New White Paper Examines the Key Role of GhangorCloud Compliance and Privacy Enforcement Deep AI Platform

GhangorCloud, a leading provider of intelligent information security and data privacy compliance enforcement solutions, today announced the release of a white paper that examines the pivotal role of deep artificial intelligent automation to ensure unified eDiscovery, compliance and data privacy enforcement.

In a recent survey by KPMG, consumers reported feeling increasingly uneasy about the data collection practices of corporations. Data privacy is a huge issue for consumers and they understandably want to safeguard their personal information and be certain that an organization does not share or sell their private information without their consent.

Article 17 of the General Data Protection Regulation (GDPR) is known as the right to erasure, but it is commonly referred to as the right to be forgotten. According to Article 17, an individual can request that an organization delete all their personal information without undue delay - at no cost to the consumer.

As a result of the increasing concern over consumer data privacy and protection, multiple compliance regulations have been sanctioned against such practices. Businesses in countries around the world must comply with these mandates or risk heavy penalties - to the tune of tens of millions of dollars in collective enforcement fines.

The GhangorCloud Compliance and Privacy Enforcement (CAPETM) platform is the key to automate disparate tasks in real-time across data discovery, data classification, data mapping and consumer privacy compliance enforcement. This ensures a company's risk and exposure is minimized and that regulatory compliance mandates are enforced for GDPR, CCPA, HIPPA, PCI, PDPB, PDPL and other global data privacy laws.

Three Keys to Ensuring Automated Compliance and Consumer Privacy Enforcement

1. Automated Data eDiscovery

GhangorCloud's AI powered Data Discovery Engine was architected from the ground up to address the deficiencies and constraints of previous generation data discovery solutions.

  • Complex Data Object Definition: CAPE embodies unique AI based patented technologies that greatly facilitate the definition and discovery process for complex data/information objects that can represent any type of concrete and abstract data or information objects of interest. Virtually any kind of data/information such as structured, unstructured, semi-structured, ordered/unordered sets of data and data sequences can all be modelled and automatically identified and classified.
  • Auto Identification: Incorporates sophisticated patented technology for auto-identification of high granularity canonical as well as complex data objects that involve components with cross modality, cross type, composite structured and unstructured, embedded, or independent canonical data types.
  • Auto Classification: CAPE incorporates a unique Auto-Classification Engine that works with sophisticated data object ontologies to auto-classify sensitive information. The Auto-Classification engine examines every data/information object in the corpuses and using GhangorCloud's patented algorithms automatically classifies it into one of the classification types defined in the data object ontology. It can classify sensitive information as granular as specific words and phrases. The Auto-Classification Engine completely replaces the requirement for manual tagging or fingerprinting of sensitive information. It can readily work out-of- the-box and does not require any pre-processing of data or a laborious training / learning process.

2. Automated Data Mapping

CAPE incorporates a sophisticated Data Mapping Engine that automatically creates a persistent Universal Data Map (UDM) for the data/information objects that exist in the enterprise corpuses. This is a crucial capability that greatly facilitates efficient navigation through large storage systems and corpuses following the lineage of any given data/information object of interest. The UDM created by the Data Mapping Engine is used effectively by the CAPE's Privacy Enforcement Workflow Engine to automatically generate the Data Subject Request (DSR) and Data Subject Access Request (DSAR) service workflow.

3. Automated Data Service Request Handling

The Privacy Request Enforcement Engine utilizes its Universal Data Map (UDM) and Actor Repository Map (ARM) to correlate Actors (i.e., custodians of data repositories), specific set of repositories over which a given Actor has jurisdiction/authorization and the corresponding operations that they are authorized to perform on the specific data repositories. Using patented AI Algorithms, the engine can automatically discretize the incoming DSAR or DSR jobs into corresponding sets of 'primitive' (or atomic) tasks. The 'primitive' tasks are then automatically 'serialized' into a task sequence using the logical and precedence dependencies between these tasks. The Workflow Engine is equipped with a built-in mechanism to monitor and report the status of the DSAR or DSR fulfillment process, and raise alerts, alarms, or other notifications as appropriate during the fulfillment process.

"Consumers are exercising the right to be forgotten when their information is being used or sold without prior consent," said Tarique Mustafa, CEO/CTO, GhangorCloud. "To enforce compliance mandates and erase an individual's data is a complex and costly problem for an enterprise as petabytes of data may be housed across multiple data repositories both on-premises and across multi-cloud environments. Our CAPE deep AI platform gives organizations the assurance of a new-era of data compliance and privacy enforcement that automates complex tasks in real-time - while slashing the cost of enforcement of regulatory compliance and privacy mandates."


Tell Us What You Think

Do you have a review, update or anything you would like to add to this news story?

Leave your feedback
Your comment type
Azthena logo powered by Azthena AI

Your AI Assistant finding answers from trusted AZoM content

Azthena logo with the word Azthena

Your AI Powered Scientific Assistant

Hi, I'm Azthena, you can trust me to find commercial scientific answers from

A few things you need to know before we start. Please read and accept to continue.

  • Use of “Azthena” is subject to the terms and conditions of use as set out by OpenAI.
  • Content provided on any AZoNetwork sites are subject to the site Terms & Conditions and Privacy Policy.
  • Large Language Models can make mistakes. Consider checking important information.

Great. Ask your question.

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.