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Video Recordings Localization Based on Electric Network Frequency Variation VIDEO RECORDINGS LOCALIZATION BASED ON ELECTRIC NETWORK FREQUENCY VARIATION Vlad-Dragos Darau Trabajo de Fin de Grado Escuela de Ingeniería de Telecomunicación Grado en Ingeniería de Tecnologías de Telecomunicación Tutores Fernando Pérez González 2016 VIDEO RECORDINGS LOCALIZATION BASED ON ELECTRIC NETWORK FREQUENCY VARIATION Vlad-Dragos, D˘ar˘au Director: Fernando P´erezGonz´alez Academic Course 2015/2016 20th of June, 2016 ii Contents 1 Introduction 1 1.1 The Signal Processing in Communications Group 1 1.2 Fingerprinting : a Branch of Watermarking ..2 1.3 ENF - What Is It? .....................2 1.4 ENF - Properties And How The Electric Net- works Work ..........................3 1.5 ENF- Relation with Generators ...........3 1.6 ENF- How to extract it? ................6 2 State Of The Art 13 2.1 Audio Authentication/Tampering .......... 13 2.2 Location Stamping ..................... 14 2.3 Video Synchronization and Historical Alignment 15 2.4 Time Stamping ....................... 15 3 Measuring the ENF - Circuits 17 3.1 Analog Option ........................ 17 3.2 Digital Option ........................ 18 3.2.1 Acquisition Part .................. 18 3.3 Processing Part ....................... 22 3.4 Other Circuits for Sensing The Mains Hum .. 24 4 Video as an ENF carrier 27 4.1 Color Spaces and Video Standards ......... 27 4.2 Aliasing Effect Consequences ............. 29 5 Experiments 33 5.1 Category I-ENF Spatial Localization ....... 33 5.1.1 ROC Curves and Signal Features ...... 33 5.1.2 Experiment I-Frequency Classification .. 35 5.1.3 Experiment II-Range Classification .... 36 iii iv CONTENTS 5.2 Category II- ENF Time localization ........ 37 5.2.1 Experiment I- Simulated Delay ....... 40 5.2.2 Experiment II-Simulated Time Localiza- tion ............................ 43 6 Conclusions and Future Work 45 Appendices 51 Appendix A 51 A.1 Circuit Schematic and BOM ............. 51 A.2 Matlab Functions and Scripts ............. 53 A.3 C Code for PIC Microcontroller ........... 69 A.4 Luminosity Extraction Algorithm .......... 73 Chapter 1 Introduction In our days, the continuous growth of digital data is supported by the nu- merous modern web sites and platforms which encourage each user to be not only a consumer, but a producer of data. More specifically, everyone can now have its own channel or web page on any video or social platform, where one can promote or just talk about anything, by means of media, like video or audio recording. One of the problems that arises from this fact is itself the name of one characteristic of the digital data: veracity. The level with which we can trust one data set is very important, especially when we are trying to prove something based on it. In fact, digital media security is and will always probably be a current topic of interest in the forensic world. Moreover, the future development of networked multimedia systems, in par- ticular on open networks like the Internet, is and will be conditioned by the development of efficient methods to protect data owners against unautho- rized copying and redistribution of material. This thesis will be organized in the following manner: first, the concept of fingerprinting and more specifi- cally, ENF as a fingerprint will be defined. In the second part, a state of art overview shall be presented. In the third part the circuit and Matlab code, followed by numerous experiments will be described. Finally, a section of results of conclusions, followed by appendices, will conclude the document. 1.1 The Signal Processing in Communications Group The following diploma project has been made with the support of The Sig- nal Processing in Communications Group (GPSC), GRADIANT and The Hardware in Communications Laboratory, which are part of Univerdidad de Vigo. The Signal Processing in Communications Group (GPSC) has been consistently developing two parallel research lines which make extensive use of advanced signal processing tools. On one hand, they have experience in the application of such techniques to communication systems and sensor networks, e.g., in synchronization, equalization, link monitoring and adapta- tion, satellite and mmWave communications, spectrum sensing, etc. On the 1 2 CHAPTER 1. INTRODUCTION other hand, the group has been active in the field of multimedia security, including digital watermarking, digital forensics, and signal processing in the encrypted domain. The proficiency of the group can be attested by the results obtained in these areas: in the last 10 years, GPSC members have directed 9 PhD theses, published over 70 papers in international journals, and secured 9 M ein funding from public (including European projects) as well as private sources (with more than 10 patents). 1.2 Fingerprinting : a Branch of Watermarking Watermarking is the process of protecting anything, from an object till any virtual information, from the threat of piracy, assuring like this intellectual property protection and it has been used starting with the year 1272 for banknotes authentication. There is an increasing need for software (or in the worst case, hardware) that allows for protection of ownership rights, and it is in this context where watermarking techniques come to our help. Perceptible marks of ownership or authenticity have been around for centuries in the form of stamps, seals, signatures or classical watermarks, nevertheless, given current data manipulation technologies, imperceptible digital watermarks are mandatory in most applications. A digital fingerprint, on the other side, is just a signal which identifies a recipient uniquely, used mainly to limit unauthorized redistribution of multimedia content. The main difference between a fingerprint and a watermark is that the first one analyses the content, identifying a unique set of inherent properties rather than adding information to the content, like the latter one. 1.3 ENF - What Is It? The variation of the ENF is a robust, natural fingerprint which is present in audio and video recordings in some conditions. The ENF, which comes from Electric Network Frequency, is nothing than the electrical power grid supply frequency, which has a nominal value of 60 Hz in USA and 50 Hz in most parts of the world. It is more popularly known as electrical "hum" and it has been proven to be picked up by audio or video recorders which are plugged in or near the power sources [4]. The variations from the nominal values have been proven to be connected with the local quantity of load in the network, which changes over time and geographical location and the switching, which represents part of the dynamic management of an electric grid. The voltage frequency of an electrical power grid can fluctuate at any time under the influence of the variations of any of the three components of the electrical network: the load, which is subject to various on and off switching according to specific operational conditions; the generator, which follows or anticipates the load variations in order to maintain an equilibrium between generation 1.4. ENF - PROPERTIES AND HOW THE ELECTRIC NETWORKS WORK3 and utilization; the electrical grid (mains), whose topology varies whenever the switching maneuvers are done, and which may be affected by faults.[1] 1.4 ENF - Properties And How The Electric Networks Work Although the electrical network frequency (ENF) should have an exact value of 50 or 60 Hz, depending on the region and on the time of the day, it finally proves to be a function of some events, like stated in Section 1.3. The supply side of the electrical network is mainly formed by devices called alternators, capable of transforming mechanical energy into electrical energy. Because of the electro-mechanical properties that they exhibit, there exist certain features that relate their way of functioning with the frequency of the generated voltage, which finally gives the frequency of the electric network to which one generator is contributing. The nominal frequency value of a power grid needs to be strictly re- spected, as some devices, like motors which spin according to this value or digital clocks which synchronize themselves based on the ENF, depend directly on this value. In order to obtain a stable value in time, different (national or regional) networks are connected between them, creating vast synchronization areas, like those presented in Figure 1.1. Although the term "synchronized" is used, this does not mean that two remote locations, both parts of the same synchronization area, will present the same variation of ENF in time, as they cannot be controlled up to that extent. In such a case, the synchronization process is based on the number of zero-crossings of the voltage waveform. For every given period, for example 24 hours, the number of zero crossings of the voltage signal in one synchronization region has to be the same. This keeps clocks which use ENF to synchronize, at 0 global error, although there might be differences between them in the speci- fied period of time; at the end of the, say, 24 hours, they will show the same time. 1.5 ENF- Relation with Generators Any generator, or more specifically alternator, is composed of two parts: one static part and one mobile part (the rotor). Depending on the number of poles that it has, in order to generate a voltage of a desired frequency, the generator must perform a number of rotations per minute. In the most com- mon case (except for nuclear plants), the generator has 2 poles, so according to the formula N = 120 × f=p; 4 CHAPTER 1. INTRODUCTION Figure 1.1: Synchronization regions by colors in Eurasia [20] one generator must spin with 3000 rotations per minute in order to generate a 50 Hz varying voltage. In the nuclear plants case, the generators usually have 4 poles and as a consequence, the number of rotations performed by such a generator in order to generate the same frequency voltage as a bipolar one has to be half,that is, 1500 in the case of 50 Hz networks.
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