What strategies can you use to protect your big data from cyber threats?

One effective strategy to protect big data from cyber threats is to implement robust access controls and encryption mechanisms. Limit access to sensitive data based on role-based permissions, ensuring that only authorized personnel can access and manipulate data. Encrypt data both at rest and in transit using strong encryption algorithms to safeguard it from unauthorized access and interception. Regularly audit and monitor access logs to detect any suspicious activity and promptly respond to potential threats.

Here's my perspective on access control, focusing on the less obvious pitfalls that can undermine your efforts: Know Your Data: Not all big data is equally sensitive. Categorizing by risk level lets you tailor access controls accordingly, avoiding unnecessary friction for users. "Least Privilege" is Your Mantra: Even trusted employees shouldn't have more access than they need. Regularly review and revoke unnecessary permissions. The "Who" Beyond IT: Do marketing folks need access to raw customer data? If not, ensure your access controls cover the whole org, not just the techies. Early in my career, I focused on keeping the bad guys out. Now I realize that even legitimate access can be abused, intentionally or not.

At Rest: Encrypt data stored in databases, data warehouses, and other storage systems to prevent unauthorized access. In Transit: Use secure communication protocols such as SSL/TLS to encrypt data being transmitted across networks. Key Management: Implement robust key management practices, including regular key rotation and secure key storage. Data Masking: Replace sensitive data with masked values to protect it while still allowing for testing or analysis. Anonymization: Remove personally identifiable information (PII) to prevent identification of individuals within datasets. Classify data based on its sensitivity and apply appropriate security controls. Implement data retention policies to manage the lifecycle of data.

Effective access control is important for ensuring the security of big data. By restricting data access to authorized personnel, you significantly reduce the risk of both internal and external breaches. Implementing robust authentication methods, such as multi-factor authentication (MFA), can greatly enhance your security measures by adding an extra layer of protection.

Wrap that crap up with network and security group segmentations too. Also get a good data object definition and define your sensitivity of data column where possibles - use that in conjunction with a good DLP program. Maintain and enforce a policy of least privileged access. Ensure every service and user has a unique and encrypted method of communication. Make sure that access is gated with SSO/MFA for human users. Trust no one!

Here's my perspective on the complexity of encryption in the big data realm: Don't Encrypt Everything: Big data is often used for analysis, which may require it in unencrypted form. Be selective: encrypt only what needs to be secret. Key Management is the Real Challenge: With large datasets, managing who has access to which keys, when, and how becomes its own security nightmare. Think Beyond the Algorithm: Even with strong AES-256, if the key is stored insecurely or transmitted over an unencrypted channel, your data is vulnerable. Early on, I felt like encryption was the be-all and end-all of data security. Now I realize it's one tool amongst many.

Use AES (Advanced Encryption Standard) to ensure data stored on servers remains inaccessible to unauthorized users, keeping sensitive information like personal details and financial records secure. Implement TLS (Transport Layer Security) to protect data as it moves across networks, preventing interceptors from accessing or altering the information during transmission. Stay ahead by frequently updating encryption protocols to combat new threats and ensure compliance with the latest security standards. People trust companies that protect their data → invest in robust encryption to build that trust.

Encryption is a key player in keeping your big data secure. By transforming sensitive information into a coded format that only the right decryption key can unlock, encryption keeps your data safe from unwanted eyes. It's essential to encrypt your data both when it's stored (at rest) and when it's being transmitted over networks (in transit). Think of AES (Advanced Encryption Standard) for stored data and TLS (Transport Layer Security) for data on the move—they're your best bet for robust protection. Don't forget to keep your encryption protocols updated and regularly audit them to stay ahead of potential threats. Embracing these encryption strategies means you can rest easy knowing your big data is well-protected and secure.

Here's my perspective on the importance of audits and how to maximize their value: Don't Just Check Boxes: Audits should be more than a compliance exercise. Use them to proactively test your security controls, not just see if they exist. Think Like an Adversary: The audit shouldn't just follow a checklist. Try to anticipate new attack vectors and design the audit to uncover them. The "Who" Matters: If the audit is always done by the same internal team, they may miss things. Periodically bring in external experts for a fresh perspective. I was felt like a good audit result was a guarantee of security. Now I realize it's a snapshot in time. The real value is in the continuous process of improving your defenses based on what you learn.

Updating systems can be one of the best ways of protecting an already secured system. There are a lot of security vulnerabilities out there that can be used to escalate privileges within a system. By keeping operating systems up to date then you can be sure that even some new vulnerabilities you haven’t heard of yet are being patched.

Regular security audits are a game-changer for keeping your big data safe. By routinely checking your software and hardware, you can ensure everything is up-to-date with the latest security patches. These audits help you catch unusual activity and potential weak spots before they turn into bigger problems. Plus, they keep you compliant with industry regulations, which means peace of mind. Regular audits can also reveal inefficiencies in your security practices, giving you a chance to make improvements. Getting your team involved in the process boosts awareness and understanding of security best practices across the board.

I personally use the 3-2-1 method. I find it gives me peace of mind. Three copies of your data so if one fails you still have 2 more. Two backup copies, redundancy. One offsite, this is important because of disasters that we cannot control.

Maintaining reliable backup solutions is essential for big data protection. During a cyber incident like a ransomware attack, having current backups can mean the difference between a quick recovery and a devastating data loss. The 3-2-1 backup rule is a great guideline: keep three copies of your data, store two on different media, and ensure one is offsite. Regular testing of these backups is crucial to confirm they work when needed. Additionally, consider using cloud backups as part of your strategy. This not only adds flexibility and scalability but also provides an extra layer of security, enhancing your overall data protection plan.

El 90% de las brechas de seguridad comienzan con un email de Phishing. Es algo que todos sabemos pero que no todos estamos atendiendo. Como CISO somos responsables de la seguridad de nuestros usuarios. Debemos contar con un programa de awareness sostenido en el tiempo y alineado con la cultura de la empresa. El usuario tiene que ser nuestra primera línea de defensa y para eso debemos involucrarlo y hacerlo parte de nuestra estrategia de seguridad.

Pareto analysis says that 80 percent of all problems can be solved with only 20 percent of the necessary effort. Combine this with the information that 70 to 90 percent of all security breaches start with phishing. Make sure that employees can differ between a malicious email and alink with a legit one.

Educating your employees about cybersecurity best practices is invaluable. Human error is a common factor in data breaches, so fostering a security-conscious culture is crucial. Regular training sessions can teach employees to identify phishing attempts, create secure passwords, and handle data responsibly. Empowering your staff with this knowledge not only bolsters your defenses but also encourages a proactive approach to cybersecurity. Additionally, consider implementing simulated phishing exercises to test and reinforce what your team has learned.

Your employees do not have to all be cyber security professionals to identify a phishing attack. By implementing the proper training they will be able to identify and report emails that my not have their best interest or the companies best interest at heart.

Here's my perspective on incident response, drawing on decades of experience in dealing with breaches: The Plan is Just the Beginning: Incidents are chaotic, and your plan won't cover every scenario. Train your team to be flexible and think on their feet. Communication is Key: Who needs to be notified? What information should be shared, and when? This can make or break your response. Learn from Mistakes: After every incident, analyze what went wrong (and what went right!). Update your plan accordingly, and train your team on those lessons. Early in my career, I felt like incident response was about having all the right tools. Now I realize it's more about having the right people and processes in place.

Craft a detailed incident response strategy that outlines exact actions for detecting, containing, and resolving security breaches. Set clear guidelines for internal and external communications during an incident to maintain transparency and control information flow. Perform routine drills to test and refine the incident response plan, ensuring your team is prepared to act swiftly and efficiently. After an incident, evaluate the response process and make necessary adjustments to improve future responses and recovery measures.

Encyrption is vital but don't miss out data masking. Your big data may include private or personally identifiable data such as health records or credit card number. Data masking inhibits this sort of data to be seen by others.

Se tratando de grandes volumes de dados, com uma possível infraestrutura robusta, uma das coisas que se torna essencial e crucial é o monitoramento dos ambientes para identificar anomalias de tráfego, consumo de memória e coisas do tipo. Além de ter politicas muito claras sobre como agir e o que deve acontecer ao notar a existência de um comportamento estranho. Isso envolve planos de contingência, bloquear algum ip por exemplo, desligar uma máquina, mudar um serviço ou ambiente e ações nessa linha.