Abstract-It is a suitable means for multi-messages to usehybrid encryption to make a safe communication. Hybrid encryption confines encryption into two parts: one part uses public key systems to scramble a one-time symmetric key, and the other part uses the symmetric key to scramble the actual message. The quick advancement of the internet technology requires distinctive message communications over the more extensive territory to upgrade the heterogeneous system security. In this paper, we present a lightweight multi-message and multireceiver Heterogeneous hybrid signcryption scheme based on the hyper elliptic curve. We choose hyper elliptic curve for our scheme, because with 80 bits key give an equivalent level of security as contrasted and different cryptosystems like RSA and Bilinear pairing with 1024 bits key and elliptic curve with 160 bits key, respectively. Further, we validate these security requirements with our scheme, for example, confidentiality, resistance against reply attack, integrity, authenticity, nonrepudiation, public verifiability, forward secrecy and unforgeability through a well-known security validation tool called Automated Validation of Internet Security Protocols and Applications (AVISPA). In addition, our approach has low computational costs, which is attractive for low resources devices and heterogeneous environment.Keywords-Multi-receiver heterogeneous hybrid signcryption; multi-message and multi-receiver heterogeneous hybrid signcryption; hyper elliptic curve; Automated Validation of Internet Security Protocols and Applications (AVISPA)
Rivest, Shamir, & Adleman (RSA), bilinear pairing, and elliptic curve are well-known techniques/algorithms for security protocols. These techniques suffer from higher computation and communication costs due to increased sizes of parameters, public keys, and certificates. Hyper-elliptic curve has lower parameter size, public key size, and certificate size. The aim of the proposed work is to reduce the computational cost and communication cost. Furthermore, we validate the security properties of our proposed scheme by using the well-known simulation tool called automated validation of Internet security protocols and applications. Our approach ensures security properties such as resistance against replay attack, confidentiality, authenticity, unforgeability, integrity, non-repudiation, public verifiability, and forward secrecy.
With the growing information on web, online movie review is becoming a significant information resource for Internet users. However, online users post thousands of movie reviews on daily basis and it is hard for them to manually summarize the reviews. Movie review mining and summarization is one of the challenging tasks in natural language processing. Therefore, an automatic approach is desirable to summarize the lengthy movie reviews, and it will allow users to quickly recognize the positive and negative aspects of a movie. This study employs a feature extraction technique called bag of words (BoW) to extract features from movie reviews and represent the reviews as a vector space model or feature vector. The next phase uses Naïve Bayes machine learning algorithm to classify the movie reviews (represented as feature vector) into positive and negative. Next, an undirected weighted graph is constructed from the pairwise semantic similarities between classified review sentences in such a way that the graph nodes represent review sentences, while the edges of graph indicate semantic similarity weight. The weighted graph-based ranking algorithm (WGRA) is applied to compute the rank score for each review sentence in the graph. Finally, the top ranked sentences (graph nodes) are chosen based on highest rank scores to produce the extractive summary. Experimental results reveal that the proposed approach is superior to other state-of-the-art approaches.
Search Engine Optimization (SEO) plays a very vital role in the development of professional websites. There are some search engines available on the internet such as Yahoo, Ask.com, AOL.com, Baidu, and Bing. Among which Google is the most widely used search engine. Each search engine uses different SEO technique and algorithm, which not only forms the foundation of SEO but affects the position of a website in organic search results as well. As Google modify its algorithm about 500 or more times per year, the web design and internet also evolves dynamically because of changes in SEO techniques and algorithms. However, how well Malaysian universities websites are optimized for other search engines is questionable particularly the critical differences between search engine ranking techniques and algorithms. This research paper tends to answer these vital questions by proposing a comparative analysis of Bing and Google on some Malaysian universities website, analyzing their search engine optimization parameters and outcomes of using Microsoft Bing as compared to its primary competitor, Google.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.