As cyber threats continue to evolve at a breakneck pace, legacy security tools and strategies are no longer sufficient. Recent statistics paint a grim picture:
- Data breaches grew 17% year-over-year in 2021, with healthcare breaches nearly doubling (IBM Report)
- 78% of organizations report having trouble hiring cybersecurity talent (ISC2 Study)
- Small businesses saw a 13X year-over-year increase in ransomware attacks (Coye Report)
Modern cyber threats are personalized, targeted, and highly impactful. Legacy security measures fail to provide adequate visibility or protection across today’s complex IT ecosystems spanning cloud, networks, IoT devices and remote users.
As shown in the chart below, data breach costs have risen dramatically over the past 8 years:
Data source: IBM Cost of a Data Breach Reports 2016-2022
Simply put, practitioners must modernize their data security stacks by leveraging advanced analytics and automation. This guide provides prescriptive guidance on updates required in 5 key areas:
1. Know Your Data
Comprehensively cataloging data across…
2. Restrict Access with Precision
While most organizations focus access controls at the network and application layers, insider risks call for more granular identity and access management tied directly to data types and context…
3. Embrace Privacy-Enhancing Technologies
Advancements in cryptography, secure computing and synthetic data present new opportunities to de-risk data usage without impeding business objectives.
Homomorphic encryption allows complex computations on encrypted data, keeping it secure even during use. Platforms like Zama are making this technology more accessible to enterprises. Leaders in analytics and cloud services are racing to offer homomorphic encryption on their platforms as well.
Federated learning enables collaborative machine learning model training without exposing any raw data. Instead of shipping data to a central server, Google pioneered an approach where only model parameters are shared from each participating device.
Consider supply chain AI applications predicting delivery delays. Each partner can improve forecasts by pooling insights from cross-company data. Federated learning preserves confidential data while allowing everyone to benefit from the aggregate model performance improvements…
4. Quantify and Manage Risk Holistically
Given increasing threats and limited resources, organizations must quantitatively assess risks and allocate budgets proportionally.
FAIR provides an open standard and methodology for measuring cyber risks in financial terms. By considering complex variables like threat actors, vulnerabilities and control failures, FAIR models derive an annualized loss expectancy (ALE) for various data breach scenarios.
ALE becomes the impartial metric that executives can use to guide decisions on security investments. If migrating HIPAA data to the cloud carries a worst-case $5 million ALE, then spending over that amount on compensating controls would be justified economically while also improving risk profile…
5. Train Employees as a Critical Defense Layer
With social engineering causing 22% of breaches (Verizon 2022 DBIR), the human element remains a key battleground. Sadly, careless and untrained employees represent low-hanging fruit for attackers to target.
Annual on-site and remote security awareness training is essential. Beyond phishing simulations and online modules, creative formats like escape rooms and games can also vividly demonstrate vulnerabilities for learning retention.
Expert Forecasts Signal More Disruption Ahead
Industry leaders point to game-changing technologies on the horizon that could fundamentally transform data security paradigms…