Suchergebnis: Katalogdaten im Frühjahrssemester 2021

Cyber Security Master Information
Ergänzung
Information Systems
Kernfächer
NummerTitelTypECTSUmfangDozierende
263-2925-00LProgram Analysis for System Security and Reliability Information W7 KP2V + 1U + 3AM. Vechev
KurzbeschreibungSecurity issues in modern systems (blockchains, datacenters, deep learning, etc.) result in billions of losses due to hacks and system downtime. This course introduces fundamental techniques (ranging from automated analysis, machine learning, synthesis, zero-knowledge and their combinations) that can be applied in practice so to build more secure and reliable modern systems.
Lernziel* Understand the fundamental techniques used to create modern security and reliability analysis engines that are used worldwide.

* Understand how symbolic techniques are combined with machine learning (e.g., deep learning, reinforcement learning) so to create new kinds of learning-based analyzers.

* Understand how to quantify and fix security and reliability issues in modern deep learning models.

* Understand open research questions from both theoretical and practical perspectives.
InhaltPlease see: https://www.sri.inf.ethz.ch/teaching/pass2021 for detailed course content.
Wahlfächer
NummerTitelTypECTSUmfangDozierende
252-0312-00LUbiquitous Computing Information W6 KP2V + 3AC. Holz
KurzbeschreibungUbiquitous Computing means interacting with information and with each other anywhere, mediated through miniature technology everywhere. We will investigate the technical aspects of Ubicomp, particularly sensing, processing, and sense making: input (touch & gesture), activity, monitoring cardiovascular health and neurological conditions, context & location sensing, affective computing.
LernzielThe course will combine high-level concepts with low-level technical methods needed to sense, detect, and understand them.

High-level:
– input modalities for interactive systems (touch, gesture)
– "activities" and "events" (exercises and other mechanical activities such as movements and resulting vibrations)
– health monitoring (basic cardiovascular physiology)
– location (GPS, urban simulations, smart cities and development)
– affective computing (emotions, mood, personality)

Low-level:
– sampling (Shannon Nyquist) and filtering (FIR, IIR), time and frequency domains (Fourier transforms)
– cross-modal sensor systems, signal synchronization and correlation
– event detection, classification, prediction using basic signal processing as well as learning-based methods
– sensor types: optical, mechanical/acoustic, electromagnetic

– signals modalities and processing of: application (modalities/methods)
* touch detection (resistive sensing, capacitive sensing, diffuse illumination/DI, spectral reflections, frustrated total internal reflection/FTIR, fingerprint scanning, surface-acoustic waves)
* gesture recognition (inertial sensing through accelerometers, gyroscopes)
* activity detection and tracking (inertial, acoustic, vibrotactile for classification, counting, vibrometry)
* occupation and use (electricity monitoring, water consumption, single-point sensing)
* cardiovascular (electrocardioagraphy, photoplethysmography, pulse oximetry, ballistocardiography, blood pressure, pulse transit time, bio impedance)
* affective computing (heart rate variability, R-R intervals, electrodermal activity, sympathetic tone, facial expressions)
* neurological (fatigue, fatigability)
* location (GPS, BLE, Wifi)
Inhalt"The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it" — Mark Weiser, 1991.

This is the premise of Ubiquitous Computing, a vision that is slowly becoming reality as everything is a device and we can interact with information and with each other anywhere, mediated through miniature technology. Along with this change, interaction modalities have changed, too, from explicit input on keyboards and mice to implicit and passively observed input through sensors in the environment (e.g., speakers, cameras, temperature/occupancy detectors) and those we now wear on our bodies (e.g., health sensors, activity sensors, miniature computers we call smartwatches).

In this course, we will look at the technical side of Ubicomp, particularly
– sensing (incl. 'signals', sampling, data acquisition methods, controlled user studies, uncontrolled studies in-the-wild),
– processing (incl. frequencies, feature extraction, detection), and
– sense making: input sensing (touch & gesture), activity sensing (motion), monitoring cardiovascular health, affective state, neurological conditions (with basics on cardiovascular physiology + PPG, PulseOx, ECG, EDA, BCG, SCG, HRV, BioZ, IPG, PAT, PTT), context & location sensing (GPS/Wifi, motion).

Lectures will be accompanied by practical sessions that focus on sensor modalities and signal processing. Here, we will work on existing data sets and devise methods to record our own data for processing and prediction purposes.

A series of reading assignments, covering both well-established publications in Ubicomp as well as emerging results and methods, will bridge the fundamentals and topics taught in class to academic research and real-world problems.

More information on the course site: https://teaching.siplab.org/ubiquitous_computing/2021/
SkriptCopies of slides will be made available. Lectures will be recorded and made available online.

More information on the course site: https://teaching.siplab.org/ubiquitous_computing/2021/
LiteraturWill be provided in the lecture. To put you in the mood:
Mark Weiser: The Computer for the 21st Century. Scientific American, September 1991, pp. 94-104
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