SEMINARS / EVENTS

September 06, 2018,  11:00-12:00,  Location : Rav. 1315,  Speaker : Schahram Dustdar, Technical University of Vienna

Smart Cities unplugged - Engineering the fabric of IoT, People, and Systems

In this talk I will explore the integration of people, software services, and things with their data, into a novel resilient ecosystem, which can be modeled, programmed, and deployed on a large scale in an elastic way. This novel paradigm has major consequences on how we view, build, design, and deploy ultra-large scale distributed systems and establishes a novel foundation for an "architecture of value" driven Smart City. In particular, this keynote talk addresses three novel paradigms for designing the service-oriented information systems of the future: Elastic Computing, Social Compute Units, and Osmotic Computing.

These three paradigms serve as a foundation for future large-scale distributed systems. Furthermore, we will discuss our responsibilities as computer scientists, technologists, and researchers for creating technologies, which benefit society in a positive way, thereby strengthening the new fabric of interconnected people, software services, and things into a novel resilient ecosystem.

BRIEF BIOGRAPHY

Schahram Dustdar is Professor of Computer Science heading the Distributed Systems Group at the Technical University of Vienna.

From 2004-2010 he was also Honorary Professor of Information Systems at the Department of Computing Science at the University of Groningen (RuG), The Netherlands.

From 1999 - 2007 he worked as the co-founder and chief scientist of Caramba Labs Software AG in Vienna (acquired by Engineering NetWorld AG), a venture capital co-funded software company focused on software for collaborative processes in teams. Caramba Labs was nominated for several (international and national) awards: World Technology Award in the category of Software (2001); Top-Startup companies in Austria (Cap Gemini Ernst & Young) (2002); MERCUR Innovationspreis der Wirtschaftskammer (2002).

From Dec 2016 until Jan 2017 he was a Visiting Professor at the University of Sevilla, Spain and from January until June 2017 he was a Visiting Professor at UC Berkeley, USA. He is co-Editor-in-Chief of the new ACM Transactions on the Internet of Things as well as Editor-in-Chief of Computing (Springer). He is an Associate Editor of IEEE Transactions on Services Computing, IEEE Transactions on Cloud Computing, ACM Transactions on the Web, and ACM Transactions on Internet Technology, as well as on the editorial board of IEEE Internet Computing and IEEE Computer. Dustdar is recipient of the ACM Distinguished Scientist award (2009), the IBM Faculty Award (2012), an elected member of the Academia Europaea: The Academy of Europe, where he is chairman of the Informatics Section, as well as an IEEE Fellow (2016). 

November 29, 2017,  12:30-13:30,  Location : Zi 2042,  Speaker : R. Bortolameotti (Riccardo) MSc.

DECANTeR: DeteCtion of Anomalous outbouNd HTTP TRaffic by Passive Application Fingerprinting

We present DECANTeR, a system to detect anomalous outbound HTTP communication, which passively extracts fingerprints for each application running on a monitored host. The goal of our system is to detect unknown malware and backdoor communication indicated by unknown fingerprints extracted from a host's network traffic. We evaluate a prototype with realistic data from an international organization and datasets composed of malicious traffic. We show that our system achieves a false positive rate of 0.9%, an average detection rate of 97.7%, and that it cannot be evaded by malware using simple evasion techniques such as using known browser user agent values. Moreover, we show that our solution outperforms the current state of the art that detects covert communication channels by focusing only on benign data. Finally, DECANTeR detects 96.8% of information stealers in our dataset, which shows its potential to detect data exfiltration. 

November 21, 2017,  14:00-15:00,  Location : Zi 2042,  Speaker : T.R. van de Kamp (Tim) MSc.

How to Monitor When All Data Is Encrypted?

We propose the first multi-client predicate-only encryption scheme capable of efficiently testing the equality of two encrypted vectors.

Our construction can be used for the privacy-preserving monitoring of relations among multiple clients. Since both the clients' data and the predicates are encrypted, our system is suitable for situations in which this information is considered sensitive. We prove our construction plaintext and predicate private in the generic bilinear group model using random oracles, and secure under chosen-plaintext attack with unbounded corruptions under the symmetric external Diffie–Hellman assumption. Additionally, we provide a proof-of-concept implementation that is capable of evaluating one thousand predicates defined over the inputs of ten clients in less than a minute on commodity hardware. 

October 24, 2017,  14:00-14:30,  Location : Zi 2126,  Speaker : H.T. Esquivel Vargas (Herson) MSc.

Automatic Deployment of Specification-based Intrusion Detection in the BACnet Protocol

Specification-based intrusion detection (SB-ID) is a suitable approach to monitor Building Automation Systems (BASs) because the correct and non-compromised functioning of the system is well understood. The goal is to compare the expected behavior of devices with their actual behavior as observed in the network.

The main drawback of SB-ID is that the creation of specifications often require human intervention. Automated specification extraction, on the other hand, is crucial to effectively apply SB-ID in volatile environments such as BASs where new devices are often added, removed, or replaced.

We present an approach to automatically extract specifications in the context of the BACnet protocol (ISO 16484-5) extensively used in our university campus. 

September 05, 2017,  13:00-14:00,  Location : HalB 2E,  Speaker : Dilan Seckiner MSc

Safety: Forensic Gait Analysis: Morphometric body assessment with associated CCTV image quantification

Closed Circuit Television (CCTV) cameras are often referred to as 'the silent witness' and have rapidly become a universal presence capturing footage useful for activity level and some source level inference. From this, photo-comparative analysis of a trace or 'a "person of interest" (POI) can be assessed when compared to a suspect. Limitation of CCTV images arises however, from the various distortions present within the camera specification and environmental influences. Additional challenges exist when facial features are concealed or otherwise obscured, thus preventing facial analysis. One solution to overcome this, is the morphometric assessment of the body. Further, as POIs are frequently recorded in motion, implementing gait analysis could further determine whether distinct features are apparent within the POI.

The aim of this study was to produce a standardised method for morphometric gait analysis that incorporates the quantification of image distortion and to determine distinct features of the body during gait (stance, walk, run). Hypothesis being, H0: P(E|Same Source) = P(E|SS) and H1: P(E|Different Source) = P(E|DS). The method comprised of a morphometric assessment of 18 anthropometric measurements (static, dynamic and angle), 25 morphological features for stance and 52 morphological features for gait assessed, of both male and female volunteers (437 in total). From this, a standardised protocol was developed, and population databases established from which frequency statistics will be obtained once all data has been completed. Furthermore to ascertain which features exactly were common or distinct once compared to all age, race and sex categories for correlation determination and finally to apply the likelihood ratio to this research.

Body mapping as a forensic tool is often poorly validated or subjective. However, this does not mean it is not of value. The broader purpose of this research is therefore to establish a method of evaluating gait analysis that offers valuable information to the criminal justice system whilst being scientifically robust, and importantly adhering to the admissibility standards of the Australian legal system. 

August 22, 2017,  15:15-16:15,  Location : ZI 2126,  Speaker : dr.ing. Thomas Hupperich, Ruhr-Universit├Ąt Bochum, Germany

Cybersecurity: Fingerprinting - An Introduction to System Recognition

Client fingerprinting is a technique for state-less user tracking and recognizing user systems in Internet context. It is widely used and implemented by advertisers, online shops and website analytic engines. Current state-of-the-art fingerprinters utilize code snippets to obtain system fingerprints and aim to identify specific systems among others.

This lecture gives an introduction to the concept of web-based client fingerprinting and covers the principle of recognition performed by a computer system. It tackles the core problem of similarity measurement and presents approaches for system recognition based on fingerprint data.