Device Fingerprinting with Magnetic Induction Signals Radiated by CPU Modules

With the widespread use of smart devices, device authentication has received much attention. One popular method for device authentication is to utilize internally measured device fingerprints, such as device ID, software or hardware-based characteristics. In this article, we propose DeMiCPU , a stimulation-response-based device fingerprinting technique that relies on externally measured information, i.e., magnetic induction (MI) signals emitted from the CPU module that consists of the CPU chip and its affiliated power-supply circuits. The key insight of DeMiCPU is that hardware discrepancies essentially exist among CPU modules and thus the corresponding MI signals make promising device fingerprints, which are difficult to be modified or mimicked. We design a stimulation and a discrepancy extraction scheme and evaluate them with 90 mobile devices, including 70 laptops (among which 30 are of totally identical CPU and operating system) and 20 smartphones. The results show that DeMiCPU can achieve 99.7% precision and recall on average, and 99.8% precision and recall for the 30 identical devices, with a fingerprinting time of 0.6~s. The performance can be further improved to 99.9% with multi-round fingerprinting. In addition, we implement a prototype of DeMiCPU docker, which can effectively reduce the requirement of test points and enlarge the fingerprinting area.

Validation of photovoltaics powered UPQC using ANFIS controller in a standard microgrid test environment

The power quality improvement becomes one of the important tasks while using microgrid as main power supply. Because the microgrid is combination of renewable energy resources. The renewable energy resources are intermittent in power supply and at the peak loading condition it has to supply the required power. So, the power quality problems may increase in that time. Out of all power quality issues the voltage drop and harmonic distortion is considered as the most serious one. In recent years unified power quality conditioner (UPQC) is emerged as most promising device which compensates both utility as well as customer side power quality disturbances in effective way. The compensating potentiality used in the UPQC is limited by the use of DC link voltage regulation and the conventional proportional integral (PI) controller. In this paper the compensating potentiality of the UPQC device is controlled by an adaptive neuro fuzzy inference system (ANFIS) control and it is powered from the available photovoltaics (PV) power generation. The effect of adding an intelligent UPQC is tested in the standard IEEE-14bus environment. MATLAB 2017b is used here for testing and plotting the simulation results.

MULTIFUNCTIONAL DATA COLLECTION SYSTEM FOR MONITORING THE STATE OF TECHNICAL FACILITIES

Представлен комплекс технических средств создания для системы сбора данных. Проведена формализация процессов реализации функций контроля технического объекта. Рассматриваемая система сбора данных состоит из функционально законченных устройств, выполняющих определенные функции в контексте работы системы. Данная система, с одной стороны, может быть одним из узлов распределенной системы сбора данных, с другой стороны, может использоваться автономно. Показана актуальность создания системы. В основе разработки использован RISC микроконтроллер STM32H743VIT6, семейства ARM Cortex-M7, работающий на частоте до 400 МГц. К основным модулям системы относятся 20-входовый распределитель напряжения; модуль питания и настройки; модуль цифрового управления; модуль анализа, хранения и передачи данных в управляющий компьютер. Рассмотрен состав и назначение этих модулей. За сбор данных в рассматриваемой системе отвечает цепочка устройств: датчик - схема согласования - АЦП - микроконтроллер. Поскольку в составе системы имеются не только АЦП, но и ЦАП, то на ее базе может быть реализована система управления объектом. Выбор датчиков для снятия информации обусловлен особенностями объекта контроля. Имеется возможность в ручном режиме измерять электрические параметры контуров связи, в том числе обеспечивать проверку питания IDE и SATA-устройств. Представленная система сбора данных является средством, которое может быть использовано для автоматизации процессов контроля состояния технических объектов We present a set of technical means for creating a data collection system. We carried out the formalization of the processes of implementing the control functions of a technical object. The multifunctional data collection system consists of functionally complete devices that perform certain functions in the context of the system operation. This system, on the one hand, can be one of the nodes of a distributed data collection system, on the other hand, it can be used autonomously. We show the relevance of the system creation. The development is based on the RISC microcontroller STM32H743VIT6, ARM Cortex-M7 family, operating at a frequency of up to 400 MHz. The main modules of the system include: a 20-input voltage distributor; a power supply and settings module; a digital control module; a module for analyzing, storing and transmitting data to a control computer. We considered the composition and purpose of these modules. A chain of devices is responsible for data collection in the system under consideration: sensor - matching circuit - ADC - microcontroller. Since the system includes not only an ADC but also a DAC, an object management system can be implemented on its basis. The choice of sensors for taking information is due to the characteristics of the object of control. It is possible to manually measure the electrical parameters of the communication circuits, including checking the power supply of IDE and SATA devices. The presented data collection system is a tool that can be used to automate the processes of monitoring the condition of technical facilities