Advanced Seminar (Masterseminar) ‚IT-Sicherheit‘ WS2016/2017
The Advanced Seminar will be held by Harald Baier, Andreas Nautsch, Christian Rathgeb and Jessica Steinberger. The Advanced Seminar will focus on Advanced Topics in Forensics, Biometrics and Internet security.
The seminar will have only few fixed class meetings. Besides these meetings, additional appointments shall be arranged individually and on demand. The schedule of this seminar can be found in the online booking system (OBS). The first meeting will take place on: 05/10/2016 10:15 a.m. in D14/204.
Each group’s term paper has to be prepared using IEEE 2-column template with a length of 6 – 8 pages without references and clear marked appendices. The IEEE templates for LaTeX can be found here: IEEEtran Template. The literature style file can be found here: IEEEtran BST file. The final presentation will be 40 minutes per group + 20 minutes discussion of the results. A grade will be given based on the term paper, a review of another term paper and final presentation as defined in the module description.
Please submit your term paper to EasyChair.
According to OBS, the course capacity is 12 seats. Eventually, additional seats can be offered. If you don’t get a seat in the allocation period, please join the kickoff and ask for an additional seat. If you got allocated a seat but can not join the kickoff, please get in touch with me by email before the kickoff. Otherwise, your seat will be revoked.
Student groups (1-2 persons) may select their own topic or choose a topic from the following list:
- Soft Biometrics in Iris Recognition: While not necessarily unique to an individual, soft biometric attributes, e.g. gender or ethnicity, can be employed in biometric systems in conjunction with primary biometric characteristics in order to improve or expedite recognition accuracy. Such attributes are typically obtained from primary biometric characteristics, are classifiable in predefined human understandable categories, and can be extracted in an automated manner. Intuitively, eye colour is the only soft biometric attribute, which can be naturally gleaned from an iris pattern acquired in visible band of light. However, the existence of further soft biometric attributes in the iris pattern, such as gender, has been alluded in medical literature. In past years, it has been shown that, soft biometric attributes, including gender and ethnicity as well as age, can be predicted from iris patterns using general purpose texture descriptors in combination with machine learning techniques. Based on a thorough literature study on iris-based soft biometrics students should compose a comprehensive survey summarizing, comparing and discussing results of existing works in the field, including biometrics as well as medical research.
- Homomorphic Encryption in Voice Biometrics: Voice biometrics is emerging as an additional factor in online banking applications. In order to cope with latest European data privacy regulations, voice templates need to be stored and processed in a protected feature space. Over the past decade, template protection became well-established for image-based biometrics, where homomorphic encryption allows to biometric comparisons in an encrypted and protected feature space. In voice biometrics, speakers are compared based on their voice divergence from an universal acoustical cluster. Comparisons are carried out in latent feature spaces for the purpose of deriving likelihood ratios (same/different subject). Based on a thorough literature study on homomorphic encryption in voice biometrics, students should compose a comprehensive survey summarizing existing literature, and point out several approaches to examine in future research. One approach should be depicted with emphasis on comparing latent variables.
- Joint Factor Analysis in dynamic Handwriting Recognition: Dynamic handwriting recognition utilizes information of the writing process e.g., coordinates and pressure in time intervals, in order to compare subjects with higher security to forgeries. Targeting so called skilled forgeries, conventionally participants are donating a series of skilled forgeries each targeting five other participants in well-established online signature databases. However, rather than recognizing identity thefts, focus can also be put on recognizing impostors. Joint factor analysis (JFA) is motivated by speaker recognition, i.e. separating contextual features from biometric features, such that biometric comparisons are conducted excluding non-biometric effects, such as the written text. Based on a thorough literature study, students should compose a comprehensive literature survey, summarizing relevant aspects of dynamic signature recognition and JFA, comparing JFA towards well-established comparison approaches pointing out pros & cons regarding different robustness criteria. Students will work together with a student assistant of the da/sec research group, who will carry out experimental analysis suggested by the student group.
- Deanonymisation in TOR: The goal is to give an overview of the state-of-the-art in finding hints about the actual identity of users in the TOR network.
- Correlation and aggregation techniques of distributed security events
- Ethics in testing mitigation and response capabilities
- Review MTD (Moving Target Defense) strategies and its effectiveness against DDoS
The presentation will take place on 9th of february, 2017 from 09:30 a.m to 04:00 p.m in room D19/203a.
The final grade will be calculated out of the paper, the presentation of the results (40 min) and their discussions (20 min), and the participation on every other presentation.
The agenda is as follows:
09:30 – 10:30 Forensik 1
10:40 – 11:40 Biometrie 2
11:40 – 12:40 Mittag
12:40 – 13:40 Forensik 2
13:50 – 14:50 Netzwerksicherheit
15:00 – 16:00 Biometrie 1
Please bring your own laptop and ensure it works with VGA or HDMI.