- How to Build Data Frameworks with Open Source Tools to Enhance Agility and Security - Oct 27, 2021.
Let’s take a look at how to harness open source tools to build your data frameworks.
Data Democratization, Deployment, Open Source, Security
- Artificial Intelligence vs Machine Learning in Cybersecurity - Aug 5, 2021.
Artificial Intelligence and Machine Learning are the next-gen technology used in various fields. With the rise in online threats, it has become essential to include these technologies in cybersecurity. In this post, we will know what roles do AI and ML play in cybersecurity.
AI, Cybersecurity, Machine Learning, Security
- 7 Data Security Best Practices for 2021 - Jun 15, 2021.
Here are seven data security best practices to adopt this year.
Cybersecurity, Data Science, Security
- What is Adversarial Neural Cryptography? - Apr 22, 2021.
The novel approach combines GANs and cryptography in a single, powerful security method.
Adversarial, AI, Cryptography, GANs, Security
- Deploying Secure and Scalable Streamlit Apps on AWS with Docker Swarm, Traefik and Keycloak - Oct 23, 2020.
If you are a data scientist who just wants to get the work done but doesn’t necessarily want to go down the DevOps rabbit hole, this tutorial offers a relatively straightforward deployment solution leveraging Docker Swarm and Traefik, with an option of adding user authentication with Keycloak.
AWS, Deployment, Docker, Scalability, Security, Streamlit
- 10 Steps for Tackling Data Privacy and Security Laws in 2020 - Jul 22, 2020.
Data privacy laws, such as the CCPA, GDPR, and HIPAA, are here to stay and significantly impact everyone in the digital era. These steps will guide organizations to prepare for compliance and ensure they support the fundamental privacy rights of their customers and users.
Advice, Big Data, CCPA, GDPR, Privacy, Security
- Federated Learning: An Introduction - Apr 15, 2020.
Improving machine learning models and making them more secure by training on decentralized data.
Federated Learning, Learning, Machine Learning, Privacy, Security
- Phishytics – Machine Learning for Detecting Phishing Websites - Mar 6, 2020.
Since phishing is such a widespread problem in the cybersecurity domain, let us take a look at the application of machine learning for phishing website detection.
Cybersecurity, Machine Learning, Security
- Trends in Machine Learning in 2020 - Mar 5, 2020.
Many industries realize the potential of Machine Learning and are incorporating it as a core technology. Progress and new applications of these tools are moving quickly in the field, and we discuss expected upcoming trends in Machine Learning for 2020.
Machine Learning, Security, Trends
- Deepfakes Security Risks - Jan 10, 2020.
Deepfakes have instilled panic in experts since they first emerged in 2017. Microsoft and Facebook have recently announced a contest to identify deepfakes more efficiently.
AI, Deepfakes, Security
The 4 Hottest Trends in Data Science for 2020 - Dec 9, 2019.
The field of Data Science is growing with new capabilities and reach into every industry. With digital transformations occurring in organizations around the world, 2019 included trends of more companies leveraging more data to make better decisions. Check out these next trends in Data Science expected to take off in 2020.
2020 Predictions, Automated Data Science, AutoML, Cloud Computing, Data Science, NLP, Privacy, Security, Trends
- Top 7 Data Science Use Cases in Trust and Security - Dec 2, 2019.
What are trust and safety? What is the role of trust and security in the modern world? Read this overview of 7 data science application use cases in the realm of trust and security.
AI, Data Science, Security, Trust, Use Cases
- Applying Data Science to Cybersecurity Network Attacks & Events - Sep 19, 2019.
Check out this detailed tutorial on applying data science to the cybersecurity domain, written by an individual with backgrounds in both fields.
Cybersecurity, Data Science, Machine Learning, Python, Security
- PySyft and the Emergence of Private Deep Learning - Jun 27, 2019.
PySyft is an open-source framework that enables secured, private computations in deep learning, by combining federated learning and differential privacy in a single programming model integrated into different deep learning frameworks such as PyTorch, Keras or TensorFlow.
Deep Learning, Differential Privacy, Privacy, Python, Security
- Why Machine Learning is vulnerable to adversarial attacks and how to fix it - Jun 13, 2019.
Machine learning can process data imperceptible to humans to produce expected results. These inconceivable patterns are inherent in the data but may make models vulnerable to adversarial attacks. How can developers harness these features to not lose control of AI?
Adversarial, Machine Learning, Safety, Security
- 3 Big Problems with Big Data and How to Solve Them - Apr 18, 2019.
We discuss some of the negatives of using big data, including false equivalences and bias, vulnerability to security breaches, protecting against unauthorized access and the lack of international standards for data privacy regulations.
Advice, Bias, Big Data, Privacy, Security
Top 10 Technology Trends of 2019 - Feb 7, 2019.
This article outlines 10 top trending technologies for 2019, a list which covers diverse topics such as security, IoT, reinforcement learning, energy sustainability, smart cities, and much more.
2019 Predictions, Automation, Cloud, Energy, IoT, Reinforcement Learning, Security, Trends
- Machine Learning Security - Jan 25, 2019.
We take a look at how malicious actors can break machine learning models and what some of the best practices are when it comes to stopping them.
Adversarial, Alexa, Machine Learning, Security
- Top 5 domains Big Data analytics helps to transform - Nov 23, 2018.
Big data analytics gives a competitive advantage to companies across many industries, especially, financial services, e-commerce, aviation, transportation, logistics, and energy. It enables to reduce downtime, mitigate risks, cut costs, and improve performance.
Aviation, Big Data, Big Data Analytics, Credit Risk, Data Analytics, Ecommerce, Finance, Security
- Building Surveillance System Using USB Camera and Wireless-Connected Raspberry Pi - Nov 6, 2018.
Read this post to learn how to build a surveillance system using a USB camera plugged into Raspberry Pi (RPi) which is connected a PC using its wireless interface.
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Computer Vision, Python, Raspberry Pi, Security, Video recognition
- Deep Learning on the Edge - Sep 19, 2018.
Detailed analysis into utilizing deep learning on the edge, covering both advantages and disadvantages and comparing this against more traditional cloud computing methods.
Cloud Computing, Deep Learning, IoT, Security
- Machine Learning-driven Firewall - Feb 23, 2017.
Cyber Security is always a hot topic in IT industry and machine learning is making security systems more stronger. Here, a particular use case of machine learning in cyber security is explained in detail.
Firewall, Fsecurify, GitHub, Machine Learning, Security
Machine Learning and Cyber Security Resources - Jan 2, 2017.
An overview of useful resources about applications of machine learning and data mining in cyber security, including important websites, papers, books, tutorials, courses, and more.
Cybersecurity, Machine Learning, Security
- Privacy, Security and Ethics in Process Mining - Dec 21, 2016.
Data Privacy, Security and Ethics are hot yet complex topics in the business and data science world. This important article talks about and provide guidelines for privacy, security and ethics, specifically in the context of Process Mining.
Pages: 1 2
Anonymity, Ethics, Privacy, Process Mining, Security
- Using Machine Learning to Detect Malicious URLs - Oct 28, 2016.
This is a write-up of an experiment employing a machine learning model to identify malicious URLs. The author provides a link to the code for you to try yourself.
Cybersecurity, Python, Security
- 5 Best Practices for Big Data Security - Jun 9, 2016.
Lack of data security can not only result in financial losses, but may also damage the reputation of organizations. Take a look at some of the most important data security best practices that can reduce the risks associated with analyzing a massive amount of data.
Best Practices, Big Data, Security
- Big Data and Data Science for Security and Fraud Detection - Dec 11, 2015.
We review big data analytics tools and technologies that combine text mining, machine learning and network analysis for security threat prediction, detection and prevention at an early stage.
Big Data, DeZyre, Fraud Detection, Security
