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This study aims to investigate the shopping behaviour of consumers, mainly in fashion apparels, and intends to understand consumer buying patterns in Indian context. The study was designed to determine the level of consumer's sense of belonging towards apparel shopping by applying the concept of self-congruence.

The study used variance-based partial least squares structural equational modelling (PLS-SEM) on a cross-sectional study conducted on 569 consumers. The study was conducted by using questionnaire to collect the responses from the central zone of India. The results support most of the projected hypotheses.

The study focused on the shopping behaviour of consumer such as self-congruence, impulse buying, hedonic values and consumer satisfaction. The results of the study highlight the association of constructs and analysed the mediation relation of hedonic and impulse buying constructs. The results revealed a positive association among the constructs and also found a partial mediation effect in their relation with constructs.

The findings are outcomes of an empirical study conducted in the fashion apparel industry of India based on the sample set of urban consumers. The study is restricted to the direct and indirect relationship of constructs. Further, research can examine by using moderating constructs like demographic factors (gender, age, income, etc.) and other shopping behaviours (like brand loyalty, brand love, brand attachment) for more clarity in results. Moreover, the study limited is with fashion apparel, whereas there are many categories in the fashion industry like accessories, perfumes, cosmetic products, footwear and also other products industry.

The study provided valuable inputs to the literature of marketing where self-congruence affects consumer shopping behaviour such as impulse buying, hedonic values and consumer satisfaction. The study proposes a practical approach that can help the marketing professionals and product developers to have a deep understanding about consumer shopping behaviour for facilitating consumer-oriented goods in the Indian fashion industry.

This is one of the first studies in the fashion industry to test the association of self-congruence with hedonic value and consumer satisfaction. This relation is not tested in context of fashion apparel. Additionally, this study also examined the mediating effect of hedonic value and impulse buying in relation with self-congruence and consumer satisfaction in the Indian context.

A zero-day vulnerability is a complimentary ticket to the attackers for gaining entry into the network. Thus, there is necessity to device appropriate threat detection systems and establish an innovative and safe solution that prevents unauthorised intrusions for defending various components of cybersecurity. We present a survey of recent Intrusion Detection Systems (IDS) in detecting zero-day vulnerabilities based on the following dimensions: types of cyber-attacks, datasets used and kinds of network detection systems.

Purpose: The study focuses on presenting an exhaustive review on the effectiveness of the recent IDS with respect to zero-day vulnerabilities.

Methodology: Systematic exploration was done at the IEEE, Elsevier, Springer, RAID, ESCORICS, Google Scholar, and other relevant platforms of studies published in English between 2015 and 2021 using keywords and combinations of relevant terms.

Findings: It is possible to train IDS for zero-day attacks. The existing IDS have strengths that make them capable of effective detection against zero-day attacks. However, they display certain limitations that reduce their credibility. Novel strategies like deep learning, machine learning, fuzzing technique, runtime verification technique, and Hidden Markov Models can be used to design IDS to detect malicious traffic.

Implication: This paper explored and highlighted the advantages and limitations of existing IDS enabling the selection of best possible IDS to protect the system. Moreover, the comparison between signature-based and anomaly-based IDS exemplifies that one viable approach to accurately detect the zero-day vulnerabilities would be the integration of hybrid mechanism.