We attended a mid-week afternoon wedding, which has thrown off the newsletter schedule a bit, since that made early Wednesday AM and Thursday catch-up times at the place that pays the bills. I'll drop another edition on Saturday to make up for it.

term2svg

I haven't had a ton of need to record my screen or terminal sessions over the past few years, but I suspect that's about to change as "outreach and education" is a major part of my new job. To prepare for said need, I've been poking around at various utilities in this space and came across a neat little project: termtosvg [GH].

Rather than make a gif or movie, termtosvg makes (wait for it…) SVGs! It uses CSS animation settings and directives to accomplish this super-cool task.

You can just enter termtosvg at any command line and have it record everything you do up until typing exit as in this toy example: https://rud.is/dl/term-to-svg-example.svg.

It is also possible to use the -c option to fire up a specific terminal program and record that session (i.e. termtosvg -c R will invoke R and record all the R console work).

There are configuration options for loop delay, screen geometry, animation frame duration, and templates for customizing the output.

The project is unmaintained (someone should offer to take it over!), but it's worked great for me.

OkSo

The internets are awash in browser-based diagramming/drawing tools. OkSo (@okso_app)goes beyond mere sketching and provides a way to organize drawings. It uses the concept of nested pages. Each page is a first-class citizen of your drawing along with other shapes like freehand curves, rectangles, ellipses, or texts. So, you may embed/draw links to sub-pages inside the page. It means that you may organize your drawings in the nested tree structure.

The app is super-minimalist, both in terms of the user interface and what features the app creators expose. The built-in library of symbols is deliberately small, and the entire app feels like a combination of a tool like Obsidian and a whiteboard.

You do not need an internet connection to use OkSo, as it has a progresive web app mode for both desktop and mobile.

If you're into freehand note-taking, OkSo may be a neat option to try.

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CCTV-Exposure

Our privacy erodes daily, and there's little we can truly do to stop the degradation. To make matters worse, said privacy is eroding everywhere, including meatspace. If you leave your abode, there is little doubt you'll encounter at least one closed-circuit television (CCTV) camera on your day's journey.

University of Jyväskylä researchers Hannu Turtiainen, Andrei Costin, and Timo t. Hämäläinen set out to understand this exposure and build some tools to help estimate personal CCTV exposure in any given location, and documented their approach and results in a recent paper. Here's the abstract:

In this work, we present CCTV-Exposure-the first CCTV-aware solution to evaluate potential privacy exposure to closed-circuit television (CCTV) cameras. The objective was to develop a toolset for quantifying human exposure to CCTV cameras from a privacy perspective. Our novel approach is trajectory analysis of the individuals, coupled with a database of geo-location mapped CCTV cameras annotated with minimal yet sufficient meta-information. For this purpose, CCTV-Exposure model based on a Global Positioning System (GPS) tracking was applied to estimate individual privacy exposure in different scenarios. The current investigation provides an application example and validation of the modeling approach. The methodology and toolset developed and implemented in this work provide time-sequence and location-sequence of the exposure events, thus making possible association of the exposure with the individual activities and cameras, and delivers main statistics on individual's exposure to CCTV cameras with high spatio-temporal resolution.

This project is based on previous work by some of the same authors as they sought to build a privacy/safety-aware navigation system. Here's that abstract:

For the last several decades, the increased, widespread, unwarranted, and unaccountable use of Closed-Circuit TeleVision (CCTV) cameras globally has raised concerns about privacy risks. Additional recent features of many CCTV cameras, such as Internet of Things (IoT) connectivity and Artificial Intelligence (AI)-based facial recognition, only increase concerns among privacy advocates. Therefore, on par \emph{CCTV-aware solutions} must exist that provide privacy, safety, and cybersecurity features. We argue that an important step forward is to develop solutions addressing privacy concerns via routing and navigation systems (e.g., OpenStreetMap, Google Maps) that provide both privacy and safety options for areas where cameras are known to be present. However, at present no routing and navigation system, whether online or offline, provide corresponding CCTV-aware functionality.

In this paper we introduce OSRM-CCTV -- the first and only CCTV-aware routing and navigation system designed and built for privacy, anonymity and safety applications. We validate and demonstrate the effectiveness and usability of the system on a handful of synthetic and real-world examples. To help validate our work as well as to further encourage the development and wide adoption of the system, we release OSRM-CCTV as open-source.

Said system operates in two modes:

Our CCTV-aware solution enables two modes of routing. Firstly, privacy-mode which aids maintaining privacy by choosing a route where CCTV cameras are avoided. Privacy-mode is strict in the sense that it will never choose a route that leads through the field of vision of a CCTV camera. Avoiding CCTV cameras would be desirable anytime when privacy or anonymity is important. Secondly, safety-mode which aids maintaining safety by choosing a weighed route that leads through the fields of vision of CCTV cameras. Safety-mode is called safe because sometimes (e.g., at night and for the preference of staying physically safe) one would prefer to be actually detected and recorded by CCTV cameras.

The database of CCTV position is presently small (they're using computer vision algorithms to identify surveillance cameras in Google Street View images), but they hope to gather more location data and release a friendly API at some point. Perhaps they can leverage leaked Ring camera locations as well.

Stay tuned to see how their project progresses, and keep your own eyes out for cameras the next time you're out.

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FIN

Someone on Twitter asked me about how to keep safe on macOS after being hit by ChromeLoader, so I dropped some thoughts and opines which might be helpful to others as well. ☮