How can you protect sensitive information during web scraping?

由人工智能和领英社区提供技术支持

Web scraping is a powerful technique for extracting data from websites, but it also poses some risks for both the scraper and the scraped. If you are not careful, you might expose sensitive information such as personal data, login credentials, or intellectual property to malicious actors or legal issues. In this article, you will learn how to protect sensitive information during web scraping by following some best practices and using some tools.

此文章中的业界达人

由社区从 4 条内容中精选。了解更多

Christopher L.

1 Use encryption and proxies

One of the most basic ways to protect sensitive information during web scraping is to use encryption and proxies. Encryption ensures that your data is not readable by anyone who intercepts it, while proxies hide your IP address and location from the websites you scrape. You can use HTTPS or SSL protocols to encrypt your web requests and responses, and you can use VPNs, TOR, or web-based proxies to mask your identity and avoid detection.

添加您的观点

Christopher L.
举报内容
As the scraper encryption is unnecessary as you have no reason to prevent the information being leaked, you are in fact taking advantage of the fact data is being leaked already, however integrity verification is helpful to ensure you're not being MitM and fed dirty data. Proxy will not serve the purpose of 'protect sensitive information' for either scraper or scrapee - it also does not provide non-repudiation controls as IP alone will not be the only thing to identify you as the scraper. As the scrapee a proxy facilitates access, not protects. Tor is another misunderstood utility in this context, it can disguise (privacy) but if exit nodes are compromised (operational security) there is risk using Tor that is not present when not using Tor

已翻译

赞

2 Follow ethical and legal guidelines

Another way to protect sensitive information during web scraping is to follow ethical and legal guidelines. This means respecting the privacy and copyright of the websites you scrape, as well as the users whose data you collect. You should always check the terms of service and robots.txt files of the websites you scrape, and avoid scraping personal or sensitive data without consent or legitimate purpose. You should also comply with the relevant laws and regulations in your jurisdiction, such as the GDPR or the CCPA.

添加您的观点

Christopher L.
举报内容
This requires the publishers of data to antipate lawful/ethical scrapers, permit them, and plan accordingly. Alternatively, regardless how ethical a scraper may be, there is a reliance on the data publisher to apply the prerequisites that allow you to follow these guidelines. The fact remains that if the scraper is not ethical they are not beholden to these expectation. Additionally, the data publishers that do not anticipate and plan for scrapers of any type are the default and none of this applies either. Only defaults matter, and those exist in the browsers - that is where we should be applying our focus.

已翻译

赞

3 Secure your storage and access

A third way to protect sensitive information during web scraping is to secure your storage and access. This means ensuring that your data is stored in a safe and encrypted location, and that only authorized people can access it. You can use cloud services, such as AWS or Google Cloud, to store your data in secure servers, and you can use authentication and authorization mechanisms, such as passwords or tokens, to control who can access your data. You should also backup your data regularly and delete it when it is no longer needed.

添加您的观点

Christopher L.
举报内容
These examples are AWS or Google Cloud indicating the premise is "public accessible" and therefore the only real set of controls here are; 1. allow list so that known requesters can access, 2. Authorisation so that after you are authenticated, each request you make is checked to ensure "you" are allowed to access the data. 3. if all data is allowed to everyone, then the AAA principal applies to ensure all access is not only authenticated and authorisaed but also audit logged so that we can monitor for access patterns and make decision around restricting access based on patterns like scraping. Only storing data you need, and only for as long as you need to keep it, are foundational information security controls not related to scraping itself

已翻译

赞

4 Use data anonymization and pseudonymization

A fourth way to protect sensitive information during web scraping is to use data anonymization and pseudonymization. These are techniques that remove or replace identifying information from your data, such as names, email addresses, or phone numbers, with random or fake data. This reduces the risk of exposing personal or sensitive data to unauthorized parties or breaching privacy laws. You can use libraries, such as Faker or Anonymizer, to generate fake data, or you can use hashing or encryption algorithms to transform your data.

添加您的观点

Christopher L.
举报内容
So pseudonymization is proven to be reversed with trivial means, and anonymization itself effects the resulting anonymised data, not the source data. What we really need to consider here, in context to scraping, is the source data after anonymisation, is deleted or rendered inaccessible with the same methods used to access the anonymised data.. Anything less than this control makes all anonymization efforts as useless as pseudonymization is..

已翻译

赞

5 Monitor and audit your web scraping activities

A fifth way to protect sensitive information during web scraping is to monitor and audit your web scraping activities. This means keeping track of what data you scrape, how you scrape it, where you store it, and who you share it with. This helps you identify and prevent any potential data breaches, errors, or misuse of your data. You can use tools, such as Scrapy or Selenium, to log your web scraping actions, and you can use dashboards, such as Grafana or Kibana, to visualize and analyze your data.

添加您的观点

6 Test and update your web scraping code

A sixth way to protect sensitive information during web scraping is to test and update your web scraping code. This means ensuring that your code is free of bugs, vulnerabilities, or inefficiencies that might compromise your data quality, security, or performance. You should always test your code before running it on live websites, and you should update your code regularly to adapt to any changes in the websites you scrape. You can use tools, such as Pytest or Unittest, to test your code, and you can use tools, such as Git or Docker, to manage your code versions.

添加您的观点

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

添加您的观点

Data Analytics

+ 关注

给文章评分

我们借助人工智能创建了此文章。您认为这篇文章怎么样？

很棒不太好

举报此文章

How can you protect sensitive information during web scraping?

1

2

3

4

5

6

7

1 Use encryption and proxies

2 Follow ethical and legal guidelines

3 Secure your storage and access

4 Use data anonymization and pseudonymization

5 Monitor and audit your web scraping activities

6 Test and update your web scraping code

7 Here’s what else to consider

Data Analytics

给文章评分

感谢您的反馈

更多Data Analytics相关文章

更多相关阅读内容