By 2020 it is predicted that over 40 billion more devices will become “smart” via embedded processors and intelligence affecting every industrial and financial sector and medical care. Different Internet of Things IoT systems are designed and implemented according to the domain requirements, typically not taking into consideration issues of openness, scalability, interoperability, and use case independence. This leads to a variety of new potential risks concerning information security and privacy, data protection and especially safety, all of which need to be considered in unison.

Large scale connectivity of intelligent objects coupled with complex constraints inevitably leads to many security challenges, which are not included into the classical formulation of security problems and solutions. Consequently, securing data, objects, networks, infrastructure, systems and people in complex transport, energy, production and financial systems require new analysis methods cognitive platforms enabling intelligent shielding and supervision of privacy, cyber-security and safety threats.


Protection& Privacy

Protecting data and associated privacy is of utmost importance to Inlecom’s public and private sector clients. With most organizations now making efforts to protect sensitive data in production environments, data privacy and protection have assumed great significance owed to strict rules and regulations governing the management, exchange and storing of data. Moreover, with data breach incidents in headlines nearly every week, protecting data and ensuring privacy has become a vital requirement to every business.

Inlecom have addressed, and implemented, responsible practices, processes and procedures for both data privacy and data protection across numerous client projects, in turn building key skills in privacy and data protection. Where needed in projects, sophisticated data privacy approaches are used to ‘de-identify’ and mask PII, using open source and/or proprietary tools, in turn protecting sensitive data.


Data modellingtechniques

Inlecom use data modelling techniques to both discover and describe sensitive data across databases, such as personally-identifiable information, trade secrets and other sensitive data.

Masking and obfuscation is based on rules that guide the necessary transformations, in turn detecting and locating hidden instances of confidential data so that they can be fully protected and compliant with privacy regulations and corporate governance standards.


Best practices

For production and regulated applications Inlecom have developed expertise in building solutions to be in alignment with leading industry regulations, operating standards, and recognized best-practices.

SOC 1, SOC 2, SOC 3
ISO 27001
PCI DSS Level 1
EU Directive 95/46/EC & GDPR (EU 2016/679)

Case studies