Search

In the age of digital transformation with adoption of Cloud and mobile computing and ever-increasing Internet of Things(IoT) devices, the cybersecurity risks and threat levels are increasing at a rapid pace. The data is spread across systems, devices and cloud leading to growing attack surface and increased frequency of the security attacks. IoT is extended to drones, driver-less cars, industrial equipment, smart buildings, consumer goods, home appliances leaving us with more vulnerable attack points. Organizations needs to have effective information security management system (ISMS) in place to proactively detect, react to security threats with reduced time to discover any potential breach. This paper highlights how Artificial Intelligence(AI) and Machine Learning(ML) can redefine cybersecurity to detect, prevent organizations from security threats and data breaches.

Temporal and spatial trends of the surface urban heat island (UHI) formation over Delhi are examined with respect to aerosol load and land-cover variations. The study reveals that temperatures over Delhi are higher than those over the surrounding regions almost through-out the year during the night time. The nocturnal heat island intensity is minimum (0–2 K) during the monsoon months and maximum during the month of March (4–6 K). The UHI trends during the day-time are however, significantly different. It is observed that a day-time cool island forms over Delhi twice during the year in the months of May–June and October–December. Analysis of temporal variations in urban heat island intensity (UHII) and aerosol load over Delhi reveals a significant negative correlation between UHII and aerosol optical depth (AOD). Spatial analysis of LST, land-cover and AOD for the months of March, May and November confirms the significant role of AOD along with land-cover variables such as percentage area under the classes built-up, rock, vegetation and bare soil. Comparative analysis of LST in the regions lying north, south, east and west of Delhi in relation to the prevailing land-cover suggests that thermal inertia is also a very important factor determining the urban-rural thermal structure.

Temporal and spatial trends of the surface urban heat island (UHI) formation over Delhi are examined with respect to aerosol load and land-cover variations. The study reveals that temperatures over Delhi are higher than those over the surrounding regions almost through-out the year during the night time. The nocturnal heat island intensity is minimum (0–2 K) during the monsoon months and maximum during the month of March (4–6 K). The UHI trends during the day-time are however, significantly different. It is observed that a day-time cool island forms over Delhi twice during the year in the months of May–June and October–December. Analysis of temporal variations in urban heat island intensity (UHII) and aerosol load over Delhi reveals a significant negative correlation between UHII and aerosol optical depth (AOD). Spatial analysis of LST, land-cover and AOD for the months of March, May and November confirms the significant role of AOD along with land-cover variables such as percentage area under the classes built-up, rock, vegetation and bare soil. Comparative analysis of LST in the regions lying north, south, east and west of Delhi in relation to the prevailing land-cover suggests that thermal inertia is also a very important factor determining the urban-rural thermal structure.