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The advent of the Android system has brought smartphone technology to the doorsteps of the masses. The latest technologies have made it affordable for every section of the society. However, the emergence of the Android platform has also escalated the growth of cybercrime through the mobile platform. Its open source operating system has made it a center of attraction for the attackers. This article provides a comprehensive study of the state of the Android Security domain. This article classifies the attacks on the Android system in four categories (i) hardware-based attacks, (ii) kernel-based attacks, (iii) hardware abstraction layer-based attacks, and (iv) application-based attacks. The study deals with various threats and security measures relating to these categories and presents an in-depth analysis of the underlying problems in the Android security domain. The article also stresses the role of Android application developers in realizing a more secure Android environment. This article attempts to provide a comparative analysis of various malware detection techniques concerning their methods and limitations. The study can help researchers gain knowledge of the Android security domain from various aspects and build a more comprehensive, robust, and efficient solution to the threats that Android is facing.

Machine Learning Approach for the Classification of Demonstrative Pronouns for Indirect Anaphora in Hindi News Items In this paper, we present machine learning approach for the classification indirect anaphora in Hindi corpus. The direct anaphora is able to find the noun phrase antecedent within a sentence or across few sentences. On the other hand indirect anaphora does not have explicit referent in the discourse. We suggest looking for certain patterns following the indirect anaphor and marking demonstrative pronoun as directly or indirectly anaphoric accordingly. Our focus of study is pronouns without noun phrase antecedent. We analyzed 177 news items having 1334 sentences, 780 demonstrative pronouns of which 97 (12.44 %) were indirectly anaphoric. The experiment with machine learning approaches for the classification of these pronouns based on the semantic cue provided by the collocation patterns following the pronoun is also carried out.

In recent years, Mobile Ad hoc NETworks (MANETs) have generated great interest among researchers in the development of theoretical and practical concepts, and their implementation under several computing environments. However, MANETs are highly susceptible to various security attacks due to their inherent characteristics. In order to provide adequate security against multi-level attacks, the researchers are of the opinion that detection-based schemes should be incorporated in addition to traditionally used prevention techniques because prevention-based techniques cannot prevent the attacks from compromised internal nodes. Intrusion detection system is an effective defense mechanism that detects and prevents the security attacks at various levels. This paper tries to provide a structured and comprehensive survey of most prominent intrusion detection techniques of recent past and present for MANETs in accordance with technology layout and detection algorithms. These detection techniques are broadly classified into nine categories based on their primary detection engine/(s). Further, an attempt has been made to compare different intrusion detection techniques with their operational strengths and limitations. Finally, the paper concludes with a number of future research directions in the design and implementation of intrusion detection systems for MANETs.