@article {ElHadj201786,
	title = {ABAC rule reduction via similarity computation},
	journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
	volume = {10299 LNCS},
	year = {2017},
	note = {cited By 0},
	pages = {86-100},
	abstract = {Attribute-based access control (ABAC) represents a generic model of access control that provides a high level of flexibility and promotes information and security sharing. Since ABAC considers a large set of attributes for access decisions, using it might get very complicated for large systems. Hence, it is interesting to offer techniques to reduce the number of rules in ABAC policies without affecting the final decision. In this paper, we present an approach based on K-nearest neighbors algorithms for clustering ABAC policies. To the best of our knowledge, it is the first approach that aims to reduce the number of policy rules based on similarity computations. Our evaluation results demonstrate the efficiency of the suggested approach. For instance, the reduction rate can reach up to 10\% for an ABAC policy with more than 9000 rules. {\textcopyright} Springer International Publishing AG 2017.},
	doi = {10.1007/978-3-319-59647-1_7},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85019735144\&doi=10.1007\%2f978-3-319-59647-1_7\&partnerID=40\&md5=948de8bee1016664b63163965c4e41fa},
	author = {El Hadj, M.A. and Benkaouz, Y. and Freisleben, B. and Erradi, M.}
}
@article {Ayache2017166,
	title = {Aspect-oriented state machines for resolving conflicts in XACML policies},
	journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
	volume = {10299 LNCS},
	year = {2017},
	note = {cited By 0},
	pages = {166-171},
	abstract = {Authorizationin collaborativesystemsisdefinedbyaglobal policy that represents the combination of the collaborators{\textquoteright} access policies. However, the enforcement of such a global policy may create conflicting authorization decisions. In this paper, we categorize two types of conflicts that may occur in such policies. Furthermore, to resolve these conflicts and to reach a unique decision for an access request, we present an approach that uses XACML policy combining algorithms and considers the category of the detected conflicts. The approach is implemented using aspect-oriented finite state machines. {\textcopyright} Springer International Publishing AG 2017.},
	doi = {10.1007/978-3-319-59647-1_13},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85019731058\&doi=10.1007\%2f978-3-319-59647-1_13\&partnerID=40\&md5=917cf51c38e853e2423ad411ec1ecadb},
	author = {Ayache, M. and Erradi, M. and Freisleben, B. and Khoumsi, A.}
}
@conference {Elaalyani2017,
	title = {Current trends in text-spotting},
	booktitle = {Proceedings - 2017 International Conference on Wireless Networks and Mobile Communications, WINCOM 2017},
	year = {2017},
	note = {cited By 0},
	abstract = {Text spotting, i.e., the localization and recognition of text occurrences in natural images and videos, is a challenging problem in computer vision. Important applications of text spotting are: video indexing, retrieval and search, the support of blind persons in finding their way in unknown environments and reading street and shop signs for autonomously driving vehicles or car license plate recognition in traffic control systems. Recently, the use of deep convolutional neural networks as well as recognizing whole words instead of single characters led to significant progress in the field of text spotting. Furthermore, there is a tendency towards merging and unifying the single steps of the text spotting pipeline. Despite current progress, it is still difficult to recognize in-scene text in comparison to overlaid text. This work gives an overview of the state-of-the-art in text spotting and highlights current breakthroughs and trends. {\textcopyright} 2017 IEEE.},
	doi = {10.1109/WINCOM.2017.8238215},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041435238\&doi=10.1109\%2fWINCOM.2017.8238215\&partnerID=40\&md5=a2aecbf47ec51f3f316606d512724a5a},
	author = {Elaalyani, I. and Erradi, M. and M{\"u}hling, M. and Freisleben, B.}
}
