Scalable Trust Management model for Machine To Machine communication in Internet of Things using Fuzzy approach

Revolution in Machine to Machine (M2M) Communication in Internet of Things (IoT) provides smart services in all verticals. These smart heterogeneous devices can be constraint or powerful devices that are generating sensitive information and introducing new challenges in security, privacy, and trust in devices to get and provide services in a distributed fashion. These challenges are overcome by providing scalable decentralized trust management for the access control system. Trust-based security models are more reliable over cryptographic security to identify and mitigate different inside threats by assessing the trust scores. This paper proposed Scalable Trust Management (STM) using a fuzzy approach and parameters like Experience, Recommendation, and device classification are used to calculate the crisp value of the trust score. While designing rule for trust score capacity of device is considered. The simulation of STM in NS2 ensures good performance and its result guarantees scalability and energy efficiency in the heterogeneous network.

The correlation between stock returns before and after analyst recommendation revisions

In this study I analyse the correlation between stock returns before and after analyst recommendation revisions. I hypothesise that if a recommendation revision for a given stock takes place after a short period when the stock?s price moves in the opposite direction, it may indicate that the fundamentals that caused the analyst to revise their recommendation are less completely (if at all) incorporated in the stock price, significantly increasing the probability of subsequent post-event price drift. Analysing a large sample of recommendation revisions, I document that both recommendation upgrades and downgrades are followed by significant one-tosix-month price drifts (reversals) if they are preceded by the opposite-sign (same-sign) short-term cumulative abnormal returns. The effect remains significant after accounting for additional relevant company specific (size, Market Model beta, historical volatility) and event-specific (stock?s return and trading volume on the event day, brokerage firm size, analyst experience, recommendation category before the revision, number of categories changed in the revision) factors.

The Impact of Status Seeking on Consumers’ Word of Mouth and Product Preference—A Comparison Between Luxury Hospitality Services and Luxury Goods

Despite the rapid growth of the luxury hospitality market, academic research has largely neglected the differences between luxury hospitality services and luxury goods, as well as the role of status seeking on luxury consumption. Relying on the status consumption and experience recommendation theories, the authors examine the combined effects of consumer characteristics (need for status) and product type (hospitality services vs. goods) on consumers’ word-of-mouth intentions. The results suggest that parvenus, who are high in need for status, are more likely to talk about their luxury goods purchases than patricians, who are low in need for status. More interestingly, both parvenus and patricians indicate equally strong intentions to spread positive word of mouth on luxury hospitality purchases. This study also extends the experience recommendation theory and reveals that parvenus are less likely to choose luxury hospitality services than patricians to advance their happiness.