No abstract

Named Data Networking (NDN) is one of the future envisioned networking paradigm used to provide fast and efficient content dissemination with interest-based content retrieval, name-based routing and in-network content caching. On the one hand, this new breed of future Internet architecture is becoming a key technology for data dissemination in the IoT networks; on the other hand, NDN suffers from new challenges in terms of data security. Among them, a content poisoning attack is the most common data security challenge. The aim of this attack is to inject poisoned content with an invalid signature to the network. Therefore, to prevent NDN against possible content poisoning attack, a signature of the contents is appended to each data packet for verifications. In this paper, we propose an identity-based signature scheme for IoT-based NDN networks, with a special emphasis on content integrity and authenticity. The proposed scheme is based on the concept of the Hyperelliptic curves, which provide the same level of security as Rivest-Shamir-Adleman (RSA), Bilinear pairing and Elliptic Curve Cryptosystems (ECC) with lower-key size. The proposed scheme is subject to both formal and informal security analysis in order to show the feasibility of our scheme. Finally, the performance of the proposed scheme is analyzed via comparison with the relevant existing schemes that authenticates the superiority of our scheme in terms of security and efficiency. INDEX TERMS Content poisoning attack, named data networking (NDN), Internet of Things, identity-based signature.

Abstract. Natural Language Processing (NLP) is a well-known technique of artificial intelligence to extract the elements of concerns from raw plain text information. It can be utilized to process the early software requirements in order to achieve the goals like requirement prioritization and classification (functional and non-functional). To the best of our knowledge, no research work is available yet to examine and summarize the utilization of NLP in the domain of Software Requirement Engineering (SRE). Therefore, in this paper, we investigate the applications of NLP in the context of SRE. A Systematic Literature Review (SLR) is carried out to select 27 studies published during 2002-2016. Consequently, 6 NLP techniques and 14 existing tools are identified. Furthermore, 9 tools and 2 algorithms, proposed by the researchers, are presented. It has been concluded that the NLP techniques and tools are highly supportive to accelerate the SRE process. However, some manual operations are still required on initial plain text software requirements before applying the desired NLP techniques.

The number of vehicles on the roads has increased proportionally over the last couple of years and this number is likely to rise due to the increase in population growth and the number of vehicles that are manufacturing every day. This high traffic density leads to several problems, from which effectively disseminating the emergency messages is a major concern. Keeping in view the dynamic characteristics of VANETs, significant challenges are faced in disseminating the message across the network. The major challenges are the broadcast storm problem, hidden node problem and the packet collision. Many studies have been performed to devise an effective and reliable mechanism for disseminating emergency messages in a Vehicular ad-Hoc Network (VANET). Researchers have proposed different models to tackle various types of scenarios for emergency message dissemination. This paper not only reviews some recent contributions to emergency message dissemination in vehicular networks but also discusses various proposed methods based on Intelligent Transportation System (ITS), Internet of Things (IoT), Priority messaging, Clustering approach, Software Defined Network (SDN) and Fog Computing. We have also tried to explore the latest developments in emergency message dissemination using 5G networks.

Transactions related to vehicles include manufacturing, buying, selling, paying insurance(takaful), obtaining regular inspection, leasing a vehicle from banks, getting in an accident, engaging in a traffic violation, calculating price predictions and renting a vehicle. Many people perform transactions related to vehicles in their daily life; transportation authorities also perform vehicle transactions as part of managing vehicle fleets. But tracking these transactions is a challenging task. There are countrywide solutions that uses centralized systems. However, these solutions have problems with trust management, transparency, and access control. Therefore, we believe there is still room for integrated automation of various vehicle-related transactions. In this paper, we present a blockchainbased framework for vehicle tracking that incorporates the mentioned features. Moreover, blockchain is customized to enable usage control for additional transactions, such as inspection, renting and islamic insurance. The usage control model is integrated with IoT devices to continuously monitor the vehicles for certain conditions and remotely revoke access if needed [1]. The complete transaction set is recorded over an immutable ledger that provides trust, transparency and a complete history of record. In this paper, we also presents a prototype implementation of a permissioned blockchain, which will be made available under the GNUv3 General Public License. Performance analysis is performed on the newly proposed framework implementation over the permissioned blockchain to measure its adoption and suitability. INDEX TERMS Blockchain, decentralized applications, smart contracts, vehicle life cycle tracking VOLUME 4, 2016 This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication.