Data privacy is one of the leading concerns for businesses to ensure confidentiality and preserve trust. Over the last few decades, the digital footprints of our society have shown exceptional growth. But, this digital revolution is striking hard over privacy concerns of individuals. According to Pew Research, 81% of Americans report the potential risk of data collected by companies overshadowing the benefits they receive from those businesses. Data privacy is not a matter only crucial to big companies.

A quick web search for "chatbots and security" brings up results warning you about the security risks of using these virtual agents. Dig a little deeper, however, and you'll find that this artificial intelligence (AI) technology could actually help address many work-from-home cybersecurity challenges -- such as secure end-to-end encryption and user authentication -- and ensure that your organization continues to prove its data privacy compliance with less direct oversight. While many companies rely on chatbots to answer customer questions or step through a process, that same service can be used to help employees connect with security professionals as they work remotely, allowing many security problems to be resolved as efficiently as they would be if the security team were able to come directly to their colleagues' desks. Between 2005 and 2018, the number of remote workers grew by 173 percent, 11 percent faster than the rest of the workforce, according to Global Workplace Analytics. And as more employees and management experience the benefits of working from home, more people will demand the opportunity.

Some of the top legal ontologies developed so far include the Functional Ontology for Law [FOLaw] The increasing need for legal information and content (Valente 1995), the Frame-Based Ontology (van Kralingen management caused by the growing amount of 1995), the LRI-Core ontology (Breuker 2004), unstructured (or poorly structured) legal data managed by DOLCE CLO [Core Legal Ontology] (Gangemi et al. legal publishing companies, law firms and public 2003), or the Ontology of Fundamental Concepts (Rubino administrations, or the increasing amount of legal et al. 2006, Sartor 2006) the basis for the LKIF-Core information directly available on the World Wide Web, Ontology (Breuker et al. 2007). Nevertheless, most legal have created an urgent need to construct conceptual ontologies are domain specific ontologies, which represent structures for knowledge representation to share and particular legal domains towards search, indexing and manage intelligently all this information, whilst making reasoning in a specific domain of national or European law human-machine communication and understanding (e.g. the IPRONTO ontology by Delgado et al. 2003, the possible.