If you have ever used a library card catalog system to gather information, you appreciate how databases, the internet, and automation efficiently aggregate and locate data. Now with massive organizational data growth, intelligent automation has become critical due to staffing shortages and the need to scale operations to both protect data and harvest accurate insights. A 24-agency coalition issued the first-ever State of the Federal Cyber Workforce Report as a “call to action on the systemic changes necessary” to close the U.S. government’s cyber talent shortage.
A new report from Foundry covered in the article “Cybersecurity Leaders Are Having a Hard Time Keeping Companies Secure, and There’s No Easy Solution” finds that staff shortages, budget problems, and the growing sophistication of cyberattacks are causing major challenges for security leaders.
Security professionals surveyed by Foundry “agreed that automation is a key tool for improving incident responses and maintaining skilled security staff … 45% use automation technology … and 32% are researching Zero Trust technologies.”
Another article, “5 Reasons Why Security Operations Are Getting Harder,” addresses that “research illustrates the fact that we don’t have the people, processes, or technologies to keep up with these scaling needs. Scaling people means more intelligent technology, better training, and structured repeatable processes.”
The reality is that human talents are best used for strategic and creative tasks focused on data insights, which simultaneously increases job satisfaction, whereas repetitive, monotonous data processing tasks are more efficiently managed using intelligent automation with human oversight. Frequently, problems stem from a data-governance level with technology and data overload that can lead to accidental insider data leaks.
A new Microsoft Insider Risk Report discusses how insider risk is frequently inadvertent with an average of 12 events per year versus eight malicious events. The inadvertent events were often from “employees taking unsafe actions, being untrained or distracted, misusing resources, or causing accidental data leakage.”
However, the report stresses that “the best risk management programs aren’t focused on constraining employee behavior. They’re focused on building trust, balancing security and privacy, and educating and empowering their workforce.”
Collaborative leadership is really the main success driver. The article, “Addressing the Complexities of Cybersecurity at Fintech Enterprises” stresses that “the effectiveness of cybersecurity is also greatly conditioned by organizational culture and the leadership skills of senior management.” The author outlines the importance of identifying your assets first as part of risk assessments, and how the NIST Cybersecurity Framework (CSF) “begins with the identification/inventory of the organization’s assets. If this is not done correctly, it will be impossible to protect the assets.”
Leaders must go beyond the boardroom to take a holistic look at the organization’s data assets, their people and technology assets, and the internal and external risks to those assets to properly prioritize and set achievable goals.
After the recent major breach of CommonSpirit Health, Becker’s Health IT asked CISOs about their cyber strategy. Comments included “asset management is foundational – you can’t protect it if you don’t know about it” and “my entire security and privacy programs need to be able to safeguard patient data and defend against cyberattack, which can be very costly.”
Breaches not only result in financial and reputational loss, but healthcare organizations are also reporting that cyberattacks are causing cancellations of procedures, increases in mortality rates, and operational shutdowns. Boards and the C-suite must make cybersecurity and data privacy a top priority to keep up with the pace of attackers.
Listening to staff, communicating, breaking down silos, and conducting asset inventories and risk assessments are all key to cybersecurity improvements. See our recent articles on tackling these challenges:
- Building a cybersecurity foundation with critical thinking, storytelling, and asset inventory
- Cybersecurity awareness benefits from data discovery automation
- Three ways to reduce cybersecurity risk: bias education, collaboration, and intelligent automation
- The root causes of cybersecurity risk and how automation can help
- Cyber resilience requires managing human risks and leveraging innovation and automation
Human-centric cybersecurity and data governance must work together to authentically address people and technology risks to data-based decision-making. Data is hailed as a key competitive advantage, however decisions based on data are only good as the quality of the data. If data is stolen or damaged – accidentally or intentionally – not only can insights be flawed, but an organization’s reputation can be damaged.
The article, “Cloud Data Breaches Are Running Rampant. What Are the Common Characteristics?,” discusses how “data continues to drive enterprise business needs and processes, spurring the need for a rapidly growing number of data stores in which to house it all.” However, at the same time, “data’s inherent value and impact on business operations have made it a prime target for cybercriminals.”
Data leakage through compliance boundaries, publicly exposed buckets, database misconfigurations, and missing encryption demonstrate the many types of human mistakes that lead to data breaches at all sizes and types of organizations.
According to the author, organizations must “take ownership of your data and identify sensitive and ‘need to be protected’ assets with periodic scans of your environment to discover any unknowns and surprises.” Other key activities are improving your data security posture, controlling data with how it moves about your organization, and also monitoring activities against sensitive data.
The reality is most organizations do not have a good accounting of their growing and changing data assets with indexing and comprehensive metadata analysis. Intelligent automation is necessary to manage exponential data growth that is often overexposed, especially with limited staff resources.
Many solutions only examine portions of the data estate, don’t encompass unstructured and structured data, or only look at metadata without being able to see file content risks or valuable data. As a result, there may be a false sense of security with unidentified data risks, as well as risks to data quality and lineage.
In the case of healthcare, there could be mistakes like PHI misfiled or other data privacy risks. Often with employee turnover there are legacy file risks as the IT department may not have a clear idea of what to keep and what to delete. Intellectual property is often at risk of being duplicated or overshared without proper encryption. And analytics solutions may not be incorporating all the valuable or necessary data that is available.
Comprehensive data discovery and intelligent document processing solutions include both unstructured and structured data, and automate multiple data identification, inventory, and processing functions for cybersecurity risk assessment, digital transformation, cloud migrations, and analytics projects.
Anacomp offers several solutions to help reduce data breach risk, as well as staff and storage costs:
- AI/ML Data Discovery and Distillation (D3) provides a single pane view of both structured and unstructured data stores for over 950 file types with visualization of all file properties and customizable metadata. Risk filters, workflows, data tagging, and federated search help to clean data up and then keep it that way with ongoing, automated monitoring.
- AI/ML and NLP Intelligent Document Processing and Scanning uses artificial intelligence (AL), machine learning (ML), and natural language processing (NLP) to read and process many types of data including handwriting and poor-quality documents, as well as images, enabling you to incorporate more data into your projects and analytics.
Anacomp has served the U.S. government, military, and Fortune 500 companies with data visibility, digital transformation, and OCR intelligent document processing projects for over 50 years.