DIFFERENT STRATEGIES TO safeguard AGAINST DEEPFAKES

Concurrently with the legal framework, public and private organisations get organised to put forward solutions allowing to detect and prevent the malicious spread of deepfakes. We can distinguish four strategies to safeguard against deepfakes.

1/ Detecting the imperfections

Detecting the deepfakes by their imperfections is one of the main existing methods. Some irregularities remain in the generated contents, such as the lack of blinks and of synchronisation between the lips and the voice, distortions of the face and accessories (arms of the glasses), or the inaccuracy of the context (weather, location).

The deepfakes are however built to learn from their mistakes and generate a content that is increasingly alike the original, making the imperfections less perceptible. The tools using this deepfake detection strategy can be effective but require a constant improvement to detect ever more subtle anomalies.

We can cite in this category Assembler, a tool intended for journalists developed by Jigsaw (branch of Alphabet, parent company of Google). It enables to verify the authenticity of contents through their analysis via five detectors, amongst which the detection of anomalies of patterns and colours, of copied and pasted areas, and of known characteristics of deepfakes algorithms.

2/ Screening and comparative analysis

Comparing the contents with a database of authentic content or by looking for similar content on search engines to see whether they have been manipulated (for instance, by finding the same video with a different face) is another strategy allowing to pre-empt deepfakes.

In 2020, the AI Foundation should make available a plugin, Reality Defender, to integrate to web browsers and over time to social networks. It will allow the detection of manipulations of contents, targeting first the politicians. Users will be led to adjust the sensitivity of this tool, according to the manipulations they will want to detect or not, not to be notified for every manipulation of content, notably for the most ordinary manipulations (photo retouch on a web page done on Photoshop for example).

3/ Watermarking

A third method consists in marking the contents with a watermark, or digital tattoo, to facilitate the authentication process by filling in their source and following the manipulations undertaken on these contents.

A team from the New York University works on a research project to create a camera embedding a watermarking technology meant to mark the photographed contents, in order not only to authenticate the original photography, but also to mark and follow all the manipulations carried out on it throughout its lifecycle.

4/ Involving the human factor

Involving the users in the detection process allows both mitigating deepfakes’ impacts by making them realise that the alteration of the acceded contents is possible, and to reduce deepfakes’ occurrence by allowing them to report the ones they suspect.

The plugin Reality Defender already mentioned will give users the possibility to report the contents they judge as fake so as to inform the other users – which once added to the analysis realised by the tool, will be able to see if the contents have been reported by other users, offering a second level of indication.

Some initiatives carried by cooperation of cross-sector actors combine these four strategies for a maximal efficiency against deepfakes. Some are already used or tested by journalists. It is the case of InVID, initiative developed within the scope of the European Union Horizon 2020 program of financing of research and innovation, used by the French press agency (AFP).

Solutions and strategies are therefore emerging, the market is developing, and new innovative solutions should appear very shortly with the results of the Deepfake Detection Challenge. This contest anti-deepfake was launched by Facebook upon the approach of the American presidential election, and more than 2,600 teams signed up. Results the 22^nd of April!

Below a table presenting examples of initiatives combining different strategies to safeguard against deepfakes.

Different means to protect one’s activity

The risk deepfakes present for businesses is genuine, and a few actions can be taken to protect one’s activity and mitigate its impacts from now on.

• Estimating the exposure: The use cases of deepfakes and the worst-case scenario of their use must be determined on the perimeters of the company, taking the fraud and undermining risks into consideration, and identifying the appropriate security strategies.

• Raising awareness: The collaborators must be made aware of the detection of deepfakes (to avoid the cases of fraud) but also of the limitation of shared contents on social media that can be reused to create deepfakes (to avoid the undermining). Just like anti-phishing campaigns, this awareness campaign focuses both on the detection of technical faults (form) of the deepfakes (although they will be led to disappear with the improvement of techniques), but mostly on the detection of the suspicious nature of information (content), encouraging the audience’s suspicion, cross checking of information and notification of the suspicions to the appropriate teams (what to do if I see a suspect video of my head of communications on the social networks during the weekend? What to do if I receive a vocal message of my chief asking me to execute a punctual operation that is slightly out of my perimeter?).

• Adapting the verification processes: The existing anti-fraud plans can be redesigned to be applied to deepfakes. For instance, for a Fake President fraud via deepfakes, one of the recommendations is to suggest to the interlocutor to hang up and call him back (if possible on a known number, and after an internal check). For the most sensitive fraud scenarios, these reaction processes must be finely defined, and the concerned collaborators regularly trained to the reflexes to adopt. Tools such as the ones defined earlier can also be used to verify all or any part of the media used by the collaborators.

• Protect the contents: The contents representing collaborators shared internally or externally by the company can be controlled to avoid them being reused to generate deepfakes. Businesses can limit the diversity (angle of the people and types of media) of the data potentially usable by malicious actors, and play on the digital quality (definition) of the shared contents. In fact, the more the malicious actors benefit from diverse and good quality contents representing the collaborators, the more it facilitates their reuse to generate deepfakes. Moreover, businesses can limit their means of communication to an official channel, verified social networks and their official websites – which creates contents’ consumer habits for the audience, that will be suspicious of all diffusion out of these habits.

• Anticipate the crises: The communications requirements in the case of a proven incident linked to deepfakes must be anticipated, and the management of the deepfake case must include the “generic” communications scenarios addressed in the crisis communication plans.

Cet article Deep dive into deepfake – How to face increasingly believable fake news? (2/2) est apparu en premier sur RiskInsight.

The recent events linked to the COVID-19 outbreak have proven the necessity of acceding to reliable and true news for all the society. More than the epidemic, we have witnessed an « infodemic », rapid spread of false or misleading information on the social networks, raising the question of the trust given to the platforms relaying the news and of the authenticity of the information they pass on.

The use of deepfakes is a topical phenomenon affecting firstly the general public. It is inherently linked to the importance gained by the social and online media in our daily life.

In September 2019, we counted near 15,000 deepfake videos online, twice more than in December 2018. If 96% of these videos were pornographic deepfakes posted on specialised websites, the extent of the affected topics has however increased to reach all the famous social networks (YouTube, Vimeo, Dailymotion).  Amongst the deepfakes posted on YouTube, 20% already represented politicians, business owners and journalists[1]. Their disinformation power on the general public allows them to influence major political and societal events from the moment they star famous personalities.

Deepfakes keep getting better, while the tools to generate them become more accessible (such as Lyrebird, for the audio deepfakes, Zao, for face-swapping, and the most recent one, Avatarify, integrated to Zoom and Skype, for the video). Their harmful power weighs more and more not only on public actors and organisations, but also on private ones, and must be taken into account in every business sector.

A RISK WORTH CONSIDERING FOR BUSINESSES

Deepfakes can also be used against businesses. They offer a new playground for malicious actors, particularly through two means of action:

• The improvement of Fake president frauds, whose impacts and probability are increased by deepfakes. The fraud becomes more credible thanks to photos, videos and audios copying the person who is impersonated. The targeted collaborators therefore consider these contents as an authentication in itself of the interlocutor, and the chances of successful attacks are increased – which is an incentive to ask for larger sums. Besides, the tools to generate deepfakes being accessible to the large public, the use of these frauds by malicious people increases.
• The undermining of the business through relayed false information can strongly damage its image, leading to a certain number of consequences, notably financial and legal. We can wonder what would be the impacts of an ExCom member’s video speech sharing fake results or strategic orientations on the price of his firm’s share or on the trust of its prospects; or those of the disclosure of a product anomaly on the direct order intake. Moreover, denying the rumours is harder when deepfakes are used. Today, many businesses still feel afar from the subject: How many have already wondered what would the impacts of a deepfake be on their activities?

A legal framework IN PROGRESS

The states start putting together an answer to the deepfake concern and legislating to regulate their diffusion. Some countries such as China criminalise the diffusion of deepfakes without notifying the audience about it (since the 1^st of January 2020). In the United States, the treatment of the deepfakes’ question is speeding up as the presidential election of November 2020 approaches, and it is dealt with both at the federal level (bills prohibiting the diffusion of deepfakes in California, Virginia and Texas) and at the national one (the DEEPFAKE Accountability Act[2]  is being discussed by the Congress to “combat the spread of disinformation through restrictions on deep-fake video alteration technology”). In France, the question of deepfakes is included in the law of the 22^nd of December 2019, related to the fight against the manipulation of information – and is therefore not dealt with specifically.

These legal frameworks remain dawning and heterogeneous, and only represent one part of the answer to provide to this technology. More than condemning their malicious use, the issue is mostly to be able to detect and avoid them.

In this first part, we have given an overview of the risks presented by deepfakes for the businesses. In the second part of the article, we will focus on the technical and organisational means available today to safeguard oneself.

[1] Study published by Deeptrace in September 2019.

[2] Defending Each and Every Person from False Appearances by Keeping Exploitation Subject to Accountability Act.

Cet article Deep dive into deepfake – How to face increasingly believable fake news? (1/2) est apparu en premier sur RiskInsight.