Data loss prevention (dlp), deployed in the network and on user devices, gives operations visibility into the movement of sensitive data and can block inappropriate access, the associated risks of the threats (that is, how relevant those threats are for a particular system) the cost to implement the proper security countermeasures for a threat; a cost versus benefit analysis to determine whether it is worthwhile to implement the security countermeasures; data, vulnerabilities, and countermeasures.
Risks arising in analytic processing analysis of the data can introduce other risks, generally, however, with many third-party, off-the-shelf technologies, such platforms are designed for the business user to change parameters on-the-fly via simple point-and-click interfaces.
Many businesses are choosing private cloud with edge computing to ensure data moves fast and securely from the iot devices to a cloud network. Despite the improvements in recovery technology and the use of cloud-based systems, the likelihood of damage to critical data and systems remains a major concern.
In addition to technology-related risks, there are risks associated with the integration of these technologies with existing information systems, with the business model that these technologies impose on supplier-customer relations, and with the security and control mechanisms required to ensure their appropriate use, luckily cloud providers and users mature security capabilities are constantly improving.