Trillium Insights

Thoughts and Insights from Trillium's Practice Leaders

How do I Secure my Cloud Services?

How do I Secure my Cloud Services?

With the growth of Cloud Services, including Software-as-a-Service (SaaS), Platform-as-a-Service (PaaS), and Infrastructure-as-a-Service (IaaS) solutions, your organization needs to be cognizant of what is involved with their use and what security in these environments means.  

SaaS is the Cloud-based service that consumes the entire operation – specific application(s) that are hosted by a third-party provider, available over the Internet.    PaaS provides the platform, allowing customers to develop, run, and manage applications without having to build and maintain the attendant infrastructure.  IaaS typically only provides infrastructure, including hardware, storage, and data center space to support the enterprise, with the customer directing the applications and operations.  

IDC estimates that in 2018 Cloud computing will be at least 50% of all IT spending, with additional growth to 60-70% by 2020.   However, with that growth additional security vulnerabilities will be uncovered, potentially exposing your organization.  Recently, a survey of security professionals indicated that one-third (1/3) of breaches affected more than one-half (1/2) of systems.  You simply cannot dismiss security concerns once you make the decision to go with a cloud-based solution. 

So, what is being done?  Cloud providers are beginning to be work directly with security solution providers to address customer concerns and implement end-to-end measures, such as Rackspace’s recent partnership with Cisco to deploy next-generation firewalls directly into its services.  Further, according to Cisco, in addition to traditional security tools, tools such as Machine Learning (ML) and Artificial Intelligence (AI) are maturing.  Tools like AWS Guardduty and AWS Macie are now being used within the enterprise.  It is imperative that as you develop relationships with Cloud providers, you understand their security roadmaps so you can make informed security decisions for your company. 

Also, there is a major security skills shortage and using an ‘automation first’ agile approach to security reduces the operational load on security, leverages automation learnings across multiple environments and provides economies of scale savings by utilizing scarce resources in a shared model.

Being acutely aware of your Cloud-based security risks, issues, and potential mitigation strategies will help your company to protect your data and electronic assets.

How do Artificial Intelligence (AI) and Machine Learning (ML) help in Cybersecurity?

How do Artificial Intelligence (AI) and Machine Learning (ML) help in Cybersecurity?

If you are running a business or an Information Technology operation, one of the biggest and most pervasive issues you deal with daily is cybersecurity.  In conjunction with security systems, Artificial Intelligence (AI) and Machine Learning (ML) are being used to protect against cyber-attacks.  A simple definition of AI in the cybersecurity context is the ability to program the identification and mitigation of attacks, alerting security staff to issues as needed.  This can help “free up” your employees for more fruitful and less repetitive security activities.  ML, a type of AI, in the cybersecurity context allows systems to identify anomalies. There are 2 types of ML – Supervised ML uses a pre-defined set of data examples to reach a conclusion, whereas Unsupervised ML finds patterns and relationships without examples from which to draw conclusions. 

It is projected that AI algorithms using ML will make it simpler to respond to cybersecurity risks, because these solutions will use ML data from prior cyber-attacks to adapt and identify similar risks, effectively “learning” behaviors in a standardized way.  Additionally, as attacks become more sophisticated, conventional cybersecurity protocols will be less and less effective. 

However, since security tools are only as good as the last successful attack, intrusions and intruders will continue to become more sophisticated.  To further complicate the issue, it is anticipated that AI and ML will also be used to conduct attacks, or “adversarial machine learning,” versus only being used as protection against attacks. 

Considering the current cybersecurity workforce shortage, estimated to grow to 3.5 million worldwide by 2021, your business will have to rely more on AI and ML solutions in conjunction with your own staff.

It is critical that your business stays vigilant in efforts to identify and mitigate cyber-attacks so your systems, data, and infrastructure remain as secure as possible.  Keeping your eyes open about both the benefits and issues surrounding AI and ML will allow you to view these emerging technologies in the cybersecurity space realistically.