Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/08/the_threat_of_f.html
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/08/influence_opera.html
Influence operations are elusive to define. The Rand Corp.’s definition is as good as any: “the collection of tactical information about an adversary as well as the dissemination of propaganda in pursuit of a competitive advantage over an opponent.” Basically, we know it when we see it, from bots controlled by the Russian Internet Research Agency to Saudi attempts to plant fake stories and manipulate political debate. These operations have been run by Iran against the United States, Russia against Ukraine, China against Taiwan, and probably lots more besides.
Since the 2016 US presidential election, there have been an endless series of ideas about how countries can defend themselves. It’s time to pull those together into a comprehensive approach to defending the public sphere and the institutions of democracy.
Influence operations don’t come out of nowhere. They exploit a series of predictable weaknesses — and fixing those holes should be the first step in fighting them. In cybersecurity, this is known as a “kill chain.” That can work in fighting influence operations, too — laying out the steps of an attack and building the taxonomy of countermeasures.
In an exploratory blog post, I first laid out a straw man information operations kill chain. I started with the seven commandments, or steps, laid out in a 2018 New York Times opinion video series on “Operation Infektion,” a 1980s Russian disinformation campaign. The information landscape has changed since the 1980s, and these operations have changed as well. Based on my own research and feedback from that initial attempt, I have modified those steps to bring them into the present day. I have also changed the name from “information operations” to “influence operations,” because the former is traditionally defined by the US Department of Defense in ways that don’t really suit these sorts of attacks.
Step 1: Find the cracks in the fabric of society — the social, demographic, economic, and ethnic divisions. For campaigns that just try to weaken collective trust in government’s institutions, lots of cracks will do. But for influence operations that are more directly focused on a particular policy outcome, only those related to that issue will be effective.
Countermeasures: There will always be open disagreements in a democratic society, but one defense is to shore up the institutions that make that society possible. Elsewhere I have written about the “common political knowledge” necessary for democracies to function. That shared knowledge has to be strengthened, thereby making it harder to exploit the inevitable cracks. It needs to be made unacceptable — or at least costly — for domestic actors to use these same disinformation techniques in their own rhetoric and political maneuvering, and to highlight and encourage cooperation when politicians honestly work across party lines. The public must learn to become reflexively suspicious of information that makes them angry at fellow citizens. These cracks can’t be entirely sealed, as they emerge from the diversity that makes democracies strong, but they can be made harder to exploit. Much of the work in “norms” falls here, although this is essentially an unfixable problem. This makes the countermeasures in the later steps even more important.
Step 2: Build audiences, either by directly controlling a platform (like RT) or by cultivating relationships with people who will be receptive to those narratives. In 2016, this consisted of creating social media accounts run either by human operatives or automatically by bots, making them seem legitimate, gathering followers. In the years following, this has gotten subtler. As social media companies have gotten better at deleting these accounts, two separate tactics have emerged. The first is microtargeting, where influence accounts join existing social circles and only engage with a few different people. The other is influencer influencing, where these accounts only try to affect a few proxies (see step 6) — either journalists or other influencers — who can carry their message for them.
Countermeasures: This is where social media companies have made all the difference. By allowing groups of like-minded people to find and talk to each other, these companies have given propagandists the ability to find audiences who are receptive to their messages. Social media companies need to detect and delete accounts belonging to propagandists as well as bots and groups run by those propagandists. Troll farms exhibit particular behaviors that the platforms need to be able to recognize. It would be best to delete accounts early, before those accounts have the time to establish themselves.
This might involve normally competitive companies working together, since operations and account names often cross platforms, and cross-platform visibility is an important tool for identifying them. Taking down accounts as early as possible is important, because it takes time to establish the legitimacy and reach of any one account. The NSA and US Cyber Command worked with the FBI and social media companies to take down Russian propaganda accounts during the 2018 midterm elections. It may be necessary to pass laws requiring Internet companies to do this. While many social networking companies have reversed their “we don’t care” attitudes since the 2016 election, there’s no guarantee that they will continue to remove these accounts — especially since their profits depend on engagement and not accuracy.
Step 3: Seed distortion by creating alternative narratives. In the 1980s, this was a single “big lie,” but today it is more about many contradictory alternative truths — a “firehose of falsehood” — that distort the political debate. These can be fake or heavily slanted news stories, extremist blog posts, fake stories on real-looking websites, deepfake videos, and so on.
Countermeasures: Fake news and propaganda are viruses; they spread through otherwise healthy populations. Fake news has to be identified and labeled as such by social media companies and others, including recognizing and identifying manipulated videos known as deepfakes. Facebook is already making moves in this direction. Educators need to teach better digital literacy, as Finland is doing. All of this will help people recognize propaganda campaigns when they occur, so they can inoculate themselves against their effects. This alone cannot solve the problem, as much sharing of fake news is about social signaling, and those who share it care more about how it demonstrates their core beliefs than whether or not it is true. Still, it is part of the solution.
Step 4: Wrap those narratives in kernels of truth. A core of fact makes falsehoods more believable and helps them spread. Releasing stolen emails from Hillary Clinton’s campaign chairman John Podesta and the Democratic National Committee, or documents from Emmanuel Macron’s campaign in France, were both an example of that kernel of truth. Releasing stolen emails with a few deliberate falsehoods embedded among them is an even more effective tactic.
Countermeasures: Defenses involve exposing the untruths and distortions, but this is also complicated to put into practice. Fake news sows confusion just by being there. Psychologists have demonstrated that an inadvertent effect of debunking a piece of fake news is to amplify the message of that debunked story. Hence, it is essential to replace the fake news with accurate narratives that counter the propaganda. That kernel of truth is part of a larger true narrative. The media needs to learn skepticism about the chain of information and to exercise caution in how they approach debunked stories.
Step 5: Conceal your hand. Make it seem as if the stories came from somewhere else.
Countermeasures: Here the answer is attribution, attribution, attribution. The quicker an influence operation can be pinned on an attacker, the easier it is to defend against it. This will require efforts by both the social media platforms and the intelligence community, not just to detect influence operations and expose them but also to be able to attribute attacks. Social media companies need to be more transparent about how their algorithms work and make source publications more obvious for online articles. Even small measures like the Honest Ads Act, requiring transparency in online political ads, will help. Where companies lack business incentives to do this, regulation will be the only answer.
Step 6: Cultivate proxies who believe and amplify the narratives. Traditionally, these people have been called “useful idiots.” Encourage them to take action outside of the Internet, like holding political rallies, and to adopt positions even more extreme than they would otherwise.
Countermeasures: We can mitigate the influence of people who disseminate harmful information, even if they are unaware they are amplifying deliberate propaganda. This does not mean that the government needs to regulate speech; corporate platforms already employ a variety of systems to amplify and diminish particular speakers and messages. Additionally, the antidote to the ignorant people who repeat and amplify propaganda messages is other influencers who respond with the truth — in the words of one report, we must “make the truth louder.” Of course, there will always be true believers for whom no amount of fact-checking or counter-speech will suffice; this is not intended for them. Focus instead on persuading the persuadable.
Step 7: Deny involvement in the propaganda campaign, even if the truth is obvious. Although since one major goal is to convince people that nothing can be trusted, rumors of involvement can be beneficial. The first was Russia’s tactic during the 2016 US presidential election; it employed the second during the 2018 midterm elections.
Countermeasures: When attack attribution relies on secret evidence, it is easy for the attacker to deny involvement. Public attribution of information attacks must be accompanied by convincing evidence. This will be difficult when attribution involves classified intelligence information, but there is no alternative. Trusting the government without evidence, as the NSA’s Rob Joyce recommended in a 2016 talk, is not enough. Governments will have to disclose.
Step 8: Play the long game. Strive for long-term impact over immediate effects. Engage in multiple operations; most won’t be successful, but some will.
Countermeasures: Counterattacks can disrupt the attacker’s ability to maintain influence operations, as US Cyber Command did during the 2018 midterm elections. The NSA’s new policy of “persistent engagement” (see the article by, and interview with, US Cyber Command Commander Paul Nakasone here) is a strategy to achieve this. So are targeted sanctions and indicting individuals involved in these operations. While there is little hope of bringing them to the United States to stand trial, the possibility of not being able to travel internationally for fear of being arrested will lead some people to refuse to do this kind of work. More generally, we need to better encourage both politicians and social media companies to think beyond the next election cycle or quarterly earnings report.
Permeating all of this is the importance of deterrence. Deterring them will require a different theory. It will require, as the political scientist Henry Farrell and I have postulated, thinking of democracy itself as an information system and understanding “Democracy’s Dilemma“: how the very tools of a free and open society can be subverted to attack that society. We need to adjust our theories of deterrence to the realities of the information age and the democratization of attackers. If we can mitigate the effectiveness of influence operations, if we can publicly attribute, if we can respond either diplomatically or otherwise — we can deter these attacks from nation-states.
None of these defensive actions is sufficient on its own. Steps overlap and in some cases can be skipped. Steps can be conducted simultaneously or out of order. A single operation can span multiple targets or be an amalgamation of multiple attacks by multiple actors. Unlike a cyberattack, disrupting will require more than disrupting any particular step. It will require a coordinated effort between government, Internet platforms, the media, and others.
Also, this model is not static, of course. Influence operations have already evolved since the 2016 election and will continue to evolve over time — especially as countermeasures are deployed and attackers figure out how to evade them. We need to be prepared for wholly different kinds of influencer operations during the 2020 US presidential election. The goal of this kill chain is to be general enough to encompass a panoply of tactics but specific enough to illuminate countermeasures. But even if this particular model doesn’t fit every influence operation, it’s important to start somewhere.
Others have worked on similar ideas. Anthony Soules, a former NSA employee who now leads cybersecurity strategy for Amgen, presented this concept at a private event. Clint Watts of the Alliance for Securing Democracy is thinking along these lines as well. The Credibility Coalition’s Misinfosec Working Group proposed a “misinformation pyramid.” The US Justice Department developed a “Malign Foreign Influence Campaign Cycle,” with associated countermeasures.
The threat from influence operations is real and important, and it deserves more study. At the same time, there’s no reason to panic. Just as overly optimistic technologists were wrong that the Internet was the single technology that was going to overthrow dictators and liberate the planet, so pessimists are also probably wrong that it is going to empower dictators and destroy democracy. If we deploy countermeasures across the entire kill chain, we can defend ourselves from these attacks.
But Russian interference in the 2016 presidential election shows not just that such actions are possible but also that they’re surprisingly inexpensive to run. As these tactics continue to be democratized, more people will attempt them. And as more people, and multiple parties, conduct influence operations, they will increasingly be seen as how the game of politics is played in the information age. This means that the line will increasingly blur between influence operations and politics as usual, and that domestic influencers will be using them as part of campaigning. Defending democracy against foreign influence also necessitates making our own political debate healthier.
This essay previously appeared in Foreign Policy.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/06/fake_news_and_p.html
When the next pandemic strikes, we’ll be fighting it on two fronts. The first is the one you immediately think about: understanding the disease, researching a cure and inoculating the population. The second is new, and one you might not have thought much about: fighting the deluge of rumors, misinformation and flat-out lies that will appear on the internet.
The second battle will be like the Russian disinformation campaigns during the 2016 presidential election, only with the addition of a deadly health crisis and possibly without a malicious government actor. But while the two problems — misinformation affecting democracy and misinformation affecting public health — will have similar solutions, the latter is much less political. If we work to solve the pandemic disinformation problem, any solutions are likely to also be applicable to the democracy one.
Pandemics are part of our future. They might be like the 1968 Hong Kong flu, which killed a million people, or the 1918 Spanish flu, which killed over 40 million. Yes, modern medicine makes pandemics less likely and less deadly. But global travel and trade, increased population density, decreased wildlife habitats, and increased animal farming to satisfy a growing and more affluent population have made them more likely. Experts agree that it’s not a matter of if — it’s only a matter of when.
When the next pandemic strikes, accurate information will be just as important as effective treatments. We saw this in 2014, when the Nigerian government managed to contain a subcontinentwide Ebola epidemic to just 20 infections and eight fatalities. Part of that success was because of the ways officials communicated health information to all Nigerians, using government-sponsored videos, social media campaigns and international experts. Without that, the death toll in Lagos, a city of 21 million people, would have probably been greater than the 11,000 the rest of the continent experienced.
There’s every reason to expect misinformation to be rampant during a pandemic. In the early hours and days, information will be scant and rumors will abound. Most of us are not health professionals or scientists. We won’t be able to tell fact from fiction. Even worse, we’ll be scared. Our brains work differently when we are scared, and they latch on to whatever makes us feel safer — even if it’s not true.
Rumors and misinformation could easily overwhelm legitimate news channels, as people share tweets, images and videos. Much of it will be well-intentioned but wrong — like the misinformation spread by the anti-vaccination community today – but some of it may be malicious. In the 1980s, the KGB ran a sophisticated disinformation campaign – Operation Infektion – to spread the rumor that HIV/AIDS was a result of an American biological weapon gone awry. It’s reasonable to assume some group or country would deliberately spread intentional lies in an attempt to increase death and chaos.
It’s not just misinformation about which treatments work (and are safe), and which treatments don’t work (and are unsafe). Misinformation can affect society’s ability to deal with a pandemic at many different levels. Right now, Ebola relief efforts in the Democratic Republic of Congo are being stymied by mistrust of health workers and government officials.
It doesn’t take much to imagine how this can lead to disaster. Jay Walker, curator of the TEDMED conferences, laid out some of the possibilities in a 2016 essay: people overwhelming and even looting pharmacies trying to get some drug that is irrelevant or nonexistent, people needlessly fleeing cities and leaving them paralyzed, health workers not showing up for work, truck drivers and other essential people being afraid to enter infected areas, official sites like CDC.gov being hacked and discredited. This kind of thing can magnify the health effects of a pandemic many times over, and in extreme cases could lead to a total societal collapse.
This is going to be something that government health organizations, medical professionals, social media companies and the traditional media are going to have to work out together. There isn’t any single solution; it will require many different interventions that will all need to work together. The interventions will look a lot like what we’re already talking about with regard to government-run and other information influence campaigns that target our democratic processes: methods of visibly identifying false stories, the identification and deletion of fake posts and accounts, ways to promote official and accurate news, and so on. At the scale these are needed, they will have to be done automatically and in real time.
Since the 2016 presidential election, we have been talking about propaganda campaigns, and about how social media amplifies fake news and allows damaging messages to spread easily. It’s a hard discussion to have in today’s hyperpolarized political climate. After any election, the winning side has every incentive to downplay the role of fake news.
But pandemics are different; there’s no political constituency in favor of people dying because of misinformation. Google doesn’t want the results of peoples’ well-intentioned searches to lead to fatalities. Facebook and Twitter don’t want people on their platforms sharing misinformation that will result in either individual or mass deaths. Focusing on pandemics gives us an apolitical way to collectively approach the general problem of misinformation and fake news. And any solutions for pandemics are likely to also be applicable to the more general – and more political – problems.
Pandemics are inevitable. Bioterror is already possible, and will only get easier as the requisite technologies become cheaper and more common. We’re experiencing the largest measles outbreak in 25 years thanks to the anti-vaccination movement, which has hijacked social media to amplify its messages; we seem unable to beat back the disinformation and pseudoscience surrounding the vaccine. Those same forces will dramatically increase death and social upheaval in the event of a pandemic.
Let the Russian propaganda attacks on the 2016 election serve as a wake-up call for this and other threats. We need to solve the problem of misinformation during pandemics together – governments and industries in collaboration with medical officials, all across the world – before there’s a crisis. And the solutions will also help us shore up our democracy in the process.
This essay previously appeared in the New York Times.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/05/fraudulent_acad.html
The term “fake news” has lost much of its meaning, but it describes a real and dangerous Internet trend. Because it’s hard for many people to differentiate a real news site from a fraudulent one, they can be hoodwinked by fictitious news stories pretending to be real. The result is that otherwise reasonable people believe lies.
The trends fostering fake news are more general, though, and we need to start thinking about how it could affect different areas of our lives. In particular, I worry about how it will affect academia. In addition to fake news, I worry about fake research.
An example of this seems to have happened recently in the cryptography field. SIMON is a block cipher designed by the National Security Agency (NSA) and made public in 2013. It’s a general design optimized for hardware implementation, with a variety of block sizes and key lengths. Academic cryptanalysts have been trying to break the cipher since then, with some pretty good results, although the NSA’s specified parameters are still immune to attack. Last week, a paper appeared on the International Association for Cryptologic Research (IACR) ePrint archive purporting to demonstrate a much more effective break of SIMON, one that would affect actual implementations. The paper was sufficiently weird, the authors sufficiently unknown and the details of the attack sufficiently absent, that the editors took it down a few days later. No harm done in the end.
In recent years, there has been a push to speed up the process of disseminating research results. Instead of the laborious process of academic publication, researchers have turned to faster online publishing processes, preprint servers, and simply posting research results. The IACR ePrint archive is one of those alternatives. This has all sorts of benefits, but one of the casualties is the process of peer review. As flawed as that process is, it does help ensure the accuracy of results. (Of course, bad papers can still make it through the process. We’re still dealing with the aftermath of a flawed, and now retracted, Lancet paper linking vaccines with autism.)
Like the news business, academic publishing is subject to abuse. We can only speculate the motivations of the three people who are listed as authors on the SIMON paper, but you can easily imagine better-executed and more nefarious scenarios. In a world of competitive research, one group might publish a fake result to throw other researchers off the trail. It might be a company trying to gain an advantage over a potential competitor, or even a country trying to gain an advantage over another country.
Reverting to a slower and more accurate system isn’t the answer; the world is just moving too fast for that. We need to recognize that fictitious research results can now easily be injected into our academic publication system, and tune our skepticism meters accordingly.
This essay previously appeared on Lawfare.com.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/04/defending_democ.html
To better understand influence attacks, we proposed an approach that models democracy itself as an information system and explains how democracies are vulnerable to certain forms of information attacks that autocracies naturally resist. Our model combines ideas from both international security and computer security, avoiding the limitations of both in explaining how influence attacks may damage democracy as a whole.
Our initial account is necessarily limited. Building a truly comprehensive understanding of democracy as an information system will be a Herculean labor, involving the collective endeavors of political scientists and theorists, computer scientists, scholars of complexity, and others.
In this short paper, we undertake a more modest task: providing policy advice to improve the resilience of democracy against these attacks. Specifically, we can show how policy makers not only need to think about how to strengthen systems against attacks, but also need to consider how these efforts intersect with public beliefs — or common political knowledge — about these systems, since public beliefs may themselves be an important vector for attacks.
In democracies, many important political decisions are taken by ordinary citizens (typically, in electoral democracies, by voting for political representatives). This means that citizens need to have some shared understandings about their political system, and that the society needs some means of generating shared information regarding who their citizens are and what they want. We call this common political knowledge, and it is largely generated through mechanisms of social aggregation (and the institutions that implement them), such as voting, censuses, and the like. These are imperfect mechanisms, but essential to the proper functioning of democracy. They are often compromised or non-existent in autocratic regimes, since they are potentially threatening to the rulers.
In modern democracies, the most important such mechanism is voting, which aggregates citizens’ choices over competing parties and politicians to determine who is to control executive power for a limited period. Another important mechanism is the census process, which play an important role in the US and in other democracies, in providing broad information about the population, in shaping the electoral system (through the allocation of seats in the House of Representatives), and in policy making (through the allocation of government spending and resources). Of lesser import are public commenting processes, through which individuals and interest groups can comment on significant public policy and regulatory decisions.
All of these systems are vulnerable to attack. Elections are vulnerable to a variety of illegal manipulations, including vote rigging. However, many kinds of manipulation are currently legal in the US, including many forms of gerrymandering, gimmicking voting time, allocating polling booths and resources so as to advantage or disadvantage particular populations, imposing onerous registration and identity requirements, and so on.
Censuses may be manipulated through the provision of bogus information or, more plausibly, through the skewing of policy or resources so that some populations are undercounted. Many of the political battles over the census over the past few decades have been waged over whether the census should undertake statistical measures to counter undersampling bias for populations who are statistically less likely to return census forms, such as minorities and undocumented immigrants. Current efforts to include a question about immigration status may make it less likely that undocumented or recent immigrants will return completed forms.
Finally, public commenting systems too are vulnerable to attacks intended to misrepresent the support for or opposition to specific proposals, including the formation of astroturf (artificial grassroots) groups and the misuse of fake or stolen identities in large-scale mail, fax, email or online commenting systems.
All these attacks are relatively well understood, even if policy choices might be improved by a better understanding of their relationship to shared political knowledge. For example, some voting ID requirements are rationalized through appeals to security concerns about voter fraud. While political scientists have suggested that these concerns are largely unwarranted, we currently lack a framework for evaluating the trade-offs, if any. Computer security concepts such as confidentiality, integrity, and availability could be combined with findings from political science and political theory to provide such a framework.
Even so, the relationship between social aggregation institutions and public beliefs is far less well understood by policy makers. Even when social aggregation mechanisms and institutions are robust against direct attacks, they may be vulnerable to more indirect attacks aimed at destabilizing public beliefs about them.
Democratic societies are vulnerable to (at least) two kinds of knowledge attacks that autocratic societies are not. First are flooding attacks that create confusion among citizens about what other citizens believe, making it far more difficult for them to organize among themselves. Second are confidence attacks. These attempt to undermine public confidence in the institutions of social aggregation, so that their results are no longer broadly accepted as legitimate representations of the citizenry.
Most obviously, democracies will function poorly when citizens do not believe that voting is fair. This makes democracies vulnerable to attacks aimed at destabilizing public confidence in voting institutions. For example, some of Russia’s hacking efforts against the 2016 presidential election were designed to undermine citizens’ confidence in the result. Russian hacking attacks against Ukraine, which targeted the systems through which election results were reported out, were intended to create confusion among voters about what the outcome actually was. Similarly, the “Guccifer 2.0” hacking identity, which has been attributed to Russian military intelligence, sought to suggest that the US electoral system had been compromised by the Democrats in the days immediately before the presidential vote. If, as expected, Donald Trump had lost the election, these claims could have been combined with the actual evidence of hacking to create the appearance that the election was fundamentally compromised.
Similar attacks against the perception of fairness are likely to be employed against the 2020 US census. Should efforts to include a citizenship question fail, some political actors who are disadvantaged by demographic changes such as increases in foreign-born residents and population shift from rural to urban and suburban areas will mount an effort to delegitimize the census results. Again, the genuine problems with the census, which include not only the citizenship question controversy but also serious underfunding, may help to bolster these efforts.
Mechanisms that allow interested actors and ordinary members of the public to comment on proposed policies are similarly vulnerable. For example, the Federal Communication Commission (FCC) announced in 2017 that it was proposing to repeal its net neutrality ruling. Interest groups backing the FCC rollback correctly anticipated a widespread backlash from a politically active coalition of net neutrality supporters. The result was warfare through public commenting. More than 22 million comments were filed, most of which appeared to be either automatically generated or form letters. Millions of these comments were apparently fake, and attached unsuspecting people’s names and email addresses to comments supporting the FCC’s repeal efforts. The vast majority of comments that were not either form letters or automatically generated opposed the FCC’s proposed ruling. The furor around the commenting process was magnified by claims from inside the FCC (later discredited) that the commenting process had also been subjected to a cyberattack.
We do not yet know the identity and motives of the actors behind the flood of fake comments, although the New York State Attorney-General’s office has issued subpoenas for records from a variety of lobbying and advocacy organizations. However, by demonstrating that the commenting process was readily manipulated, the attack made it less likely that the apparently genuine comments of those opposing the FCC’s proposed ruling would be treated as useful evidence of what the public believed. The furor over purported cyberattacks, and the FCC’s unwillingness itself to investigate the attack, have further undermined confidence in an online commenting system that was intended to make the FCC more open to the US public.
We do not know nearly enough about how democracies function as information systems. Generating a better understanding is itself a major policy challenge, which will require substantial resources and, even more importantly, common understandings and shared efforts across a variety of fields of knowledge that currently don’t really engage with each other.
However, even this basic sketch of democracy’s informational aspects can provide policy makers with some key lessons. The most important is that it may be as important to bolster shared public beliefs about key institutions such as voting, public commenting, and census taking against attack, as to bolster the mechanisms and related institutions themselves.
Specifically, many efforts to mitigate attacks against democratic systems begin with spreading public awareness and alarm about their vulnerabilities. This has the benefit of increasing awareness about real problems, but it may especially if exaggerated for effect damage public confidence in the very social aggregation institutions it means to protect. This may mean, for example, that public awareness efforts about Russian hacking that are based on flawed analytic techniques may themselves damage democracy by exaggerating the consequences of attacks.
More generally, this poses important challenges for policy efforts to secure social aggregation institutions against attacks. How can one best secure the systems themselves without damaging public confidence in them? At a minimum, successful policy measures will not simply identify problems in existing systems, but provide practicable, publicly visible, and readily understandable solutions to mitigate them.
We have focused on the problem of confidence attacks in this short essay, because they are both more poorly understood and more profound than flooding attacks. Given historical experience, democracy can probably survive some amount of disinformation about citizens’ beliefs better than it can survive attacks aimed at its core institutions of aggregation. Policy makers need a better understanding of the relationship between political institutions and social beliefs: specifically, the importance of the social aggregation institutions that allow democracies to understand themselves.
There are some low-hanging fruit. Very often, hardening these institutions against attacks on their confidence will go hand in hand with hardening them against attacks more generally. Thus, for example, reforms to voting that require permanent paper ballots and random auditing would not only better secure voting against manipulation, but would have moderately beneficial consequences for public beliefs too.
There are likely broadly similar solutions for public commenting systems. Here, the informational trade-offs are less profound than for voting, since there is no need to balance the requirement for anonymity (so that no-one can tell who voted for who ex post) against other requirements (to ensure that no-one votes twice or more, no votes are changed and so on). Instead, the balance to be struck is between general ease of access and security, making it easier, for example, to leverage secondary sources to validate identity.
Both the robustness of and public confidence in the US census and the other statistical systems that guide the allocation of resources could be improved by insulating them better from political control. For example, a similar system could be used to appoint the director of the census to that for the US Comptroller-General, requiring bipartisan agreement for appointment, and making it hard to exert post-appointment pressure on the official.
Our arguments also illustrate how some well-intentioned efforts to combat social influence operations may have perverse consequences for general social beliefs. The perception of security is at least as important as the reality of security, and any defenses against information attacks need to address both.
However, we need far better developed intellectual tools if we are to properly understand the trade-offs, instead of proposing clearly beneficial policies, and avoiding straightforward mistakes. Forging such tools will require computer security specialists to start thinking systematically about public beliefs as an integral part of the systems that they seek to defend. It will mean that more military oriented cybersecurity specialists need to think deeply about the functioning of democracy and the capacity of internal as well as external actors to disrupt it, rather than reaching for their standard toolkit of state-level deterrence tools. Finally, specialists in the workings of democracy have to learn how to think about democracy and its trade-offs in specifically informational terms.
This essay was written with Henry Farrell, and has previously appeared on Defusing Disinfo.