Today's Document
TVSTRANGERTHINGS
Cosmic Funnies
Misplaced Lens Cap

Product Placement
"I'm Dorothy Gale from Kansas"

❣ Chile in a Photography ❣
tumblr dot com
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todays bird
NASA
untitled
Claire Keane
Xuebing Du

izzy's playlists!
Lint Roller? I Barely Know Her
will byers stan first human second
Cosimo Galluzzi
Fai_Ryy

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@blackberriesandbluegrass
may you get a sign this week that shows you that you’re on the right path and that things are flowing and moving in your favor. may the sign be evident, clear, and direct
Shout out to everyone that’s actually really intelligent but have difficulty articulating what they know especially when they’re being questioned.
2019 is going to be a great year because we’re going to fucking make it that way, no more of this “I hope good things come to me” shit, I’m gonna go out and drag good things to me by the fucking hair
SAME FRIEND, SAME
2019 Is The Year Of Not Even Remotely Fucking Around
childhood summers in the south
flat dr. pepper bottle rolling in the floorboard of daddy’s pickup
there’s some country song playing on the radio, you don’t know what it’s about but the only words you can pick out are ‘bar’ and ‘highway’
on the general store counter is a container of bubblegum, slimjims, and a large jar of dill pickles, the wood floor is dusty on your feet
picking muscadine grapes in the backyard, Daddy’s making “musky-dime” wine
watching cottonmouth snakes snap dragonflies at the river bank
the grass is grown tall, granddaddy’s ford hasn’t moved since he died
lying in bed listening to the crickets and cicadas of the night under cotton sheets, scratching mosquito bites until they bleed
sunday morning at church with mama, a lady hands her an avon brochure, she politely smiles and puts it in her purse
a honeysuckle bush intertwines with the backyard fence, you always grab a flower or two for that tiny drop of nectar inside
Hey
I completely forgot about this place. How is everyone?
Never ever turn off your phone: rethinking security culture in the era of big data analysis.
Back in the 80′s if you were a pissed off anarchist that wanted to burn down a building, you probably checked your home for listening devices and made a plan. If you were the same kind of pissed off anarchist in the late 90′s, you turned off your phone and encrypted your online traffic. In the 2020′s we’re gonna have to change our strategies once again. Intelligence gathering has adapted and so we must adapt too.
To get a head start at this, let’s look at how big data analysis is being used. To do this, we’ll need to talk about 3 things: metadata, patterns and networks. Those sound boring and complicated but I’m not a techy and I won’t bore you with tech language, I’ll keep it as easy as I can.
Metadata: In the context of online activity, ‘content’ means ‘the message you send’ and ‘metadata’ means ‘everything other than the content’. So, for example, if you send your friend a text about lunch, the content might be “Let’s go out for lunch” and the metadata might be “Message send at 01/04/2018 11.32 from phone 0478239055 to phone 079726823 using Signal”.
This information is registered by your phone even if the app encrypts your actual message. Your metadata is very badly protected by technology and very badly protected by the law. No matter which country you are in, most of your metadata if freely available to intelligence agencies regardless of whether you are a suspect in anything.
Patterns: Whether you realize it or not, your metadata has a pattern. If you have a daily job you might have a very consistent pattern, if you do not your pattern might be more flexible but you have a pattern. If someone wanted to know the rhythm of your day, they could very easily do so because your pattern is in the metadata.
For example: Maybe you use the wifi at your favourite bar on most Sunday nights until about midnight, you wake up around 10 AM and check your Signal, you use your public transport card to get to class every Monday afternoon and you spend on average 1 hour on Tumblr twice a day. All this is part of your pattern.
Networks: You have online networks. Your facebook friends, the people in your phone adress book, the dropbox you share with coworkers, everyone who bought online tickets to the same punk band you attended, the people using the same wifi points as you. Take your networks, combine them with other people’s networks, and clusters reveal themselves. Your work community, your family, your activist scene, etc.
If you are in an anarchist community that will probably be abundantly clear from all your minor network connections like going to the same band and knowing the same people as other anarchists. Even if you never liked an anarchist facebook page or pressed ‘going’ on an anarchist facebook event, your network is hard to hide.
Now, let’s say you commit a crime,
the kind that would result in some serious research. Let’s say that on Sunday night 3 AM, you are your friends go out and burn down a nazi’s house. It’s obvious that anarchists did it but there are no other clues. You use traditional style security culture: you burn your notes, you are careful not to communicate about your plans near technology and you do not leave physical traces.
But because you commited the crime that night, your metadata will vary strongly from your usual rhythm: you stay at your usual bar until 2 AM to wait for your friends, you do not wake up at 10 AM in the morning so you do not check your Signal or Tumblr until 1 PM. You do not go to class. Your metadata pattern is very different from your usual pattern. The metadata patterns of your friends are different too. If one of you is clumsy, they might generate a super suspicious metadata signal like a phone being switched off at 2.30 AM and activated at 4AM. You wouldn’t be the first.
If I wanted to solve this crime using data analysis, what I would do is:
let a piece of software run a pattern analysis of the local anarchist scene to generate the 300 people most connected to the anarchist scene.
let a second piece of software analyse the metadata patterns of those 300 people over the last months and identify the biggest metadata variations around Sunday night as well as very suspicious metadata activity
Illiminate pattern variations with an obvious cause or an obvious alibi (people who are on vacation, people who are in the hospital, people who lost their job, etc).
Do indepth research into the ones that remain.
Which is how, out of a massive amount of people that I couldn’t possible all listen to at the same time, I could quickly identify a few to monitor closely. This is how I could find and catch you.
So, now what?
If traditional security culture doesn’t protect us as well as it used to, how do we adapt? Well, I don’t have all the answers but for a start, I’d say: know your network + know your pattern.
In the case of the crime above: leave the bar at midnight, return home and put your phone on your bedside table. Check the apps you check before going to bed and set your alarm to 10AM. Return to the bar without your phone. Commit the crime. Wake up at 10AM and check your Signal. Drag yourself to class or ask a comrade to make the trip with your travel card and do not use technology in your home while the comrade is taking your travel card to class. Stick to your pattern. Never ever turn off your phone.
You might also be able to manipulate your network but that seems much harder to do. Not having a smartphone and dropping out of all social activity online is a big commitment. Knowing your data pattern and making sure your data pattern doesn’t look out of the ordinary? Much less commitment.
Some of the old rules will still apply: don’t talk about a crime around devices with microphones, don’t brag after a succesful action, etc. Other rules, like ‘turn off your phone when planning an illegal act’ need to change because their metada looks too out of the ordinary. No one switches off their phone anymore. We look suspicious as fuck when we do.
This is just one idea on how we could update our security culture. There are probably other people with other, better ideas about updating our security culture. If we start the conversation, we may get somewhere.
Finally: we need to keep adapting.
As technology changes, more information is becoming available, including data we have very little control over. Smart-tv’s and ads in public spaces that listen to every word we say and the tone of our voice when we say it are examples. Data analysis projects are currently using license plate reading software on security footage to map the travel patterns of cars. A lot suggests they may soon be ready to do the same with face recognition, at which point the presence of our face in public space becomes part of our metadata. More information means more accurate data analysis. Our metadata may soon be too vast annd too complex to completely map and mirror. Which means we will need to adapt our counter measures if you want to hide something.
How do we keep it all under the radar? I don’t know. But let’s try to figure this shit out. These are some first thoughts about what security culture should look like in the age of modern big data analysis and I’d be very happy for any insights from comrades that have some thoughts on this.
Also: feel free to distribute and rework these words without credit.
I had a class on security. One of the students said “well, they only track the metadata.” My prof’s answer to that is “Yes, and the metadata is EVERYTHING.”
Yup. Metadata is when you sleep, who you talk to, where you travel and a lot of other details about you. Metadata shows how often you visit your parents, who of your friends you talk to most often and who have faded out of your life. Metadata reveals that you stopped talking to your partner on February 4th and have been watching Netflix until 3 AM regularily since then. Metadata reveals that you called a suicide hotline, or visited the website of an abortion clinic or a weapons dealer. Metadata reveals how often you call your therapist.
Consider the following hypothetical example: A young woman calls her gynecologist; then immediately calls her mother; then a man who, during the past few months, she had repeatedly spoken to on the telephone after 11p.m.; followed by a call to a family planning center that also offers abortions. A likely storyline emerges that would not be as evident by examining the record of a single telephone call.
Example from a Washingtonpost article about metadata
Outliers in your metadata reveal as much as patterns. If you have a network of friends that you contact regularily and you suddenly start sending messages to someone who is completely unconnected to your network, that could reveal a new romantic relationship or a partner in crime.
Apply metadata to activist networks and you get the potential to follow much of it’s comings and goings. Who is well connected to who, who stop talking to each other, which network fractures and how the participants regroup, how many of them travel to specific events, etc etc.
🌺Spring🌺 cats with 👑 🌺 🌺🌸🌼🌺🌸🌼🌺🌸🌼🌺
🔮💑👪🛡🔒💉💊🔫🗡🔒🛡👪💑🔮
A spell to keep your loved ones safe from any kind of harm
Likes charge
Reblogs cast
ily: i love you
ilysm: i love you so much
iccifymfbiccy: i can’t carry it for you, mr frodo, but i can carry you
viggo mortensen’s appeal as aragorn is 70% the voice, 25% the scene where the wild horse saves him from drowning, 12% hair, 8% ‘the beacons are lit!’, 3% swinging around the broken blade, 1.03% spitting soup back into the bowl on a windy day, .3% the way he speaks elvish (which mostly fits into the voice, but its elvish so its special), and .0004% when he kicks the orc head and screams
This is blatant “smoking a pipe with his hood on in Bree” and “shoving the double doors of helm’s deep open” erasure and I will not stand for it.
There is something about sunlight that makes life seem just a little less horrible
it’s the vitamin d bitch
when the story is just not working, but you keep writing anyway
Current mood…
Reminder that she actually wins that season, so keep your head up.
Reminder that she constantly had trouble believing that she deserved to be there and her first few could best be described as ‘not the worst’.
And she won. She stayed positive, cried when she needed to, and kept going.
Once more:
Stay positive
Cry when you need to
Keep going
Daily reminders
Drink water
Sit up straight
Breathe deeply
Stay present
Be grateful
Love everything
Thank you! 💛
This is one of my favorite posts because that cat’s fucking name is fucking meatloaf
Let us just appreciate that this person’s dad didn’t know when they would be home and so he couldn’t plan for them to be able to join the family for dinner, but he knew with no doubts that dear sweet Meatloaf staying in that exact position for hours was an absolute in this scenario. Truly, that cat was named well.
one of my favorite posts on tumblr over the course of 5 fucking years.. clearly i need a life
Meatloaf is a reliable cat and did not steal the money for selfish reasons. A rare friend.
I love Meatloaf. :)
Bless Meatloaf
Reblog Money Meatloaf to get surprise $40