This article introduces a sentiment analysis approach that adopts the way humans read, interpret, and extract sentiment from text. Our motivation builds on the assumption that human interpretation should lead to the most accurate assessment of sentiment in text. We call this automated process Human Reading for Sentiment (HRS). Previous research in sentiment analysis has produced many frameworks that can fit one or more of the HRS aspects; however, none of these methods has addressed them all in one approach. HRS provides a meta-framework for developing new sentiment analysis methods or improving existing ones. The proposed framework provides a theoretical lens for zooming in and evaluating aspects of any sentiment analysis method to identify gaps for improvements towards matching the human reading process. Key steps in HRS include the automation of humans low-level and high-level cognitive text processing. This methodology paves the way towards the integration of psychology with computational linguistics and machine learning to employ models of pragmatics and discourse analysis for sentiment analysis. HRS is tested with two state-of-the-art methods; one is based on feature engineering, and the other is based on deep learning. HRS highlighted the gaps in both methods and showed improvements for both.

The Domain Name System is a crucial part of the Internet's infrastructure, as it provides basic information that is vital for the proper operation of the Internet. The importance of DNS has caused it to be targeted by malicious attackers who are interested in causing damage and gaining personal benefits. Thus nowadays, DNS faces many security threats such as DNS spoofing and cache poisoning attacks. This paper presents S-DNS, an efficient security solution for thwarting cache poisoning attacks in the DNS hierarchy. The contribution of the S-DNS protocol lies in: (1) decreasing the success probability of DNS spoofing and cache poisoning by preventing man-in-the-middle attacks, (2) providing a backward compatible and simple security solution with low computation and communication overheads, (3) targeting the different DNS query interaction models from iterative, recursive, and caching schemes, and (4) employing an efficient IdentityBased Encryption key management scheme that relieves the different DNS interacting entities from the burden and complexities of traditional public-key infrastructures.

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