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anonymity

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Harassment By Package Delivery

People harassing women by delivering anonymous packages purchased from Amazon.

On the one hand, there is nothing new here. This could have happened decades ago, pre-Internet. But the Internet makes this easier, and the article points out that using prepaid gift cards makes this anonymous. I am curious how much these differences make a difference in kind, and what can be done about it.

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Commenting Policy for This Blog

Over the past few months, I have been watching my blog comments decline in civility. I blame it in part on the contentious US election and its aftermath. It’s also a consequence of not requiring visitors to register in order to post comments, and of our tolerance for impassioned conversation. Whatever the causes, I’m tired of it. Partisan nastiness is driving away visitors who might otherwise have valuable insights to offer.

I have been engaging in more active comment moderation. What that means is that I have been quicker to delete posts that are rude, insulting, or off-topic. This is my blog. I consider the comments section as analogous to a gathering at my home. It’s not a town square. Everyone is expected to be polite and respectful, and if you’re an unpleasant guest, I’m going to ask you to leave. Your freedom of speech does not compel me to publish your words.

I like people who disagree with me. I like debate. I even like arguments. But I expect everyone to behave as if they’ve been invited into my home.

I realize that I sometimes express opinions on political matters; I find they are relevant to security at all levels. On those posts, I welcome on-topic comments regarding those opinions. I don’t welcome people pissing and moaning about the fact that I’ve expressed my opinion on something other than security technology. As I said, it’s my blog.

So, please… Assume good faith. Be polite. Minimize profanity. Argue facts, not personalities. Stay on topic. If you want a model to emulate, look at Clive Robinson’s posts.

Schneier on Security is not a professional operation. There’s no advertising, so no revenue to hire staff. My part-time moderator — paid out of my own pocket — and I do what we can when we can. If you see a comment that’s spam, or off-topic, or an ad hominem attack, flag it and be patient. Don’t reply or engage; we’ll get to it. And we won’t always post an explanation when we delete something.

My own stance on privacy and anonymity means that I’m not going to require commenters to register a name or e-mail address, so that isn’t an option. And I really don’t want to disable comments.

I dislike having to deal with this problem. I’ve been proud and happy to see how interesting and useful the comments section has been all these years. I’ve watched many blogs and discussion groups descend into toxicity as a result of trolls and drive-by ideologues derailing the conversations of regular posters. I’m not going to let that happen here.

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De-Anonymizing Browser History Using Social-Network Data

Interesting research: “De-anonymizing Web Browsing Data with Social Networks“:

Abstract: Can online trackers and network adversaries de-anonymize web browsing data readily available to them? We show — theoretically, via simulation, and through experiments on real user data — that de-identified web browsing histories can be linked to social media profiles using only publicly available data. Our approach is based on a simple observation: each person has a distinctive social network, and thus the set of links appearing in one’s feed is unique. Assuming users visit links in their feed with higher probability than a random user, browsing histories contain tell-tale marks of identity. We formalize this intuition by specifying a model of web browsing behavior and then deriving the maximum likelihood estimate of a user’s social profile. We evaluate this strategy on simulated browsing histories, and show that given a history with 30 links originating from Twitter, we can deduce the corresponding Twitter profile more than 50% of the time. To gauge the real-world effectiveness of this approach, we recruited nearly 400 people to donate their web browsing histories, and we were able to correctly identify more than 70% of them. We further show that several online trackers are embedded on sufficiently many websites to carry out this attack with high accuracy. Our theoretical contribution applies to any type of transactional data and is robust to noisy observations, generalizing a wide range of previous de-anonymization attacks. Finally, since our attack attempts to find the correct Twitter profile out of over 300 million candidates, it is — to our knowledge — the largest scale demonstrated de-anonymization to date.

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