To reduce the number of reports caused by this issue which is outside of uBO's control, uBO's toolbar icon will now reflect its readiness status at browser launch.
Cyber criminals purchase advertisements that appear within internet search results using a domain that is similar to an actual business or service. When a user searches for that business or service, these advertisements appear at the very top of search results with minimum distinction between an advertisement and an actual search result. These advertisements link to a webpage that looks identical to the impersonated business’s official webpage.
In instances where a user is searching for a program to download, the fraudulent webpage has a link to download software that is actually malware. The download page looks legitimate and the download itself is named after the program the user intended to download.
而 FBI 建議個人的保護方式包括了 ad blocking extension，這算是減少被攻擊的管道：
Use an ad blocking extension when performing internet searches. Most internet browsers allow a user to add extensions, including extensions that block advertisements. These ad blockers can be turned on and off within a browser to permit advertisements on certain websites while blocking advertisements on others.
Grafana to render the statistics ;
InfluxDB to store the information ;
syslogd(8) and awk(1) to turn DNS queries into statistics ;
collectd(1) and shell script to store unbound statistics and logs ;
unbound(8) and shell script to get and block DNS queries.
Banner blindness is a phenomenon in web usability where visitors to a website consciously or unconsciously ignore banner-like information. A broader term covering all forms of advertising is ad blindness, and the mass of banners that people ignore is called banner noise.
The first banner ad appeared in 1994. The average click-through rate (CTR) dropped from 2% in 1995 to 0.5% in 1998. After a relatively stable period with a 0.6% click-through rate in 2003, CTR rebounded to 1% by 2013.
Smart speakers collect voice input that can be used to infer sensitive information about users. Given a number of egregious privacy breaches, there is a clear unmet need for greater transparency and control over data collection, sharing, and use by smart speaker platforms as well as third party skills supported on them. To bridge the gap, we build an auditing framework that leverages online advertising to measure data collection, its usage, and its sharing by the smart speaker platforms.
We evaluate our framework on the Amazon smart speaker ecosystem. Our results show that Amazon and third parties (including advertising and tracking services) collect smart speaker interaction data. We find that Amazon processes voice data to infer user interests and uses it to serve targeted ads on-platform (Echo devices) as well as off-platform (web). Smart speaker interaction leads to as much as 30X higher ad bids from advertisers. Finally, we find that Amazon's and skills' operational practices are often not clearly disclosed in their privacy policies.
幾個比較重要的資訊，其中一個是「Network traffic distribution by persona, domain name, purpose, and organization」：
