Are Cloud Providers Responsible for All Aspects of Data Security?
What Is a Cloud Provider Cloud providers are third-party companies that offer a cloud-based platform, infrastructure, application, or storage services. Their responsibilities typically cover the following: Certifications and standards Technologies and service roadmap Data security, data governance, and business policies Service dependencies and partnerships Contracts, commercials, and SLAs (Service Level Agreements) Reliability and performance Migration support, vendor lock-in, and exit planning Business health and company profile Cloud Providers and castles have many similarities. They both host and have a standard protection system, like keys and locks, doors, a moat, etc. The responsibility falls on the users and the royal family that is using them. Like any attacker on a castle, talented hackers can get into the infrastructure at any time. The entire system is ruined if they don’t protect what’s inside. How Can the C² Data Privacy Platform Help? The C² Data Privacy Platform is your all-in-one solution for managing and securing data across enterprise cloud and hybrid environments. It handles data management, discovery, and security with ease. Key Features: C² Manage: Gain full visibility into all data regions within your AWS account, laying the foundation for comprehensive data discovery by answering the crucial question: “Where is my data stored?” C² Discover: Leverage cutting-edge data discovery techniques, including machine learning, AI, and contextual knowledge, to accurately analyze and identify sensitive data across various sources. C² Discover provides a unified view of data locations, highlights areas with high concentrations of sensitive information, and assigns the risk scores based on what types and how much sensitive data was found. C² Secure: Enhance your data security posture and mitigate the impact of breaches. With over 21 years of experience serving Fortune 500 clients, C² Secure offers expert recommendations on data encryption, masking, synthesis, and redaction to effectively protect sensitive data.
Can Cloud Data Be Controlled?
Looking at all the different ways to store data in the cloud, but want to know about data privacy and security? A data lake may be the answer. What Is a Data Lake? A data lake is a designated location where you can store, process, and secure substantial amounts of knowledge in all forms from structured, semi-structured, and unstructured. Enterprises like to use it to either: ingest or process data. Some great benefits include: Improve security and governance Lower total costs of ownership Simplify management Prepare to incorporate AI and machine learning Speed up analytics How Can C² Discover Help? The C² Data Privacy Platform is your all-in-one solution for managing and securing data across enterprise cloud and hybrid environments. It handles data management, discovery, and security with ease. Key Features: C² Manage: Gain full visibility into all data regions within your AWS account, laying the foundation for comprehensive data discovery by answering the crucial question: “Where is my data stored?” Turn on and off the unnecessary accounts to reduce AWS costs. C² Discover: Leverage cutting-edge data discovery techniques, including machine learning, AI, and contextual knowledge, to accurately analyze and identify sensitive data across various sources in various data types, structured, unstructured, and semi-structured. C² Discover provides a unified view of data locations, highlights areas with high concentrations of sensitive information, and assigns the risk scores based on what types and how much sensitive data was found. C² Secure: Enhance your data security posture and mitigate the impact of breaches. With over 21 years of experience serving Fortune 500 clients, C² Secure offers expert recommendations on data encryption, masking, synthesis, and redaction to protect sensitive data effectively.
Challenges of Machine Learning-Based Data Discovery
Machine learning is more accurate than regex. In fact, many data discovery tools claim to use machine learning when combing through data environments, looking for sensitive data. However, it may face several challenges. Data Bias and Fairness Machine learning models are sensitive to biases present in the training data. If the training data contains biased or unrepresentative samples, the model can learn and perpetuate the biases, leading to unfair or discriminatory outcomes. Ensuring fairness and mitigating bias in machine learning models is a critical challenge. Data Privacy and Security Machine learning models often require access to sensitive or private data. Protecting the privacy and security of such data. Protecting the privacy and security of such data during training and deployment is essential. Adversarial attacks, data breaches, or unintended information leakage can pose significant risks. Data Processing and Cleaning Preparing the data of machine learning often involves data preprocessing, including handling missing values, outliers, and inconsistent formatting. These tasks can be time-consuming and require domain knowledge and expertise. Interpretability and Explainability As models become more complex, their interpretability and explainability diminish. Understanding and interpreting the decision made by a model can be challenging, which can hinder trust and acceptance, particularly in critical domains such as healthcare or finance. Lack of Transparency The models can be viewed as black boxes, making it difficult to understand their internal workings. This lack of transparency can lead to skepticism and resistance, especially in scenarios where explainability is required, such as regulatory compliance or auditing. Data Quantity and Quality Machine learning models typically require large amounts of high-quality labeled data for effective training. However, obtaining labeled data can be very expensive, time-consuming, and in some cases, practically infeasible. Limited or low-quality data can adversely affect model performance and generalization. Model Robustness and Adversarial Attacks Machine learning models can be vulnerable to adversarial attacks, where malicious actors intentionally manipulate inputs to mislead or exploit the model. Ensuring robustness against such attacks is crucial, especially in safety-critical applications like autonomous vehicles or cybersecurity. Addressing these challenges requires a comprehensive and thoughtful approach, encompassing data collection and preprocessing practices, model selection and training, robust evaluation methodologies, and ethical considerations throughout the entire machine learning pipeline. How Is C² Data Privacy Platform’s Data Discovery Different C² Discover’s data discovery methods don’t rely on machine learning only. C² Discover leverages AI, contextual knowledge from our extensive experience protecting Fortune 500 companies, and machine learning to deliver accurate data discovery results. Our “data first, metadata second” approach ensures direct data analysis, using surrounding data to confirm and enhance our findings right out of the box. Understand what was found using the interactive, drill-down user interface. C² Discover displays the landscape of where the risk lies throughout the environment through the sensitive data landscape. Drill down to the source level to see what and where the highest concentrations of sensitive data are. The percentage breakdown is also displayed for users to view.
Cloud Security, Do You Need It?
The cloud is a remote location to store and share your files and data, and has some built-in cloud security: Back up of your data to the cloud No more external hard drives Remotely update and sync your files Share your files easily Remote work made easy Keep your files encrypted Cloud Security The cloud provider’s job isn’t just to house the data of companies, it’s to also ensure the cloud users how safe it is. When developing the cloud, they focused on: user and device authentication, data and resource access control, and data privacy protection. To achieve optimum security, they start with secure access control, zero-trust network, change management, web application firewall, data protection, and continuous monitoring. 6 Pillars of Cloud Security Secure Access Control: secure Identity Access Management (IAM) protocol; access to what they need and that’s all Zero-Trust Network Security Controls: separating the data from what needs to be protected and what doesn’t Change Management: management has control over governance and compliance when there is a request; can catch any suspicious activity Web Application Firewall: added protection to add a blockade to breachers à serves as an indicator of suspicious behavior Data Protection: strongly encourage encrypting files and have a plan of what to do if there is suspicious activity and breach Continuous Monitoring: comparing to older logs and auditing Let’s Get in the Mind of the Hackers The object of the game is you must get money or something that will lead to the money like credit card information, social security, someone’s identification, etc. Before, they relied on pickpocketing and scamming scenarios to get quick cash. With everything becoming digital, added tactics like phishing emails and malware to get your information. Two common events happen: they get access to the data and expose known data that isn’t fictionalized, or they expose data that you didn’t know residing in the cloud that wasn’t fictionalized. What You Can Do No matter what you do to your cloud security process, hackers are going to try to get their paycheck. Here are things we can do to add to the existing security protocol: Move sensitive data off the cloud Encrypt sensitive data Change your passwords Require 2-factor authentication/multifactor authentication Invest in firewalls on email servers Educate yourself and the company to make sure Know what information is on the cloud How Can C² Discover Help? The C² Data Privacy Platform is your all-in-one solution for managing and securing data across enterprise cloud and hybrid environments. It handles data management, discovery, and security with ease. Key Features: C² Manage: Gain full visibility into all data regions within your AWS account, laying the foundation for comprehensive data discovery by answering the crucial question: “Where is my data stored?” Turn on and off the unnecessary accounts to reduce AWS costs. C² Discover: Leverage cutting-edge data discovery techniques, including machine learning, AI, and contextual knowledge, to accurately analyze and identify sensitive data across various sources in various data types, structured, unstructured, and semi-structured. C² Discover provides a unified view of data locations, highlights areas with high concentrations of sensitive information, and assigns the risk scores based on what types and how much sensitive data was found. C² Secure: Protect your discovered data with expert recommendations on encryption, masking, synthesis, and redaction. With over 21 years of experience serving Fortune 500 clients, C² Secure ensures your sensitive data is effectively safeguarded.
The Problem with Regex-Based Discovery
Unlocking the Potential: Beyond the Limitations of Regex-based Discovery In today’s data-driven world, regex-based discovery has proven to be a valuable tool for pattern matching. However, it’s important to recognize the challenges that come with it, as patterns Unlocking the Potential: Beyond the Limitations of Regex-based Discovery In today’s data-driven world, regex-based discovery has proven to be a valuable tool for pattern matching. However, it’s important to recognize the challenges that come with it, as patterns…
C² Discover 3.0 released Sensitive Data Landscape
Today we are excited to announce some major advancements to the C² Discover product that provide users with a deeper understanding of their sensitive data across the enterprise. This includes a new Sensitive Data Landscape, Improved Data Risk Monitoring, Improved Discovery Performance, and Extended File Support. Sensitive Data Landscape This feature shows your data exposure risk across all your data sources. Based on our proprietary risk scoring algorithms the sensitive data landscape shows you what types of sensitive data are stored in your databases and files as well as the potential risk it represents. The goal is to provide insight into your enterprise’s risk so you can determine how best to protect your data. C² Discover calculates risk by analyzing the data discoveries you have run as well as how many other data sources you have but have not yet scanned. C² Discover tells you what types of sensitive data you have such as personal identifiable data, financial data, and healthcare or HIPAA data. Improved Data Risk Monitoring Get even closer and see how your risk is trending over time. C² Discover shows if your sensitive data increased, decreased or stayed the same on a monthly, quarterly, or annual basis. This tells you when and where to act to secure your data before it is too late. Improved Discovery Performance With C² Discover 3.0, the scanning process has been made smarter so you get your results faster. C² Discover already provided sophisticated sampling features to allow you to control how you search for your sensitive data. Some of our larger clients asked us to improve the speed of the Discoveries for large or complex databases as well as hundreds or even thousands of data sources. We listened and improved how C² Discover does parallel sampling. One more step to making C² Discover the best solution for large enterprises! Smarter File Support Large customers have legacy systems that use older file types. C² Discover now supports EDI files, both X12 and EDIFACT and can discover sensitive data in individual worksheets in Microsoft Excel (XLS, XLSX). C² Discover scans all your files and has built-in intelligence to identify common industry file types to improve the accuracy of the results. C² Discover is your enterprise-level cloud solution. C² Discover connects to your cloud-native data sources, whether it’s relational databases, NoSQL, S3, data lakes, or warehouses, and discovers sensitive data. Our approach to sensitive data discovery uses our deep learning technology, utilizing machine learning models and contextual knowledge based on our unmatched experience with data privacy experience. Visually understand your risk across your enterprise, what and where the sensitive data was found.
