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In today’s digital landscape, enterprises are grappling with the daunting challenge of safeguarding their data against a myriad of threats. The repercussions of a data breach are staggering, both in terms of time and money. On average, it takes companies a staggering 277 days and a substantial $2.4 million to detect and recover from a single breach. With the proliferation of enterprise data, understanding who has access to this critical information and where it resides has become paramount. The risk of data leakage intensifies as employees increasingly share sensitive information like product roadmaps, internal documents, or passwords through various platforms and devices.

Moreover, the legal landscape is evolving rapidly. By the end of this year, an estimated 75 per cent of the world’s population will be covered under privacy regulations, mandating stringent data protection measures. Consequently, business and security leaders must grasp and implement the data security life cycle — a comprehensive framework outlining the steps necessary to safeguard data from creation to disposal.

Access to data

At the core of this framework lies the process of Data Discovery, which involves locating all corporate data dispersed across diverse platforms. Understanding who has access to this data and ensuring minimal and necessary access through the principle of least privilege is essential. This step is not just about organisational efficiency; it is critical for compliance with regulations such as GDPR, HIPAA, and PCI. Data Classification, an integral part of the life cycle, complements Data Discovery.

It involves identifying and categorising the types of data collected, differentiating between critical regulated data and redundant or obsolete data. Advances in artificial intelligence have streamlined this process, enhancing accuracy and efficiency.

Data Monitoring is a crucial step in this life cycle, where constant vigilance is maintained to evaluate risk. Real-time monitoring allows swift identification of suspicious activities, enabling proactive responses to potential threats. Continuous scanning detects abnormal data interactions, providing valuable insights for compliance and risk management. This monitoring, when coupled with automation, streamlines incident response, ensuring rapid containment of breaches and minimal data loss.

Ultimately, the goal of the data security life cycle is Data Protection. By focusing on securing data from the outset, organisations can control every interaction effectively. Automated incident response and proactive enforcement are facilitated through insights gained from the discovery, classification, and monitoring stages. Automated data protection measures minimise the impact of data risks, preventing unauthorised data downloads or exchanges on any device.

In the face of the current economic climate, organisational leaders must recognise the paramount importance of the data security life cycle. Investment in cutting-edge technology, including discovery, classification, monitoring, and protection software, is imperative. These tools offer data forensics, uniform policy management, and adaptive automation, crucial in mitigating evolving risks.

However, technical solutions alone are not sufficient. CEOs and CISOs must foster a culture where data security is a top priority. Regular employee training, encouraging the reporting of suspicious activities, and continuous review and update of security policies are essential. Achieving explicit permissions for every interaction, be it logging in, sharing data, using applications, or browsing websites, is vital. Embracing a holistic approach to data security, grounded in the principles of the data security life cycle, is key to achieving zero trust.

As cybercriminals exploit information assets and global data privacy regulations become stringent, a comprehensive and proactive data security strategy is indispensable.

— The writer, Samer Diya is Vice President, Sales Emerging Markets, Forcepoint