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Articles by Tag: Data Security

Understanding DSPM: A Data-First Security Shift
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Understanding DSPM: A Data-First Security Shift

Businesses now manage massive, scattered data across cloud environments, devices, and applications, creating blind spots and increased data leak risks. A data-first security approach, like data security posture management (DSPM), is becoming more critical. DSPM solutions can allow CISOs and IT leaders to effectively protect sensitive data across complex cloud environments.
Rethinking Red Teaming for SME AI Models
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Rethinking Red Teaming for SME AI Models

SMEs have been adopting AI quickly, but AI models bring unique risks like hallucinations, bias, prompt injections, and data leakage. Built-in vendor safeguards are no longer sufficient. Cost-effective AI red teaming solutions allow SMEs to discover hidden threats in AI models. CISOs and security leaders can turn to these solutions to ensure that models are resilient to adversarial attacks, strengthen regulatory compliance, build stakeholder trust, and improve model reliability.
Learning from Shadow AI: Delivering the AI Tools Your Employees Actually Need
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Learning from Shadow AI: Delivering the AI Tools Your Employees Actually Need

As AI adoption surges, shadow AI was bound to follow, just like shadow IT before it. This can lead to data leaks and compliance violations, prompting urgent alarms when detected. However, it is also important to understand why shadow AI occurs. By uncovering its root causes, CISOs and IT leaders can close gaps and deploy the AI tools that employees truly need.
Shadow AI: Turning Hidden Risks into Secure Innovation
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Shadow AI: Turning Hidden Risks into Secure Innovation

Shadow AI, the unsanctioned use of generative AI in enterprises, offers productivity benefits but introduces serious risks, from data leaks to regulatory breaches. SMEs can respond by strengthening governance, enabling secure experimentation, and integrating sanctioned AI pathways to balance innovation with compliance. CISOs and IT leaders must address shadow AI risks while enabling safe, innovative adoption.
Offline Intelligence: How SMEs Can Harness AI Without the Cloud
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Offline Intelligence: How SMEs Can Harness AI Without the Cloud

Deploying AI in the cloud is convenient and streamlines operations. However, this approach may not be suitable for SMEs facing compliance, privacy, and budget constraints. AI deployments in an air-gapped environment may be suitable to decrease the risk of data leaks and unpredictable cloud costs. CIOs can help their SMEs to maintain full control over data, cost, and regulatory alignment without cloud exposure by using air-gapped environments.
Unraveling the Local Loop: A Guide to Safer Locally Deployed AI
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Unraveling the Local Loop: A Guide to Safer Locally Deployed AI

Organizations are increasingly adopting large language models (LLMs) to enhance operations and decision-making. While deploying these models locally offers significant advantages in terms of data sovereignty and control, it also presents unique security challenges that cannot be overlooked. IT executives who have, or are planning, a local LLM deployment should make sure it is implemented securely, ethically, and effectively to avoid data breaches and operational risks.