TY - GEN
AB - We present a new transformation of chosen-plaintext secure predicate encryption schemes with public index into chosen-ciphertext secure schemes. Our construction requires only a universal one-way hash function and is selectively secure in the standard model. The transformation is not generic but can be applied to various existing schemes constructed from bilinear groups. Using common structural properties of these schemes we provide an efficient and simple transformation without overhead in form of one-time signatures or message authentication codes as required in the known generic transformations.
AU - Blömer, Johannes
AU - Liske, Gennadij
ID - 442
TI - Constructing CCA-secure predicate encapsulation schemes from CPA-secure schemes and universal one-way hash functions
ER -
TY - GEN
AU - Pauck, Felix
ID - 418
TI - Generierung von Eigenschaftsprüfern in einem Hardware/Software-Co-Verifikationsverfahren
ER -
TY - CONF
AU - Yasasin, Emrah
AU - Rauchecker, Gerhard
AU - Prester, Julian
AU - Schryen, Guido
ID - 5573
T2 - 1st Workshop on Security in highly connected IT systems (SHCIS 14)
TI - A Fuzzy Security Investment Decision Support Model for Highly Distributed Systems
ER -
TY - JOUR
AU - Wex, Felix
AU - Schryen, Guido
AU - Feuerriegel, Stefan
AU - Neumann, Dirk
ID - 5585
JF - European Journal of Operational Research
TI - Emergency Response in Natural Disaster Management: Allocation and Scheduling of Rescue Units
ER -
TY - JOUR
AB - Natural disasters, including earthquakes, Tsunamis, floods, hurricanes, and volcanic eruptions, have caused tremendous harm and continue to threaten millions of humans and various infrastructure capabilities each year. In their efforts to take countermeasures against the threats posed by future natural disasters, the United Nations formulated the ?Hyogo Framework for Action?, which aims at assessing and reducing risk. This framework and a global review of disaster reduction initiatives of the United Nations acknowledge the need for information systems research contributions in addressing major challenges of natural disaster management. In this paper, we provide a review of the literature with regard to how information systems research has addressed risk assessment and reduction in natural disaster management. Based on the review we identify research gaps that are centered around the need for acquiring general knowledge on how to design IS artifacts for risk assessment and reduction. In order to close these gaps in further research, we develop a research agenda that follows the IS design science paradigm.
AU - Schryen, Guido
AU - Wex, Felix
ID - 5614
IS - 1
JF - International Journal of Information Systems for Crisis Response and Management (IJISCRAM)
KW - Natural Disaster Management
KW - Risk Reduction
KW - Hyogo Framework
KW - IS Design Science
KW - Literature review
TI - Risk Reduction in Natural Disaster Management Through Information Systems: A Literature review and an IS design science research agenda
VL - 6
ER -
TY - JOUR
AU - Schryen, Guido
AU - Hristova, Diana
ID - 5627
IS - 1
JF - OR -Spectrum
TI - Duality in fuzzy linear programming: A survey
VL - 37
ER -
TY - JOUR
AU - Schryen, Guido
ID - 5636
JF - Communications of the AIS
TI - Writing qualitative IS literature reviews ? Guidelines for synthesis, interpretation and guidance of research
ER -
TY - CONF
AB - "A method for nonstationary noise robust automatic speech recognition (ASR) is to first estimate the changing noise statistics and second clean up the features prior to recognition accordingly. Here, the first is accomplished by noise tracking in the spectral domain, while the second relies on Bayesian enhancement in the feature domain. In this way we take advantage of our recently proposed maximum a-posteriori based (MAP-B) noise power spectral density estimation algorithm, which is able to estimate the noise statistics even in time-frequency bins dominated by speech. We show that MAP-B noise tracking leads to an improved noise model estimate in the feature domain compared to estimating noise in speech absence periods only, if the bias resulting from the nonlinear transformation from the spectral to the feature domain is accounted for. Consequently, ASR results are improved, as is shown by experiments conducted on the Aurora IV database."
AU - Chinaev, Aleksej
AU - Puels, Marc
AU - Haeb-Umbach, Reinhold
ID - 11746
T2 - 11. ITG Fachtagung Sprachkommunikation (ITG 2014)
TI - Spectral Noise Tracking for Improved Nonstationary Noise Robust ASR
ER -
TY - CONF
AB - "In this contribution we derive a variational EM (VEM) algorithm for model selection in complex Watson mixture models, which have been recently proposed as a model of the distribution of normalized microphone array signals in the short-time Fourier transform domain. The VEM algorithm is applied to count the number of active sources in a speech mixture by iteratively estimating the mode vectors of the Watson distributions and suppressing the signals from the corresponding directions. A key theoretical contribution is the derivation of the MMSE estimate of a quadratic form involving the mode vector of the Watson distribution. The experimental results demonstrate the effectiveness of the source counting approach at moderately low SNR. It is further shown that the VEM algorithm is more robust w.r.t. used threshold values."
AU - Drude, Lukas
AU - Chinaev, Aleksej
AU - Tran Vu, Dang Hai
AU - Haeb-Umbach, Reinhold
ID - 11752
T2 - 39th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014)
TI - Source Counting in Speech Mixtures Using a Variational EM Approach for Complexwatson Mixture Models
ER -
TY - CONF
AB - This contribution describes a step-wise source counting algorithm to determine the number of speakers in an offline scenario. Each speaker is identified by a variational expectation maximization (VEM) algorithm for complex Watson mixture models and therefore directly yields beamforming vectors for a subsequent speech separation process. An observation selection criterion is proposed which improves the robustness of the source counting in noise. The algorithm is compared to an alternative VEM approach with Gaussian mixture models based on directions of arrival and shown to deliver improved source counting accuracy. The article concludes by extending the offline algorithm towards a low-latency online estimation of the number of active sources from the streaming input data.
AU - Drude, Lukas
AU - Chinaev, Aleksej
AU - Tran Vu, Dang Hai
AU - Haeb-Umbach, Reinhold
ID - 11753
KW - Accuracy
KW - Acoustics
KW - Estimation
KW - Mathematical model
KW - Soruce separation
KW - Speech
KW - Vectors
KW - Bayes methods
KW - Blind source separation
KW - Directional statistics
KW - Number of speakers
KW - Speaker diarization
T2 - 14th International Workshop on Acoustic Signal Enhancement (IWAENC 2014)
TI - Towards Online Source Counting in Speech Mixtures Applying a Variational EM for Complex Watson Mixture Models
ER -