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Internet of Things (IoT) is an innovative era of interrelated devices to provide services to other devices or users. In Social Internet of Thing (SIoT), social networking aspect is used for building relationships between devices. For providing or utilizing services, devices need to trust each other in complex and heterogeneous environments. Separating benign and malicious devices in SIoT is a prime security objective. In literature, several works proposed trust computation models based on trust features. But these models fail to identify malicious devices. This paper focuses on detection of malicious devices. In this paper, basic fundamentals, properties, models and attacks of trust in SIoT are discussed. Up-to-date research distributions on trust management and trust attacks are reviewed and idea of Trust Management using Machine Learning Algorithm (TM-MLA) is proposed for identification of malicious devices.

A shock wave-driven needle-free syringe was developed and tested for liquid jet delivery into an artificial skin model and porcine skin samples. The device could deliver an adequate volume of liquid to a depth sufficient for drug dissemination in skin samples. The device is equipped with a splash-proof conduit and a silencer for smooth operation. The concept is expected to minimize the pain of liquid injection by (a) minimally breaching the blood vessels in the skin, (b) reducing trauma and inflammation, and aiding in regeneration of the incised spot by the liquid of the jet, and (c) preserving most of the microcirculation system in the target, enabling an effective drug uptake. A theoretical model that predicts jet penetration into viscoelastic targets is derived and presented. A sound agreement has been observed between the experimental jet penetration depths and the corresponding theoretical predictions. The development can offer a cost-effective, minimally invasive health care solution for immunization and drug delivery.

Granular matter exhibits interesting patterns and instabilities that in many practical situations become critically important and require a proper understanding. Many of these phenomena arise because of small perturbations and instability waves that are present within the flow system. In the present work, we study the characteristics of interfacial waves that are generated when two streams of granular material move together side-by-side on an inclined chute. The streams are gravity driven and are composed of monodisperse grains of same material but different grain size. As the grains accelerate down, the chute instabilities appear on the interface, which grow into finite, quasi-periodic waves. Under certain experimental conditions, the waves are shown to locally induce the cross-stream mixing of grains. The mechanism of formation of interfacial waves is found to be sensitive to grain size and velocities of granular streams, which are varied by changing the chute inclination.

Shock–shock interaction structures and a newly discovered dynamic instability in granular streams resulting from such interactions are presented. Shock waves are generated by placing two similar triangular wedges in a gravity-driven granular stream. When the shock waves interact, grains collapse near the centre region of the wedges and a slow-moving concentrated diamond-shaped streak of grains is formed that grows as the inclination of the channel is increased. The diamond streak, under certain geometric conditions, is found to become unstable and start oscillating in the direction transverse to the mainstream. When the wedges are placed too close to each other, the granular flux of the incoming stream is unable to pass through the small gap, resulting in the formation of a single bow shock enveloping both the wedges. Experiments are performed for a wide range of flow speeds, wedge angles and wedge separations to investigate the interaction zone. We discuss a possible mechanism for the formation of the central streak and the associated dynamic instability observed for specific physical parameters.