University of Isfahan & Iranian Society of CryptologyJournal of Computing and Security2322-44603420161001On the Security of Permutation Based Authentication Protocols for Internet of Things Applications: The Case of Huang et al.'s Protocol20120922574ENSamadRostampourDepartment of Computer Engineering, Science and Research branch, Islamic Azad University, Tehran, IranNasourBagheriDepartment of Electrical Engineering, Shahid Rajaee Teachers Training University, Tehran, IranMehdiHosseinzadehDepartment of Electrical Engineering, Shahid Rajaee Teachers Training University, Tehran, IranAhmadKhademzadehIran Telecommunication Research Center, Tehran, IranJournal Article20170120The Internet of Things (IoT) is a new technology, which enables objects to exchange data via the Internet. Authentication process is a method to prevent an unauthorized access to the IoT systems. The using of bit-wise functions such as XOR, Shift and Rotation could decrease the cost of authentication protocols. On the other hand, the simple operations usually could not provide an acceptable security level. Therefore, the researchers try to improve the security level by creating new permutation functions. In this paper, we evaluate some permutation functions and analyze a protocol which recently has been proposed by Huang et al. We prove that their protocol is vulnerable to the disclosure and the impersonation attacks and an adversary can clone a valid tag easily. The complexity of the proposed attack is low and attack method works efficiently for the secret keys and ID numbers with variable length.https://jcomsec.ui.ac.ir/article_22574_c9b080d947657d1e1f21c859bc245727.pdfUniversity of Isfahan & Iranian Society of CryptologyJournal of Computing and Security2322-44603420161001Multicollision Attack on a recently proposed hash function vMDC-221121522575ENZahraZolfaghariShahid Rajaee Teacher Training UniversityHamidAsadollahiShahid Rajaee Teacher Training UniversityNasourBagheriShahid Rajaee Teacher Training UniversityJournal Article20161210In this paper, we describe an attack on a new double block length hash function which was proposed as a variant of MDC-2 and MDC-4. The vMDC-2 compression function is based on two calls to a block cipher that compresses a 3n-bit string to a 2n-bit one. This attack is based on the Joux's multicollision attack, where we show that an adversary wins finding collision game by requesting $2^{70}$ queries for $ n=128$-bit block cipher that is much less than the complexity of birthday attack.https://jcomsec.ui.ac.ir/article_22575_d9afd4a4e3982aa266b142bb10981c38.pdfUniversity of Isfahan & Iranian Society of CryptologyJournal of Computing and Security2322-44603420161001Randomized SVD Based Probabilistic Caching Strategy in Named Data Networks21723122576ENNargesMehranNaserMovahhediniaUniversity of IsfahanJournal Article20161129Named Data Networking (NDN), a data-centric enabled-cache architecture, as one of the candidates for the future Internet, has the potential to overcome many of the current Internet difficulties (\emph{e.g.}, security, mobility, multicasting). Influenced by using cache in intermediate equipment, NDN has gained attention as a prominent method of Internet content sharing. Managing the NDN caches and reducing the cache redundancy are the important goals in this paper. Our main contribution in this research is toward caching optimization in comparison with betweenness probabilistic in-network caching strategy. Therefore, with respect to combined impacts of long-term centrality-based metric and Linear Weighted Moving Average (LWMA) of short-term parameters such as user incoming pending requests and unique outgoing hit requests on caching management, a flexible probability caching strategy is proposed. Moreover, a simple Randomized-SVD approach is applied to combine averaged short-term and long-term metrics. The output of this data-fusion algorithm is used to allocate a proper probability to the caching strategy. Evaluation results display an increase in the hit ratios of NDN routers' content-stores for the proposed method. In addition, the producer's hit ratio and the Interest-Data Round Trip Time, compared to the betweenness scheme, is decreased.https://jcomsec.ui.ac.ir/article_22576_a32687f17618e9cbd52bc3ce147be5a3.pdfUniversity of Isfahan & Iranian Society of CryptologyJournal of Computing and Security2322-44603420161001Persian Texts Part of Speech Tagging Using Artificial Neural Networks23324122577ENZahraHosseini PozvehScience and research branch
Islamic Azad university,
TehranAmirhassanMonadjemiUniversity of IsfahanAliAhmadiKhajeh Nasir Toosi University of TechnologyJournal Article20150728Part of speech tagging (POS) is a basic task in natural language processing applications such as morphological parsing, information retrieval, machine translation and question answering. POS Tagging is the task of giving a word its part of speech (e.g. noun or verb). It is followed by a lot of challenging steps, in particular, disambiguation, named entity recognition and compound verb detection. Most of tagging approaches for Persian language are focused on the hidden Markov models (HMMs) and rule based models. Since Persian is a free word order language, those models cannot cope with all the complexity of this language for POS tagging, named entity, word sense disambiguation and other related tasks. In this paper, artificial neural networks (ANNs) are used for POS tagging due to their ability to learn complex patterns. In the first study ANN is fed with raw data and in the second phase, data are clustered and multiple ANNs are trained separately for each cluster. The accuracy rates of 95.7% and 96.17% were received respectively. Comparing the results with the other approaches makes it clear that neural networks can do POS tagging and named entity recognition more precise than other methods.https://jcomsec.ui.ac.ir/article_22577_2ad63880a788e9cbaa4e333396a9f6dc.pdf