Friday, August 16, 2024

Q&A: AI and the complication of the security landscape

By Dr. Tim Sandle
DIGITAL JOURNAL
August 15, 2024

Image: © PRENSA SENADO/AFP Handout

Cybersecurity remains an ever-present and pressing need for all types of enterprises. How challenging is the current situation and what is the contribution of the advent of artificial intelligence (AI) to this complexity?

To learn more about the current issues and ways to resolve them, Digital Journal caught up with Akmal Chaudhri, Technical Evangelist at SingleStore.

Digital Journal: Why have so many companies turned to the cloud for data management?

Akmal Chaudhri: Many companies have turned to the cloud for data management because it offers cost savings with its scalability and pay-per-use models, making it a flexible, economical option. The cloud’s faster deployment and global access also make it an attractive option. With cloud providers offering enhanced security, reliability, and disaster recovery capabilities, companies’ traditional data management concerns are being alleviated.

Additionally, the ability to use advanced analytics, machine learning, and data integration within cloud platforms enables businesses to gain valuable insights and make data-driven decisions. So, by allowing cloud providers to manage the IT infrastructure and offloading internal IT management, companies can spend more time focusing on core competencies and drive innovation. In other words, leave the management of storage and plumbing details to the experts.

DJ: What are the main security challenges that companies face when managing their data?

Chaudhri: From safeguarding data against cyber threats such as ransomware and phishing attacks, to ensuring data privacy and staying compliant with industry or legal regulations – it’s safe to say that today’s companies face many security challenges when it comes to managing their data. Given the increasing volume and complexity of data, coupled with remote work environments, this creates added vulnerabilities. Which makes managing access permissions, preventing insider threats, and protecting data across different platforms a significant challenge for organizations.

DJ: How can these challenges be overcome?

Chaudhri: Overcoming data security challenges requires a multi-pronged approach including robust encryption, firewalls, and intrusion detection systems. Regular security audits, employee training to mitigate human error, adherence to data privacy regulations, and strict access controls are also essential. Additionally, by having data loss prevention measures and disaster recovery plans in place, businesses are set up for continuity, enabling them to quickly restore operation and minimize downtime. All of this to say, a proactive and layered security strategy is a necessity for businesses to safeguard sensitive information.

DJ: Does AI complicate the situation further?

Chaudhri: Yes, AI significantly complicates the data security landscape. While offering potential solutions like advanced threat detection and automated response, AI also introduces new risks. For example, malicious actors could exploit AI to launch more sophisticated attacks, such as deepfakes and adversarial machine learning – we have seen examples of this already. Ensuring that AI systems are reliable and unbiased is important to prevent data breaches caused by faulty algorithms. Additionally, the ethical implications of AI in data management, including issues of privacy and accountability, also require careful consideration.

DJ: With SaaS, what challenges does this present in terms of data consolidation?

Chaudhri: Today, the proliferation of SaaS platforms results in data being scattered across various cloud environments, making it difficult to integrate and analyze. Data inconsistencies, varying data formats, and API limitations prevent the creation of a unified data view, a critical component when gathering actionable and accurate business insights. Data ownership and governance issues also arise, as organizations grapple with controlling data spread across multiple SaaS providers. All together, these factors complicate data consolidation efforts and hinder deriving actionable insights.

DJ: You’re an advocate of ‘Bring Your Own Cloud’ (BYOC). What does this entail?

Chaudhri: Bring Your Own Cloud (BYOC) enables organizations to use their existing cloud infrastructure for running specific applications or services provided by a vendor. Instead of relying solely on a vendor’s cloud environment, BYOC allows businesses to maintain control over their data, security, and costs while benefiting from the vendor’s expertise in application development and management. This approach offers flexibility, customization, and potential cost savings, as there is no one-size-fits all cloud approach.

DJ: Where should enterprises interested in BYOC turn to for guidance?

Chaudhri: Enterprises exploring BYOC should seek guidance from multiple sources. For example, cloud service providers with BYOC offerings can provide technical expertise and support, while IT consulting firms specializing in cloud migration and management can offer strategic advice and implementation assistance. Industry associations and research organizations are also a valuable resource, as they can share best practices and insights. Additionally, networking and benchmarking with other organizations that have successfully implemented BYOC can provide valuable lessons learned and practical guidance.

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