Noyse On Twitter: Another Cover Design For Mac
Russian cyber disinformation campaigns have many missions, but one of particular interest is using technology to monitor, influence, and disrupt online communications surrounding culturally sensitive topics or protests. The ability to watch these events, and even filter positive or negative tweets to amplify, gives rise to the ability to execute a number of disinformation campaigns. With reports of Russian disinformation campaigns in the news, many are curious how these attacks are even possible. As with most effective attacks, it all starts with good recon. Scanning a global conversation on social media isn't the same as scanning a network, but thanks to machines in Maltego designed for monitoring Twitter, we can use some of the same tools we use to examine networks to visualize social media conversations. Don't Miss. Disinformation Campaigns Disinformation campaigns were made famous by the tactics discovered to be in use during the 2016 election tampering operations used by Russian-linked hackers.
These attacks used the anonymous nature of Twitter and other social platforms to attempt to deepen political and social rifts in US society by spreading false and misleading information designed to be polarizing. To enable these campaigns, online conversations were carefully studied to craft information that would have the maximum impact. Once sensitive topics were gathered, the fake news was aggressively injected into the public discussion by strategically placed bots targeting real users determined likely to share the content as legitimate.
Often, these talks would appear to be from a valid or known source, or at the very least, a member of an existing fringe group. The careful study of online conversations used by activists or other politically involved users was a vital part of these campaigns. Several tactics contributed to the success of these efforts, such as feeding fake content to real users for distribution by monitoring who shared news stories, and what they tended to share. Amplifying a Polarized Discussion Social media companies have been developing the ability to automatically sort tweets and social media messages by sentiment, using machine learning to identify patterns associated with positive or negative tweets.
By using sentiment analysis, an attacker can amplify a polarizing discussion by triggering an army of bots to retweet and share legitimate tweets about specific topics or people depending on if they are saying negative or positive things. Don't Miss: The advantage of this attack is that you can emulate a reactive jammer, which waits for a specific type of communication to happen before performing the jamming action.
In this case, an attacker can use sentiment analysis to sort polarizing tweets to amplify, and quickly overwhelm, a discussion by amplifying fringe opinions. This prevents a fair and open debate, allowing the attacker to overcome dissenting views with tweets written by real users. Jamming Tactics Generally, the techniques used to jam other communications apply equally to interactions on social media. In particular, we'll discuss how continuous jamming, deceptive jamming, and scan-jamming can be used to dominate an online conversation. Continuous jamming effectively aims to overload the communications targeted with random noise in order to make it unsuitable for use.
It does not attempt to blend in with the conversation, instead, looking more like spam. Bots are used to flood a particular hashtag being used to communicate with unrelated tweets, diluting the discussion so that finding legitimate tweets becomes impossible. This tactic has the added benefit of Twitter automatically censoring the tweet because it's detected as being used to spread spam. Deceptive jamming aims to disguise the attack by making the jamming appear to be part of the conversation. In this attack, a targeted hashtag is flooding with legitimate looking tweets spreading confusing of misleading information. Through rendering the information on the channel useless by introducing doubt, anyone using the hashtag to communicate or understand what's happening will quickly find themselves buried under tweets offering important-sounding false information.
This attack can also be used in a targeted way by spreading negative information about critical individuals more quickly. Using Maltego to Monitor Unfolding Events in Real Time To launch any of these attacks, it's essential to be able to 'scan' an ongoing Twitter conversation the same way you would run Nmap on a network. Without knowing an attack surface, you cannot design a practical plan to attack it, so the challenge becomes mapping a very organic conversation like on Twitter using hacking tools usually more suited to scanning routers and hosts.
As it turns out, Maltego is a perfect platform for watching social media conversations unfold. With the added advantage of importing targets directly into Maltego for followup research or targeting, a hacker using Maltego to track social media can find all the key hashtags and users involved in the spread of information around an event, topic, or person. While most hackers think of Maltego as useful for finding static information like, several Maltego machines are specifically designed to do things like track users and topics of interest on social media.
Don't Miss: These tactics are used by authorities to track the social media accounts of known activists in real time, allowing police to stay on top of what's happening at protests in real time without a warrant. The same tactics can be used to decide on how best to use an army of Twitter bots to disrupt a society from half a world away. Step 1: Sign into Maltego To install Maltego, you'll need to have Java installed on your machine.
Maltego comes installed by default in, so if you're running Kali, you should be able to get started by just selecting it from the main menu. If you're using or, you can download Maltego Community Edition from the. Once you open up Maltego in Kali or install it on another system, you will need to create a free account with Paterva to use. Register the account, receive the confirmation email, and then enter the code to confirm your account so you can log in. When this is done, log into the Maltego Community Edition, and you'll be ready to start a new graph. Step 2: Begin Watching the Conversation In our example, we'll be searching for conversations around sensitive current events that could be used in a disinformation campaign. To start, we'll be using a machine that monitors Twitter for activity around certain phrases.
These phrases, like 'space force' or 'collusion,' are likely to bring up a heated debate on a sensitive topic. By zeroing in on the global conversation around these issues, we can start to determine who the major players are and what the discussion looks like. To start, click on the 'Machines' tab in Maltego, and you'll be taken to a menu where you can select the 'Run Machine' icon. This machine will pull in updates automatically, and you can see the timer to do so on the top right of the Machines pane. As the information fills the graph, you can start to organize it by selecting all entities with Ctrl-A. Don't Miss: In the Detail View pane on the bottom right, you can click the box next to the plus symbol to organize entities by type. Within these groupings, you can see Maltego has resolved certain entities as people who are being frequently mentioned or discussed.
This will begin to show you the people behind the conversations on this topic. Here, we can see the key people mentioned in conversations about 'collusion' after the machine runs a few times. Click on image to enlarge.
Step 4: Identify Social Media Channels for Jamming In the event an attacker wants to jam a conversation on a topic, this Maltego machine provides a convenient list of hashtags being used to communicate around a particular topic. With this information, an army of bots could flood the channel with noise, rendering the conversation impossible. You should be able to view hashtags from discovered tweets automatically, but if you're only seeing tweets in your graph, you can select all by clicking on the graph, choose Ctrl-A, right-click to bring up the transform menu, then type 'hashtag' into the search bar that appears.
This should show the 'To Hash Tags' transform, which you can click to extract hashtags from tweets. Step 5: Amplify Divisive Opinions with Sentiment Analysis Once you've gained a pool of tweets around a certain topic, you can start to automatically organize them by a few rules. One of the most interesting is sentiment analysis, which allows you to separate out negative or positive tweets about the topic you're monitoring.
These tools have been available to social media manager for years, but Maltego allows hackers to have the same advantage. Don't Miss: To sort discovered tweets by sentiment, select all with Ctrl-A, then right-click to show the transform menu. Type 'sentiment' to show the 'To Sentiment IBM Watson' transform. Click on this to run it on all discovered tweets. If you have a lot of tweets in the Community Edition, which has a 50 entity per run limit, grab the tweets 50 at a time in the Detail View and run them through the transform quickly to squeeze all the data out quickly. Freedom of Speech on Social Media Isn't Guaranteed Thanks to the promise of open communication in real time in a scalable fashion, Twitter has been used by journalists, activists, and others reporting critical information or coordinating events. This use has made the service a prime target for monitoring, interfering with, and suppressing online conversations by those with the resources to do so.
Advanced persistent threats like nation-state backed hackers will continue to exploit these weaknesses in platforms like Twitter that are used for online discussions to satisfy political, propaganda, and censorship ambitions. Because these attacks borrow from traditional jamming, some of the same defenses can be applied. First, finding out whether jamming is taking place in the first place must be established. If a conversation is suddenly flooded with messages from accounts which have little to no legitimate posts, or which appear to have been hijacked and are suddenly acting out of character, this is a sign a conversation is being targeted autonomously. Using the same tactics in Maltego, you can explore talks of interests and determine the likelihood they are being influenced or jammed. Don't Miss: I hope you enjoyed this guide to using Maltego to monitor events on Twitter in real time! If you have any questions about this tutorial or Maltego machines, feel free to leave a comment or reach me on Twitter.
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I am known for my strong views on mobile technology, online media, and the effect this has on and communication will have on the public conscious and existing businesses. I've been following this space for over ten years, working with a number of publishers, publications and media companies, some for long periods of time, others for commissions, one-off pieces or a series of articles or shows. As Scotland’s first podcaster, I continue to be a prominent voice in the rise of podcasting and new media online, and picked up a British Academy (BAFTA) nomination for my annual coverage of the Edinburgh Festival Fringe, alongside contributions to Radio 5 Live, the BBC World Service, presenting Edinburgh local radio's coverage of the General Election. You'll find me on Twitter ,. The author is a Forbes contributor.
The opinions expressed are those of the writer. MacBook Pro, mid-2018 (Apple PR) Apple notes that the new butterfly keyboard on the ‘mid-2018 MacBook Pro machines’ retains the same amount of vertical travel’ while providing a quieter typing experience. That makes for great copy and of course, continues to advance the point of Apple’s continual improvements, but there may be a very useful side-effect to the tweak to the keyboard design. The silicone cover over each butterfly switch reduces the chance of any dust getting trapped in the mechanism. – with long-term Apple watcher Jon Gruber calling the butterfly keyboard ‘’ – action to change the construction was to be expected. In fact, the silicone cover technique on show, when the USPTO published an Apple patent for ‘’. The patent talks about Keyboards include mechanisms that prevent and/or alleviate contaminant ingress In other embodiments, a keyboard includes a base; a web that defines apertures; keys moveably coupled to the base within the apertures; and a gasket coupled to the keys, the gasket fixed between the web and the base, operable to block passage of contaminants into the apertures.
Noise On Twitter Another Cover Design For Mac
I can’t see anything about reducing noise levels in this patent, and it looks remarkably close to what has discovered about the changes: Here’s the really good part: I can tell you it’s there, but I can’t definitively prove it’s a reliability fix. After all, “this new third-generation keyboard wasn’t designed to solve those dust issues.” Apple is in the middle of several class-action lawsuits for the failure of their keyboards, so of course they can’t just come out and say, “Hey, we fixed it!” That says there was a problem to begin with. But you’ve heard that clever analysis from already. I’m just here to posit: the advertised boost in quietude is a side-effect of this rubbery membrane. The quiet angle is, quite literally, a cover up. The question now is if this will reduce the number of damaged keyboards in the new machines. And I wonder if any repairs to older MacBook Pro keyboards will incorporate this new technology?
Noise On Twitter Another Cover Design For Mac V19
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