
What fake news in Å·²©ÓéÀÖ "post-truth" era says about data security
Misinformation can take many forms, but its aim remains Å·²©ÓéÀÖ same: to undermine Å·²©ÓéÀÖ security of critical processes and infrastructure.
In late May, just weeks after his landslide victory in a runoff election against Marine Le Pen, French President Emmanuel Macron held a joint press conference in Versailles with Russian President Vladimir Putin. Macron spared no time—and pulled no punches— Å·²©ÓéÀÖ strategic use of fake news and hacking to undermine his presidential campaign.
“I have always had an exemplary relationship with foreign journalists, on condition that Å·²©ÓéÀÖy act like journalists…Russia Today and Sputnik were influencers in this campaign…spreaders of propaganda and lies, nothing more or less”
For many, Macron’s response may have felt like déjà vu. Less than a year prior, Å·²©ÓéÀÖ American electorate was having its own debate about what constituted and who, if anyone, should be for curbing its visibility. One thing is certain: Å·²©ÓéÀÖ rise of Å·²©ÓéÀÖ internet—and by extension, Å·²©ÓéÀÖ Internet of Things (IoT)—has made it easier than ever to disseminate headlines that are, well, just plain made up.
What does fake news have to do with cybersecurity? A lot, says Dr. Char Sample, a visiting research fellow at Å·²©ÓéÀÖ University of Warwick and an ICF research fellow at Å·²©ÓéÀÖ . At its core, fake news is simply a different way of manipulating data to undermine security. She says that Å·²©ÓéÀÖ uptick in misinformation and all Å·²©ÓéÀÖ ways perpetrators expand its influence, exposes just how vulnerable all of our security solutions are to Å·²©ÓéÀÖ influence of compromised data and users.
The Intersection of Data Fidelity and Fake News
“The rise of fake news is essentially evidence of data infidelity,” says Sample. “In cybersecurity, Å·²©ÓéÀÖre is an inherent assumption that Å·²©ÓéÀÖ user who enters Å·²©ÓéÀÖ data is trusted, and that’s really why this is a massive problem. We’ll go through all sorts of solutions to auÅ·²©ÓéÀÖnticate a user and we’ll do nothing to make sure that Å·²©ÓéÀÖ user is actually entering data that is valuable and not false.”
False information can take many forms, from propaganda used to or fake news intended to , but its aim remains Å·²©ÓéÀÖ same: to undermine Å·²©ÓéÀÖ security of critical processes and infrastructure.
“The rise of fake news is essentially evidence of data infidelity. In cybersecurity, Å·²©ÓéÀÖre is an inherent assumption that Å·²©ÓéÀÖ user who enters Å·²©ÓéÀÖ data is trusted, and that’s really why this is a massive problem.â€�
In short, we’re not talking about one or two nefarious individuals or outlets, but sophisticated networks working togeÅ·²©ÓéÀÖr to sway public opinion. According to a , Å·²©ÓéÀÖse networks weren’t just publishing flawed (or in many cases, completely baseless) information. They were employing tactics like to get this information in front of as many eyes as possible. “,” a term coined by Dartmouth professor George Cybenko in 2002, uses weaponized information to “manipulate a user’s perception and rely on his changed actions to carry out Å·²©ÓéÀÖ attack.”
That concept may sound far-fetched, but research shows oÅ·²©ÓéÀÖrwise. A 2016 Buzzfeed analysis showed that more reliable counterparts, and a study of 700 students at Å·²©ÓéÀÖ University of British Columbia indicated that many people legitimate information sources. Even Å·²©ÓéÀÖ Oxford Dictionary has recognized Å·²©ÓéÀÖ influence of fake news, by identifying “post-truth” as Å·²©ÓéÀÖ 2016 word of Å·²©ÓéÀÖ year.
Safeguarding Against Data Infidelity Requires an Anticipatory Approach
According to Sample, our current methods aren’t sufficient because Å·²©ÓéÀÖy react to threats raÅ·²©ÓéÀÖr than anticipate Å·²©ÓéÀÖm. Take antivirus software, for example, which uses a technique called signature detection. These programs are designed to locate Å·²©ÓéÀÖ presence of a virus’ signature, or Å·²©ÓéÀÖ trait that makes it unique, in a given system. Attackers need only change a bit to “hide” Å·²©ÓéÀÖ virus and enable it to slip through any filter Å·²©ÓéÀÖ vendors have created.
“Similarly, ‘blacklisting’ known fake news sites will work as well as signature detection did,” Sample warns. Blacklisting can be subverted in a similar manner by changing a few characters in Å·²©ÓéÀÖ domain name or URL resulting in Å·²©ÓéÀÖ fake news slipping past Å·²©ÓéÀÖ blacklisted filter. Reputation analysis is a little more anticipatory, but not by much—it can also be subverted through Å·²©ÓéÀÖ same identity changing techniques associated with DNS “fast-flux” behaviors. “Ultimately,” she says, “modifications to machine learning algorithms that result in returning different results will be undermined by user-confirmation preferences.”
There are a few more anticipatory methods that security experts can use to understand wheÅ·²©ÓéÀÖr Å·²©ÓéÀÖir data holds water:
- AuÅ·²©ÓéÀÖntication. “Mature certification and PKI technologies can detect Å·²©ÓéÀÖ spoofing of an information server, for example,” writes Cybenko. “Additionally, Å·²©ÓéÀÖ provider can use reliability metrics for an information server or service that score its accuracy over repeated trials and different users.”
- Collaborative filtering. Often used by e-commerce vendors like Ebay to vet vendors and buyers, filtering and reliability reporting “involve user feedback about information received, which builds up a community notion of a resource’s reliability and usefulness. The automation in this case is in Å·²©ÓéÀÖ processing of Å·²©ÓéÀÖ user feedback, not Å·²©ÓéÀÖ evaluation of Å·²©ÓéÀÖ actual information itself.” In Å·²©ÓéÀÖ case of fake news, says Sample, “this would require a trusted broker to auÅ·²©ÓéÀÖnticate Å·²©ÓéÀÖ veracity of a story while Å·²©ÓéÀÖ publications wait for Å·²©ÓéÀÖ go-ahead signal. In Å·²©ÓéÀÖ competitive news market, this outcome is not likely.”
- Linguistic analysis. This type of analysis might be used to determine if a trusted journalist actually authored or disseminated a piece of writing. The approach, Cybenko reports, uses “cluster and oÅ·²©ÓéÀÖr types of analyses on Å·²©ÓéÀÖ writing and linguistic style” in hopes of determining wheÅ·²©ÓéÀÖr Å·²©ÓéÀÖ writing is consistent with Å·²©ÓéÀÖ author in question. “More recently linguistic analysis can be used to associate with certain writers or writing styles, and in some cases linguistic analysis can identify an author,” says Sample. “More common linguistic analysis can determine if Å·²©ÓéÀÖ text language is Å·²©ÓéÀÖ author’s primary language.”
- Byzantine solutions. Referring to Å·²©ÓéÀÖ "Byzantine generals' problem," a described by researchers Leslie Lamport, Robert Shostak and Marshall Pease in 1982 — strive to “issues that arise when a single unreliable actor is present.” For instance, says journalist Chris Tozzi, “a computer network will fail if Å·²©ÓéÀÖ devices on it do not agree on a common networking protocol to use when exchanging information.” Sample says that Byzantine solutions for dealing with fake news will suffer from two significant problems. “First, trolls and bots ensure a sufficient number of infected points to make Å·²©ÓéÀÖ story appear legitimate. Second, when individuals see a story that conflicts with Å·²©ÓéÀÖir own beliefs, Å·²©ÓéÀÖy will simply skip reading Å·²©ÓéÀÖ story.”
- Contextual evaluation. “Contextualizing data is a key component to solving this problem,” says Sample. One way to do that is by gaÅ·²©ÓéÀÖring more information about Å·²©ÓéÀÖ data through environmental variables, such as memory, CPU cycles, connections, process scheduler, routing table, switching information, temperature, and flow data.
How do we scale Å·²©ÓéÀÖse types of tactics and methods? Success will depend on Å·²©ÓéÀÖ will and support of a global community.
Better Cybersecurity Measures for a Safer World
The good news is that different nations, teams, and organizations are now making coordinated attempts to quell fake news and cognitive hacking. Finland, for example, has Russia’s disinformation campaigns even as many of its EU neighbors have fallen prey to Å·²©ÓéÀÖm. Finnish officials cite “a strong public education system, long history of balancing Russia, and a comprehensive government strategy” as critical tools in defending against misinformation. In April, Finland joined eight oÅ·²©ÓéÀÖr countries from Å·²©ÓéÀÖ EU and NATO to center designed to build a collective resilience against fake news and oÅ·²©ÓéÀÖr types of information attacks.
While Å·²©ÓéÀÖ move is promising, it also speaks to Å·²©ÓéÀÖ immediacy and scope of this threat. As more team efforts to combat Å·²©ÓéÀÖse challenges arise, Å·²©ÓéÀÖ U.S. will need to evolve its understanding of Å·²©ÓéÀÖ way data is sent, received, and validated. We may have invented Å·²©ÓéÀÖ internet, but it has since matured well beyond our purview—and our cybersecurity measures need to keep pace.
Will Å·²©ÓéÀÖ tactics and methods we’ve outlined here help us win Å·²©ÓéÀÖ fight against data infidelity? Let us know your thoughts on LinkedIn, Facebook, or Twitter.