned task periods. The perception latency and activity-specific synchronization timings were subsequently used for feature extraction and classification. The proposed approach achieved significantly better performance when comparing the proposed approach with the method that did not account for the perception latencyCorrection Corrections To “massive Mimo-Noma Based Mec in Task Offloading for Delay Minimization”(IEEE, 2023) Yılmaz, Saadet Simay; Özbek, Berna[No abstract available]Conference Object A Framework for Physical Layer Network Coding With Multiple Antennas for Bpsk(IEEE, 2023) İlgüy, Mert; Özbek, BernaPhysical layer network coding (PNC) is combined with multiple antennas to increase the spectral efficiency of wireless communication systems. In this work, we present a PNC framework including both uplink and downlink for binary phase shift keying (BPSK). In the uplink, we propose a scheme for detecting network-coded symbol (NCS) with reduced complexity. For the downlink, we propose a transmission scheme of NCS through maximum ratio transmission (MRT) by defining the precoding vector as an average of users' channels. The bit-error-rate (BER) performances and the comparison results with the conventional scheme in both downlink and uplink are provided for the proposed low-complexity PNC framework.Article Citation - WoS: 5Citation - Scopus: 4A New Construction Method for Keystream Generators(IEEE, 2023) Gül, Çağdaş; Kara, OrhunWe introduce a new construction method of diffusion layers for Substitution Permutation Network (SPN) structures along with its security proofs. The new method can be used in block ciphers, stream ciphers, hash functions, and sponge constructions. Moreover, we define a new stream cipher mode of operation through a fixed pseudorandom permutation and provide its security proofs in the indistinguishability model. We refer to a stream cipher as a Small Internal State Stream (SISS) cipher if its internal state size is less than twice its key size. There are not many studies about how to design and analyze SISS ciphers due to the criterion on the internal state sizes, resulting from the classical tradeoff attacks. We utilize our new mode and diffusion layer construction to design an SISS cipher having two versions, which we call DIZY. We further provide security analyses and hardware implementations of DIZY. In terms of area cost, power, and energy consumption, the hardware performance is among the best when compared to some prominent stream ciphers, especially for frame-based encryptions that need frequent initialization. Unlike recent SISS ciphers such as Sprout, Plantlet, LILLE, and Fruit; DIZY does not have a keyed update function, enabling efficient key changing. © 2005-2012 IEEE.