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Öğe A Broad Overview of GPS Fundamentals: Now and Future(Ieee, 2017) Vatansever, Saffet; Bütün, İsmailGPS (Global Positioning System) is a satellite based navigation system and is used in a variety of applications such as mapping, vehicle navigation and surveying. In this work, a detailed background of GPS is included. First, historical development of GPS technology is provided. This is followed by a detailed theoretical background of GPS and GNSS (Global Navigation Satellite System). Afterwards, the topics of "GPS estimation error" and "increasing GPS position accuracy" are covered. Then, various counterparts of GPS technology, developed by rival countries are discussed. Finally, future expectations of scientific world from the GNSS technology are presented.Öğe A Review of Electrical Network Frequency (ENF) Based Applications in Media Forensics(Institute of Electrical and Electronics Engineers Inc., 2023) Gunes, Ahmet Seyfullah; Vatansever, SaffetElectricity network frequency (ENF) is the frequency of electrical voltage transmitted by power distribution lines, with a nominal value of 50 Hz in most of the world and a nominal value of 60 Hz in the vast majority of America. The ENF makes continuous oscillations within certain limits around the nominal value depending on the supply-demand power imbalance in the network. These time-dependent changes in ENF are called the ENF signal. Although the ENF signal may show similarities in short time intervals, it becomes unique in large time intervals. The ENF signal is intrinsically integrated into audio and video recordings under certain conditions. The fact that the ENF signal shows different characteristics in different networks and is unique depending on time allows researchers to make inferences about the file content integrity, together with the location and time information of the audio and video files. In this study, it is discussed how to detect modifications in the file content and metadata using ENF within the scope of ENF-based forensic analysis of audio and video. In this context, existing ENF applications in the literature and the potential ENF usage areas are examined and analyzed. © 2023 IEEE.Öğe A Survey of Source Camera Attribution Applications Using PRNU(Institute of Electrical and Electronics Engineers Inc., 2023) Gunes, Ahmet Seyfullah; Vatansever, SaffetPRNU (Photo Response Non-Uniformity) is a sensor noise component that arises from the non-homogeneous structure of the semiconductor materials used in the production of image sensors, physical differences during the sensor manufacturing stage, and other unpredictable irregularities and defects. The PRNU characteristic differs among camera sensors, even within the same brand and model, and remains constant over time. In other words, it possesses a unique quality for each camera sensor. PRNU unintentionally embeds itself in every captured image, much like a fingerprint. Thanks to these features, PRNU enables various forensic applications for image and video, including source camera identification, file integrity verification, and forgery detection. This study presents an examination of PRNU-based source camera detection, which is the most common application of PRNU. Different scenarios in recordings of various resolutions and stabilized videos are discussed separately. © 2023 IEEE.Öğe A Thorough Investigation Into the ENF Reconstruction in Videos Exposed by Rolling Shutter(Ieee-Inst Electrical Electronics Engineers Inc, 2023) Vatansever, SaffetIn electric network frequency (ENF)-based video forensics, the analysis of videos captured by rolling shutter systems, where each row of a frame is exposed at different time instances, is critical. To gain the advantage of increased sampling frequency in these videos, in contrast to those captured by the global shutter where an entire frame is exposed at a time, the ENF-related luminance signal that is essential for ENF estimation is built by concatenating ENF-related luminance estimates across consecutive frames. However, this approach brings about some issues or phenomena owing to an idle period at the end of each frame. First, the ENF harmonics may be replaced by new ENF components and attenuated, thereby affecting the reliability of the ENF estimates from these videos. Another critical phenomenon is ENF reversal, which is yet to receive much research. This study comprehensively investigates this phenomenon to explore how and under what conditions the ENF is reversed. Further investigations led this study to examine how the ENF in the emerging components is mainly reconstructed from multiple ENF-related luminance harmonics, depending on the idle period. This helps identify reliable ENF components from which the ENF signal can be accurately estimated. In addition, it reveals the optimal idle periods for any ENF component. Using this outcome, this study also proposes a technique to enhance the effectiveness of an ENF component based on idle period modification. The experimental results show that the proposed method may boost the efficiency of an unreliable ENF component, outperforming the existing techniques.Öğe An Enhanced STFT Segmentation Framework for ENF-Based Media Forensics(Ieee-Inst Electrical Electronics Engineers Inc, 2024) Berk Yalinkilic, Ali; Vatansever, SaffetThe electric network frequency (ENF) criterion has gained significant attention over the past two decades as a promising tool in digital media forensics. ENF is the frequency of the alternating current (AC) signal in a mains electricity network, exhibiting continual fluctuations within certain limits around a nominal frequency, contingent upon supplied and demanded power disparities. A sequence of ENF alterations is called an ENF signal, which is inherently embedded in audio and video recordings under certain circumstances. Several efforts have been made to accurately estimate the ENF signal from media. However, no matter how accurately estimated, a media ENF signal may not be reliably used in forensic applications unless sufficiently distinctive. To clarify, ENF may show similar fluctuation patterns at different time intervals. These patterns become more distinct over longer periods of time. Accordingly, working with as large an ENF signal as possible is critical for reliability. To achieve an extended and, thus, more distinctive ENF signal, this study proposes a smart segmentation scheme for Short-Time Fourier Transform (STFT)-based ENF estimation, which derives more data segments from a given media than the conventional STFT technique, leading to increased ENF estimates for any specified STFT parameter setting. The proposed approach can be combined with any ENF accuracy enhancement strategy to obtain relatively more reliable signals. Large-scale tests conducted with different STFT parameters and audio clip lengths showed that the proposed scheme can efficiently improve the performance when used alone or in conjunction with other ENF enhancement strategies.Öğe An Overview of Deepfake Video Detection Using Remote Photoplethysmography(Institute of Electrical and Electronics Engineers Inc., 2024) Yilmaz, Berkay; Vatansever, SaffetDeepfake technology, which can create remarkably realistic videos through deep learning techniques, has many applications that serve humanity, including cinema and television productions, education, social media applications, art, fashion, and virtual assistants. However, this technology also brings with it potential abuse scenarios through manipulative content. Particularly in cases like fake news, identity fraud, blackmail, and slander, it can hasten the dissemination of false information and violate people's privacy. Moreover, it may cause major legal and societal issues in crucial fields like politics and public security. In this context, developing solutions for detecting deepfake videos has become imperative. While some methods developed in the literature to detect deepfake video are based on spatial and frequency-based analysis of digital traces and residues, which emerge intrinsically during the fake content production stage, some are based on examining physiological signs. Remote photoplethysmography (rPPG)-based physiological approaches, which analyze imperceptible color changes on the skin surfaces of individuals, have gained significant attention due to their high performance. This study examined rPPG-based techniques and their effectiveness in detecting fake videos made with Generative Adversarial Network (GAN) and Autoencoder (AE), two of the most popular deep learning algorithms used to produce deepfake content, and discussed the technical challenges encountered. © 2024 IEEE.Öğe Analysis of Rolling Shutter Effect on ENF-Based Video Forensics(Ieee-Inst Electrical Electronics Engineers Inc, 2019) Vatansever, Saffet; Dirik, Ahmet Emir; Memon, NasirElectric network frequency (ENF) is a time-varying signal of the frequency of mains electricity in a power grid. It continuously fluctuates around a nominal value (50/60 Hz) clue to changes in the supply and demand of power over time. Depending on these ENF variations, the luminous intensity of a mains-powered light source also fluctuates. These fluctuations in luminance can he captured by video recordings. Accordingly, the ENF can he estimated from such videos by the analysis of steady content in the video scene. When videos are captured by using a rolling shutter sampling mechanism, as is done mostly with CMOS cameras, there is an idle period between successive frames. Consequently, a number of illumination samples of the scene are effectively lost due to the idle period. These missing samples affect the ENF estimation, in the sense of the frequency shift caused and the power attenuation that results. This paper develops an analytical model for videos captured using a rolling shutter mechanism. This model illustrates how the frequency of the main ENF harmonic varies depending on the idle period length, and how the power of the captured ENF attenuates as idle period increases. Based on this, a novel idle period estimation method for potential use in camera forensics that is able to operate independently of video frame rate is proposed. Finally, a novel time-of-recording verification approach based on the use of multiple ENF components, idle period assumptions, and the interpolation of missing ENF samples is also proposed.Öğe Detecting the Presence of ENF Signal in Digital Videos: A Superpixel-Based Approach(Ieee-Inst Electrical Electronics Engineers Inc, 2017) Vatansever, Saffet; Dirik, Ahmet Emir; Memon, NasirElectrical network frequency (ENF) instantaneously fluctuates around its nominal value (50/60 Hz) due to a continuous disparity between generated power and consumed power. Consequently, luminous intensity of a mains-powered light source varies depending on ENF fluctuations in the grid network. Variations in the luminance over time can be captured from video recordings and ENF can be estimated through content analysis of these recordings. In ENF-based video forensics, it is critical to check whether a given video file is appropriate for this type of analysis. That is, if ENF signal is not present in a given video, it would be useless to apply ENF-based forensic analysis. In this letter, an ENF signal presence detection method is introduced for videos. The proposed method is based on multiple ENF signal estimations from steady super pixels, i.e., pixels that are most likely uniform in color, brightness, and texture, and intra-class similarity of the estimated signals. Subsequently, consistency among these estimates is then used to determine the presence or absence of an ENF signal in a given video. The proposed technique can operate on video clips as short as 2 min and is independent of the camera sensor type, i.e., CCD or CMOS.Öğe ENF Based Robust Media Time-Stamping(Ieee-Inst Electrical Electronics Engineers Inc, 2022) Vatansever, Saffet; Dirik, Ahmet Emir; Memon, NasirElectric Network Frequency (ENF) continuously fluctuates around a nominal value (50/60 Hz) due to a persistent imbalance between supplied and demanded power. In certain circumstances, ENF gets intrinsically embedded into audio and video recordings and can be extracted from these recordings. Consequently, ENF can be used in a number of media forensic applications, such as verifying the time of recording of the media. In this work, a robust media time-stamping approach is proposed for media whose ENF content is relatively contaminated. It essentially entails two procedures: first, detecting all useful, i.e., considerably accurate, samples of an estimated ENF signal, and then applying an adapted normalized cross-correlation process that is designed for exploiting just the selected ENF portions based on a binary mask of the identified accurate samples. Experimental results show that the proposed approach provides significantly increased performance.Öğe Factors Affecting Enf Based Time-of-recording Estimation for Video(Institute of Electrical and Electronics Engineers Inc., 2019) Vatansever, Saffet; Dirik, Ahmet Emir; Memon, Nasir D.ENF (Electric Network Frequency) oscillates around a nominal value (50/60 Hz) due to imbalance between consumed and generated power. The intensity of a light source powered by mains electricity varies depending on the ENF fluctuations. These fluctuations can be extracted from videos recorded in the presence of mains-powered source illumination. This work investigates how the quality of the ENF signal estimated from video is affected by different light source illumination, compression ratios, and by social media encoding. Also explored is the effect of the length of the ENF ground-truth database on time of recording detection and verification. © 2019 IEEE.Öğe FACTORS AFFECTING ENF BASED TIME-OF-RECORDING ESTIMATION FOR VIDEO(Ieee, 2019) Vatansever, Saffet; Dirik, Ahmet Emir; Memon, NasirENF (Electric Network Frequency) oscillates around a nominal value (50/60 Hz) due to imbalance between consumed and generated power. The intensity of a light source powered by mains electricity varies depending on the ENF fluctuations. These fluctuations can be extracted from videos recorded in the presence of mains-powered source illumination. This work investigates how the quality of the ENF signal estimated from video is affected by different light source illumination, compression ratios, and by social media encoding. Also explored is the effect of the length of the ENF ground-truth database on time of recording detection and verification.Öğe Farklı çözünürlükteki sayısal imge ve videolar için PRNU tabanlı kaynak kamera tespiti üzerine bir çalışma(2023) Vatansever, Saffet; Dirik, Ahmet EmirHer bir kamera sensörüne has benzersiz bir gürültü bileşeni olan PRNU (Photo Response Non-Uniformity), sayısal imge ve videoların adli analizi kapsamında ihtiyaç duyulan önemli araçlardandır. PRNU’nun en yaygın uygulama alanı olan kaynak kamera tespiti, aynı marka ve model kameraların bile PRNU karakteristiğinin birbirinden farklı oluşu ve bu örüntünün çekilen her bir resim karesi üzerine bir kamera parmak izi gibi istemsiz eklenmesi esasına dayanmaktadır. Bir test dosyasından (imge ya da video) kestirimi sağlanan PRNU sensör gürültüsü ile dosyanın kaynağı olduğu düşünülen kameraya ait referans PRNU (sabit içerikli düz duvar ya da gökyüzü görüntülerinden yüksek doğrulukta elde edilen PRNU örüntüsü) arasındaki benzerliğe göre bu kameranın test videosunun kaynağı olup olamayacağı belirlenebilir. Sayısal video çerçevelerinin imgelere göre düşük kalitede kodlanması, videolardan kestirilen PRNU sensör gürültüsünün doğruluğunu, dolayısıyla da benzerlik analizini etkilemektedir. Bu bağlamda, videolarda PRNU tabanlı kaynak kamera tespitinde, referans PRNU’nun videolardansa imgelerden elde edilmesi performans etkinliği için önemli bir hamledir. Ancak, imge ve videolar aynı kaynak kamera ile çekilmiş olsalar dahi farklı en boy oranında ve/veya çözünürlükte kaydedilmektedirler. Bu sebeple, imgelerden elde edilen PRNU izinin, sorgu videosuna ait PRNU sensör gürültüsü ile aynı foto-alıcı hücrelere karşılık gelecek forma dönüştürülmesi gerekmektedir. Bu çalışmada, bu dönüşümü sağlayan ölçekleme ve kırpma parametrelerini hassas bir şekilde hesaplayabilen bir yöntem önerilmiştir.Öğe Forensic Analysis of Digital Audio Recordings based on Acoustic Mains Hum(Ieee, 2016) Vatansever, Saffet; Dirik, Ahmet EmirENF (Electrical Network Frequency), fluctuates instantaneously from its nominal value (50/60 Hz) depending on an increase or decrease in power consumption as against power production in the grid network. An ENF-sourced noise component is added into audio recordings where mains power sourced electromagnetic field or acoustic mains hum exists. With the use of this component, recording date and time of an audio file can be verified. In this work, existence and estimation of the acoustic mains hum sourced ENF noise in audio files is studied by analysing the acoustic noise emitted by several devices that are frequently used at home or in workplace. Detection of the file recording time truly is examined by computation of the similarity between the ENF signals estimated from the audio recordings and the reference ENF obtained with the help of a circuit that is connected to power grid network. The behaviour of dynamic microphone and electret microphone towards acoustic mains hum is investigated and the extent of acquiring the information about recording device type and settings from audio files is analysed. Besides, as part of this work, ENF estimation from videos on social media is also investigated.Öğe Hafif Bir Derin Öğrenme Modeli İle Bilgisayarlı Tomografi Görüntülerinden Beyin Kanaması Tespiti(2024) Altun, Emine Betül; Engin, Sümeyye; Başkaya, Esma; Şafak, Fatma Nur; Vatansever, SaffetBeyin dokusu içine kan sızması durumu olarak ifade edilen beyin kanaması, acil tıbbi müdahale gerektiren nörolojik bir komplikasyondur. Bu sebeple, beyin kanamasında erken tanı, hastaların hayatta kalma şansını ve iyileşme sürecini önemli ölçüde etkiler. Beyin kanaması teşhisinde, radyologlarca yaygın olarak tercih edilen bilgisayarlı tomografi (BT) ve manyetik rezonans (MR) görüntüleri, derin öğrenme tabanlı yaklaşımlar ile analiz edilerek, beyin kanamasının varlığı ve kanamanın yeri hızlı ve etkili bir şekilde tespit edilebilir. Bu yöntemler, radyologların iş yükünü önemli ölçüde azaltabileceği gibi, kompleks vakalarda daha kesin teşhisler koyulmasına da yardımcı olabilir. Buna bağlı olarak, beyin kanaması kaynaklı ölümlerin veya bedensel işlev bozukluklarının önüne geçilebilir. Bu çalışmada, bilgisayarlı tomografi görüntüleri üzerinden beyin kanaması ve türünü yüksek doğrulukta tespit edebilen CNN tabanlı düşük boyutlu bir derin öğrenme modeli önerilmiştir. DenseNet121, MobileNet ve Inception V1 gibi popüler CNN modelleri ile yapılan karşılaştırmalı deneysel analizler, önerilen modelin, eğitim süresini önemli ölçüde kısalttığını ve daha başarılı bir performans sergilediğini göstermiştir.Öğe Ses Dosyalarının ENF Tabanlı Adli Analizine Kısa Zamanlı Fourier Dönüşümü Parametre Seçimlerinin Etkisi(2023) Yalinkilic, Ali Berk; Vatansever, SaffetHızla gelişmekte olan bilgisayar teknolojisi sayesinde çeşitli tekniklerle dijital ses, görüntü ve video dosyaları üzerinde modifikasyonlar yapılabilmektedir. Bu modifikasyonlar doğrudan dosya içeriğinde olabileceği gibi bazen de meta data üzerinde olabilmektedir. Bu bağlamda dijital medyaların adli analizi büyük önem arz etmektedir. Elektrik şebeke frekansı (ENF) tabanlı adli analiz yaklaşımı dosya bütünlük kontrolünde ve dosyaların kayıt zamanı tespitinde kullanılabilen önemli bir araçtır. ENF sinyali kestiriminde en çok tercih edilen yöntemlerden biri, kısa zamanlı Fourier dönüşümü (Short-Time Fourier Transform - STFT) temelli yaklaşımdır. STFT yönteminde, pencere boyutu ve kaydırma miktarı parametrelerinin seçimi büyük öneme sahip olup, kestirimi yapılan ENF sinyali doğruluğunu, dolayısıyla da ENF tabanlı adli analiz uygulamalarının performansını doğrudan etkileyebilmektedir. Bu çalışmada, STFT parametreleri seçiminin, ENF tabanlı dosya kayıt zamanı doğrulamada performansa ne derece etki ettiği araştırılmıştır. Farklı uzunluktaki ses dosyaları, çeşitli STFT pencere boyutu ve STFT kaydırma miktarlarına göre ayrı ayrı test edilerek karşılaştırmalı bir analiz yapılmıştır.Öğe The Effect of Inverse Square Law of Light on ENF in Videos Exposed by Rolling Shutter(Ieee-Inst Electrical Electronics Engineers Inc, 2023) Vatansever, Saffet; Dirik, Ahmet Emir; Memon, NasirDue to a constant imbalance between demand and supply of power, ENF (Electric Network Frequency) fluctuates around a nominal value of 50 or 60 Hz. These variations in ENF cause the luminance intensity of a mains-powered light source, having no AC/DC converter inside, also to fluctuate. As a result, a video of a scene illuminated by a mains-powered light source can be used to estimate these fluctuations. As a consequence, the ENF signal within the time period when the video was captured can be estimated. This work explores the effects of frame rate harmonics that emerge when a rolling shutter based approach is used for ENF estimation from videos captured using CMOS cameras. These harmonics are a problem, especially for videos whose frame rate is a divisor of the nominal ENF because the frame rate harmonics and the ENF harmonics overlap. It is discovered that a key reason for the presence of the harmonics is the inverse square law of light that results in some repeating patterns of luminance variation across frames. This paper presents an analysis of the effect of the inverse square law of light on ENF estimation. A technique for refined ENF-related luminance signal estimation is proposed that attenuates these frame rate harmonics. This enables more accurate ENF estimates. The work also proposes an approach to estimate ENF-related luminance waveform cycles within each video frame, and a method to compute the confidence score for the estimated cycles. It provides insight into the reliability of the extracted ENF signal from a video, in the sense of its usefulness for ENF forensics, and consequently for ENF detection, which is an important precursor to ENF-based video forensics.Öğe Videolardan Kalp Atış Hızı Kestirimi Üzerine Bir İnceleme(Osman SAĞDIÇ, 2022) Korkmaz, Mustafa; Vatansever, SaffetKalp atış hızı; kişinin sağlığı, aktivite seviyesi, stres durumu, zindeliği ve benzeri fizyolojik durumları hakkında önemli ipuçları vermektedir. Kalp atış hızı, elektrokardiyogram (EKG) ve nabız oksimetreleriyle ölçülebilir olmakla birlikte, bu cihazlar sürekli temas gerektirdiğinden zamanla rahatsız edici olabilmektedir. Bilgisayarlı görü (computer vision) alanındaki son gelişmeler, bir kişiye elektrot veya nabız oksimetreleri takmanın mümkün veya uygun olmadığı durumlarda, videolardan kişinin kalp atış hızını tespit etmeye olanak sağlamıştır. Uzaktan fotopletismografi (rPPG), bir video kamera aracılığıyla derideki hassas renk değişikliklerini yakalayarak, yaşamsal belirtilerin tespit edilmesine imkân sağlayan bir teknolojidir. Son yıllarda yapılan çalışmalar, uzaktan kalp atış hızı tespiti için en uygun bölgenin yüz olduğunu göstermiştir. Bu çalışmada; videolar aracılığıyla kişilerin yüz bölgesinden kalp atışı hızı kestiriminin nasıl yapılabildiği, kalp atışı hızı kestirimi sürecindeki aşamaların nasıl iyileştirilebileceği ve nasıl daha yüksek doğrulukta kalp atışı hızı tespiti yapılabileceği hakkında literatürdeki mevcut yöntemler incelenerek kapsamlı bir analiz yapılmıştır.Öğe VİDEOLARIN ENF TABANLI ADLİ KANIT ANALİZİNE IŞIK KAYNAĞI ETKİSİ(2017) Vatansever, Saffet; Dirik, Ahmet EmirVideo dosyalarının Elektrik Şebeke Frekansı (Electric Network Frequency - ENF) temelli adli kanıt analizi tekniği, çoklu ortam dosyalarının kayıt zamanını doğrulamada ve dosyalarda yapılan sahteciliği tespit etmede son yıllarda önerilmiş en önemli araçlardan biridir. ENF, şebekede üretilen toplam gücün tüketilen toplam güce göre artıp azalmasına bağlı olarak nominal değer (Avrupa"da 50 Hz) etrafında sürekli salınımlar yapar. Bu salınımlar aynı şebeke üzerindeki her noktada aynıdır. Elektrik şebekesinden beslenen bir ışık kaynağının yaymış olduğu aydınlatma şiddeti elektrik şebeke frekansına bağlı olarak insan gözünün fark edemeyeceği anlık değişkenlikler gösterir. Işık şiddetindeki bu değişimler, video kameralar tarafından yakalanabilmektedir. Çekilen videolardaki tüm resim çerçeveleri boyunca değişmeyen içerik analiz edilerek aydınlatma şiddetinin değişim hızı, dolayısıyla elektrik şebeke frekansı kestirilebilir. Videolardan kestirimi yapılan ENF sinyalinin, elektrik şebekesinden doğrudan elde edilen referans ENF sinyali ile benzerlikleri hesaplanarak dosya kayıt zamanı bilgisine ulaşılabilir. Bu çalışmada, şebeke elektriğine bağlı ışık kaynağı türünün, CCD sensörlü kamera ile çekilmiş videolardan kestirilen ENF sinyali kalitesinde ne derece etkili olduğu incelenmiştir. Işık kaynağı türüne göre, çeşitli uzunluktaki videolarda ENF temelli kayıt zamanı doğrulama performansı analiz edilmiştir.
