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What is brave browser & how it works ?

But the best privacy feature of Brave is its private browsing mode. Despite what most people assume, standard private browsing (known in Chrome as “Incognito” mode) doesn't keep your web activity or identity private from your ISP or the websites you visit–or perhaps even from Google

By InDesign Media | Friday 4th October 2019
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Brave Browser
Brave Browser

Is the brave browser safe?

Short Answer is ‘Yes’ but Brave is not the MOST secure browser among all. Brave is a Chromium Browser. That means, it uses Chromium Project’s source code. Chromium Project is open-source and it is maintained by Google.

How does brave browser work?

First, Brave Rewards locally picks which private ads to show you based on your browsing activity. Then, Brave uses an anonymous accounting process to confirm ad event activity, keep personal details private, and ensure people earn rewards for their attention.

Is it better than Chrome?

Comparatively, Brave is Faster And Private Than Chrome web browser while upholding support for all Chrome Extensions. Moreover, Brave web browser is reliable, high at performance, compatible and the fastest browser among other Chromium-based web browsers like Opera, Vivaldi or Microsoft’s Edge for a chance.

Why You Should Use brave browser?

Not to mention, Brave does several things to protect your security online. First, it blocks all malware, malvertising, spyware, phishing, fingerprinting, and also upgrades websites to HTTPS (a secure connection between you and a website). Also, it also prevents scripts running on the page, so no-one can hijack your browser. 5 reason why we should use it.

Is it free?

Above all, Brave is a free and open-source web browser developed by Brave Software, Inc. based on the Chromium web browser. Additionally ,the browser blocks ads and website trackers. As of 2018, Brave supports Windows, macOS, Linux, Android, and iOS.

Is Brave really private?

But, the best privacy feature of Brave is its private browsing mode. Despite what most people assume, standard private browsing (known in Chrome as “Incognito” mode) doesn’t keep your web activity or identity private from your ISP or the websites you visit–or perhaps even from Google.

What is the safest browser to use?

While some browsers claim to be secure against vulnerabilities, they might not be the best choice from a privacy perspective.

  1. Google Chrome. Google Chrome is a secure browser, but it also collects quite a bit of data.
  2. Microsoft Internet Explorer/Edge.
  3. Opera browser.
  4. Epic browser.
  5. Safari browser.
  6. Vivaldi browser.

Is it faster than Chrome?

Brave is based on Chromium, and so are other viable alternatives like Vivaldi, Opera, and soon even Microsoft’s Edge. So, each of those browsers supports Chrome extensions and provides performance comparable to — or, in the case of Brave, faster than — Google’s Chrome.

How much does it cost?

Notably, the company behind the browser, Brave Software, won’t begin rolling out the actual token rewarding for another several weeks. But, it estimates participating users will be able to earn around $60 to $70 this year, and possibly around $224 in 2020.

What is the safest Internet browser?

The best browser 2019: a faster, safer way to get online

  1. Mozilla Firefox. Firefox is back after a total overhaul, and has retaken its crown.
  2. Google Chrome. If your system has the resources, Chrome is 2018’s best browser.
  3. Opera.
  4. Microsoft Edge.
  5. Microsoft Internet Explorer.
  6. Vivaldi.
  7. Tor Browser.

Brave Fingerprinting Protections v2: Farbling for Greater Good

This is the fourth in an ongoing, regular series of blog posts, describing new privacy-related features in Brave. This post describes work done by Senior Software Engineer Mark Pilgrim, Senior Privacy Researcher Peter Snyder, Principal Engineer Brian Johnson, and Chief Scientist Ben Livshits.

The TL;DR

Not to mention, Brave is redesigning its browser fingerprinting defenses to build on the randomization-based techniques discussed in the previous post. Also, these new defenses provide stronger and more web-compatible protections by default: for users who are willing to accept some broken sites for further privacy, they can opt into an even stronger set of defenses. Moreover, this system is currently being developed, and parts of it can be used today in our Nightly builds.

Overview

Brave’s goal is to both be the best browser for protecting your privacy, and the best browser for day-to-day, full-featured Web use. Also, this post describes new privacy features being developed in Brave to better protect user privacy, without breaking privacy-respecting, user-serving websites. And, these new features build on the randomization based defenses described in the previous entry in this series, and we detail how these randomization defenses will be applied to more of the Web API in Brave. We will cover three areas:

  1. Past Generation Fingerprinting Defenses
  2. Brave’s New Fingerprinting Defense System: Farbling
  3. A Possible Future of Fingerprinting Protections in Brave

1. Past and current Generation Fingerprinting Protections

Brave’s goal is to improve the Web by, among other things, providing a full featured, pleasant to use browser that protects your privacy without degrading the browsing experience. First, one difficult type of privacy-threat that Brave protects against is “browser fingerprinting”. Moreover, this section briefly describes what browser fingerprinting is, how browsers (including Brave) have attempted to defend against it, and why current protections are insufficient.

What is Fingerprinting? (a brief refresher)

Browser fingerprinting is a technique for identifying and tracking people on the Web by combining multiple semi-identifiers (things that are slightly different about each person’s browser. Such as, the size of the browser window or computer hardware details) and combining them into a single, unique identifier.

In addition, the technique works like this: different people have different language preferences, use different operating systems, etc. In isolation, none of these differences is likely to be unique enough to identify you. And, a website can see that one user reads French, while another reads Malay. But, there will be many French and Malay speakers (amongst others). So, a site can’t track individuals based on whether they prefer French, Malay, or any other language. Similarly, some users use MacOS, others Windows and others Linux; there are many people in each category.

However, by combining a large number of these semi-identifiers, sites can identify individuals. Not to mention, a site might have a lot of French readers, and a lot of Linux users; only a much smaller number of people will be both using Linux and preferring French. And, by combining many such semi-identifiers, sites can often uniquely identify (and so track) a large percentage of their users.

How Do Most Browsers Currently Address Fingerprinting?

Most browsers try to prevent fingerprinting by reducing the number of possible values each of these semi-identifying features return. For example, instead of specifying that a user prefers “Australian English” or “British English”, the browser might just report “English” in order to reduce how identifying a language preference is.

While this can bring some privacy improvement at the margins, in practice these defenses are insufficient for several reasons. First, there are many semi-identifiers in the browser. So, reducing the identifiability of just some isn’t sufficient to keep most users private (especially for people on uncommon hardware, or uncommon languages, etc). Second, privacy-through-similarity fingerprinting protections are only effective on popular site. And, if a site doesn’t have large numbers of visitors that are similar to you, your browser will still look unique. Third, and most tricky, modifying values to be less identifying can break websites that rely on that value being accurate. Thus, this category of fingerprinting protection then creates a privacy/functionality trade-off.

How is Brave’s Current System Evolving to Further Prevent Fingerprinting?

Brave is transitioning between two systems for preventing fingerprinting. Additionally, in some places, Brave removes or otherwise modifies browser features, to try to make different Brave users look similar. While useful, these defenses have all the weaknesses discussed above. Because of these weaknesses, and because these defenses often break websites. And, Brave applies these defenses only in third-party frames by default. Again, useful but not ideal.

However, Brave also ships some defenses that employ a very different strategy: instead of trying to make everyone look identical, these defenses try to make everyone look different, to each website, for each session. Since, this category of defenses make Brave users look different to each site, sites cannot use fingerprinting to track users across sites.

Similarly, these defenses were discussed in detail in the previous entry in this series, and are currently applied to the canvas and Web Audio APIs. And, the rest of this post describes both how Brave will improve its existing randomization-based defenses. Also, how Brave plans to apply these randomization-techniques to many more parts of the browser.

2. Fingerprinting Protections 2.0: Farbling for Great Good

Brave currently applies randomization-based protections to canvas and Web audio based fingerprinting. We call this privacy-through-randomization technique “farbling”. Additionally, this section presents how Brave is building on existing farbling protections to further protect against fingerprinting.

What is Farbling?

Farbling is Brave’s term for slightly randomizing the output of semi-identifying browser features, in a way that’s difficult for websites to detect. But, doesn’t break benign, user-serving websites. Also, these “farbled” values are deterministically generated using a per-session, per-eTLD+1 seed2 . So, a site will get the exact same value each time it tries to fingerprint within the same session. But, that different sites will get different values, and the same site will get different values on the next session. Moreover, this technique has its roots in prior privacy research, including the PriVaricator (Nikiforakis et al, WWW 2015) and FPRandom (Laperdrix et al, ESSoS 2017) projects.

Similarly, Brave’s farbling-based fingerprinting protections have three levels, each described in more detail in the following subsections:

  • Off: no fingerprinting protections are applied
  • Default: protections that prevent fingerprinting and have a low risk of breaking websites
  • Maximum: protections designed to provide fundamental defenses against fingerprinting, even at the risk of breaking sites

In addition, this system is currently under development, with some parts shipping in Nightly builds, and others still being built. We anticipate the full system to be completed in the next few months, and deployed in our release builds shortly after.

Similarly, these defenses are applied in both first and third-party contexts. Also, it’s trivial and common for third-party frames to collude with the first-party when tracking users. Thus, we need to apply our defenses accordingly.

Farbling Level: Off

In this setting, Brave will apply no fingerprinting protection techniques. Not to mention, our goal is for users to never apply this setting.  The “off” setting is included for sites requiring a high level of trust, for developers testing functionality, or other uncommon cases.

Farbling Level: Default

The default setting for farbling-based fingerprinting is to add small amounts of randomness to semi-identifying endpoints; small enough that it’s not noticeable to humans, but sufficient to prevent sites from tracking you.

Similarly,This setting will be the default configuration, and is designed as a balance between privacy protections and web compatibility. So, we will continue to tweak and improve as we see how online trackers respond.

The primary goal of these defenses is to provide strong protections against web-scale trackers and advertisers, who want to identify users, but can’t spend outsized effort on any one target. As a secondary goal, these defenses aim to make benign use look very different from malicious use, so as to leave room for further intervention opportunities if needed. And third, when the prior two goals aren’t achievable (because of the nature of the APIs), we aim to significantly increase the amount of work required by the attacker, by requiring attackers to enumerate devices they’re trying to fingerprint, or reduce the amount of material fingerprints can draw from.

We should note that the “default” category still uses values derived from the “true” values of the underlying features. Because of this, we expect that these defenses could be circumvented by motivated, targeted attacks. Protecting against these hypertargeted attacks is not Brave’s primary goal; Brave’s goal is to protect users from the kinds of online trackers and privacy violations that are (sadly) pervasive on the Web, which in turn depend on large-scale economic return on investment to the fingerprinting adversary. Users requiring protection against targeted attacks may be better served by using tools specifically designed to protect against those, such as the Tor Browser Bundle.

Farbling Level: Maximum

Finally, Brave’s new fingerprinting defenses will include a third, “maximum” protection setting that provides additional privacy protections, although it may also break sites. In this category, randomized values are returned without incorporating any “true” underlying input. Where the “default” setting will add subtle randomness to fingerprintable outputs, the “maximum” setting is only the random values.

Because, in this configuration, the returned values are unrelated to the “true”, fingerprintable values otherwise returned by the relevant APIs, we do not expect these defenses to be susceptible to the kinds of statistical or easily-distinguishable attacks that are possible in the “default” configuration. This, however, carries with it a heightened risk of breaking sites, which may not function correctly when given random values.

What Will Get Farbled (and How, and When)?

The previous subsections described the goals and levels of protection in Brave’s new farbling defenses. This section describes which browser features will be modified under the “default” and “maximum” configurations, and how.

The below table lists which features will be modified by our farbling-based fingerprinting defenses. The first column describes the interface being modified, and the second column lists the specific properties and functions being modified. The third column gives the link and issue number we use internally for tracking the implementation status of each change.

 

3. Fingerprinting Protections Still to Come

We’re excited to share our new farbling-focused fingerprinting defenses. Fingerprinting is an extremely difficult problem to solve without breaking the Web, so much so that browser implementers often pose the problem as “browser features or privacy, pick one”. Farbling is part of Brave’s effort to show that this is a false dilemma, and that the Web can be richly featured and privacy respecting.

However, while we’re confident farbling improves privacy on the Web, there is still more work to do.

Fingerprinting Protections v3?

The initial version of farbling-based defenses, currently being implemented and described in this post, cover the majority of APIs used in popular fingerprinting attacks today. However, there are additional semi-identifying features we plan to address too. For example, we have in-development plans to address font-enumeration based fingerprinting, and we’d like to share less identifying values about graphics-card hardware by default. We’ll share more about these plans as we complete development of the initial farbling system.

Fighting Fingerprinting By Improving Standards

Finally, the farbling-defenses described here will end up not being useful if new browser features are added to the Web that allow for new forms of tracking and identification. To prevent this from happening, Brave works in the W3C to make sure new browser features are privacy-preserving and human-respecting.

The main, though not only, way Brave works for privacy in standards is through PING, the W3C body responsible for reviewing new specifications and fighting for them to be privacy-respecting. This is ongoing, perpetual work, and we’re eager to work with privacy-minded partners in the W3C to improve the Web for everyone.

Conclusion

Brave currently leads the way in fingerprinting protection, and no other browser offers users the functionality that Brave presently features or is working on implementing. When users browse with Brave, they know they’re using a browser that puts their interests first, and that our novel fingerprinting protection techniques prevent them from being tracked by sites and third parties. We look forward to receiving feedback on our new techniques, and hope that others will choose to implement similar approaches to give users the privacy they deserve.

Footnotes

  1. We’re not sure where the term farbling comes from. Brendan Eich pointed to prior use of the term to mean “twiddling”, or “subtly modifying”. That phrase was more convenient to say than “privacy protections based on randomization” so we ran with it.
  2. Each time you start Brave, a unique, random session token is created. This is never exposed to websites in any form, and is regenerated when you restart Brave. This token is then mixed (i.e. HMAC256) with each first-party, top-frame domain you visit, to generate a new, session-lifetime token per domain. All farbled values are generated from these per-session, per-domain random seeds.

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