Sécurité des données Enjeux liés à l'internet des objets et à l'intelligence artificielle
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Thierry Matusiak
Architecte Division Sécurité IBM
Membre actif du CLUSIF
thierry_matusiak@fr.ibm.com
LinkedIn : https://fr.linkedin.com/in/thierrymatusiak
Sécurité des données
Enjeux liés à l'internet des objets et à l'intelligence artificielle
Sécurité des données Travaux du CLUSIF Internet des objets Intelligence artificielle
Club de la sécurité de l’information français
Présentation du CLUSIF
➢ Association de professionnels de la sécurité de l’information
Lieu d’échange pour ses 700 membres, permettant de mettre en commun expertises
et réflexions au service d’une SSI efficace
➢ Les activités de l’association
• des groupes et Espaces de Travail
• des publications
• des conférences thématiques
• des ateliers fournisseurs sur le grill
• un exercice de Cyber-Crise (ECRANS)
Pour plus d’information : clusif@clusif.fr
Club de la sécurité de l’information français
A propos des GTs
➢ GT GDPR
➢ GT IoT
➢ GT Sécurité des systèmes industriels
➢ Pas de GT "sécurité de l'IA"
➢ Sujet d'innovation
➢ Lancement de "l'invité du CLUSIF" pour aborder ces sujets prospectifs
➢ Pas de GT "sécurité des données"
➢ Probablement parce que le sujet est très (trop) vaste
➢ Mais c'est un sujet récurrent, par exemple sur l'anonymisation des données
Club de la sécurité de l’information français
Zoom sur le GT GDPR
➢ "RSSI & DPO"
➢ Des profils très différents : juristes, CIL, RSSI, fournisseurs de solutions
➢ Infographie publiée début 2018 (Fr : 50000+ vues, En : 7000+ vues)
➢ Augmentation des fuites de données communiquées
➢ Probablement parce que ca devient une obligation légale
➢ Risque de banalisation. Qui a entendu parler de la fuite Adidas par exemple ?
➢ Les amendes de la CNIL restent modérées
➢ Priorités de la CNIL
➢ La première règle est que vous devriez être conformes avec les règles de 1978
➢ 3 secteurs sont dans le viseur en 2018: logement, emploi et stationnement
Sécurité des données Travaux du CLUSIF Internet des objets Intelligence artificielle
Club de la sécurité de l’information français
Groupe de travail IoT
• Le premier problème est de définir de quoi on parle
• IoT grand public
• IIoT / SCADA (qui a son propre GT)
• L'IoT introduit des nouvelles classes de risques
• Vies humaines mises en danger
• Risque systémique
• Toutes les entreprises sont clientes, au moins à travers :
• La gestion de leurs bâtiments
• Le shadowIoT importé par leurs employés
• Données IoT
• Big Data
• Enjeux de privacy forts car ce sont souvent des données personnelles ou sensibles
• Besoin de réglementation pour réguler le secteur - sujet d'actualité
Club de la sécurité de l’information français
Cas concrets
Exposition de données : Strava / Polar
https://www.theguardian.com/world/2018/jan/28/fitness-tracking-app-gives-away-location-of-secret-us-army-bases
https://www.bellingcat.com/resources/articles/2018/07/08/strava-polar-revealing-homes-soldiers-spies/
Détournement et surveillance : Enceintes connectées
https://www.theguardian.com/technology/2018/feb/14/amazon-alexa-ad-avoids-ban-after-viewer-complaint-ordered-cat-food
Mauvaise sécurité générale : Jouets
https://www.cnil.fr/fr/jouets-connectes-mise-en-demeure-publique-pour-atteinte-grave-la-vie-privee-en-raison-dun-defaut-de
Sécurité des données >> sécurité de l'objet (exemple : vol de voiture)
https://www.wired.com/story/hackers-steal-tesla-model-s-seconds-key-fob/
Club de la sécurité de l’information français
Quelques constats et recommandations
1. Les objets vont probablement fonctionner dans un environnement hostile
2. Leur niveau de sécurité diminue avec le temps
3. Un secret initial ou partagé entre objets n'est pas un vrai secret
4. Si la configuration initiale est faible, elle le restera
5. Le risque de fuite grossit avec le volume des données qui s'accumulent
https://www-01.ibm.com/common/ssi/cgi-bin/ssialias?htmlfid=SEF03018USEN
Sécurité des données Travaux du CLUSIF Internet des objets Intelligence artificielle
IoT + Cognitive = Actionable AI
AI security extends the perimeter – where no one has gone before
https://www.businessinsider.de/cambridge-analytica-could-rebrand-emerdata-2018-5?r=US&IR=T
/
• Political Security
̶ Mass surveillance
̶ Data & people manipulation
https://www.theatlantic.com/technology/archive/2014/07/makeup/374929
• Physical Security https://www.wired.com/story/hackers-steal-tesla-model-s-seconds-key-fob/
̶ SCADA systems get exposed to the Internet
̶ IoT & AI bring threats into the real world (e.g. connected vehicles)
• Digital Security remains crucial
https://www.theguardian.com/technology/2018/may/29/tesla-crash-autopilot-california-police-carAI Digital Security – 2018 Landscape
• AI security includes the same "usual suspects"
̶ Identity & Access Management
̶ Network
̶ Application
̶ Data
̶ Infrastructure & Cloud
• But AI also introduces new risks
̶ It can be misused
̶ It can be abused
̶ AI may also be difficult to auditAI & Security : The Good, the Bad and the Ugly • The Good : AI improves security • The Bad : AI becomes a weapon for attackers • The Ugly : AI applications can be attacked
Using Artificial Intelligence to address growing security needs
Data Analytics Trusted Advisors & Response Intelligence Consolidation
• Approach: Model behaviors and • Approach: Assist admins & • Approach: Curation of
identify emerging and past users intelligence and contextual
threats and risks reasoning
• Applications: Cognitive SOC
• Applications: Network, user, analyst, orchestration, • Applications: Structured and
endpoint, app and data, cloud automation and digital guardian unstructured (NLP) data sourcesData analytics
What to predict… Inputs Output
Security logs and events
Insider Threats Peer grouping, time-series, anomaly
Risk score of users
Malicious Traffic Network data Risk score of flows
Botnet Domains DNS data, registrar info Domain risk score and reputation
New vulnerability rules
Vulnerable Code Benchmark set of applications
Reduced false positives
Sql queries, errors, file access activity
Database Attacks Anomalies & clusters
Abnormal activity, risk scores
IAM data, logs and UBA alerts
Risky User Access Outlier detection with peer group
Risk score of users, apps
Behavioral Biometrics
Fraudulent Users Keystrokes, app, mouse usage
Risk score of users
Phishing Websites URLs and website content Risk score of suspected sites
Malware infection Endpoint activity AlertsTrusted advisors
"Pull" Assistants help you to answer a question
"Push" Assistants provide relevant information / alert to the user
What to do… Inputs Output
Automatic offense investigations Events Root cause analysis, augmented context
Voice, unstructured content, threat Contextual security information, spoken
Virtual cybersecurity analyst content content
Administrator advisor Unstructured content, threat alerts, etc. Personalized recommendations
User commands, calendar and email Coordinates calendar and email activities;
User self-service assistant contents, support knowledge base provides real-time end-user support
Crisis management In the future, AI will also learn how to proactively adaptIntelligence consolidation
A SIEM ingests and analyzes structured data
Artificial Intelligence adds a major dimension : unstructured data
Watson for Cyber Security has ingested over 2 billion documents in the corpus and is adding thousands more
every day. It’s reduced the time to analyze an incident from hours to minutes, greatly accelerating mitigation and
reducing the impact to the organization.
What to do… Inputs Output
Security intelligence consolidation Unstructured content, web content Cybersecurity contextual knowledge base
Data Lake Custom Implementation Unstructured + structured data Neutral / agnostic knowledge baseAI & Security : The Good, the Bad and the Ugly • The Good : AI improves security • The Bad : AI becomes a weapon for attackers • The Ugly : AI applications can be attacked
AI For Bad Guys ?
• Should we be scared by AI in the hands of cybercriminals ?
• Mass Surveillance & Mass Influence http://deepangel.media.mit.edu/
https://www.blackhat.com/docs/us-16/materials/us-16-Seymour-Tully-Weaponizing-
Data-Science-For-Social-Engineering-Automated-E2E-Spear-Phishing-On-Twitter.pdf
• Attacks automation
• Massive change of scale
TRUE FALSE
• New types of attack
• Generated text, sound, images & videos
… even though AI can be used to identify forged videos…
http://fortune.com/2018/02/21/artificial-intelligence-oxford-cambridge-report/
https://youtu.be/AmUC4m6w1woAI-powered attacks
• Targeted phishing attacks rely on Twitter data
• Neural networks produce a better password cracker
https://arxiv.org/pdf/1709.00440.pdf
• Generative Adversarial Networks learn novel steganographic channels
• XEvil breaks 1000's of existing catchas
• Remember that your webcam may be watching you
To learn more about GANs
https://securityintelligence.com/generative-adversarial-networks-and-cybersecurity-part-1/
https://securityintelligence.com/generative-adversarial-networks-and-cybersecurity-part-2/AI & Security : The Good, the Bad and the Ugly • The Good : AI improves security • The Bad : AI becomes a weapon for attackers • The Ugly : AI applications can be attacked
AI Can Be Attacked
Direct Attack Theft (IC or data)
https://qz.com/823820/carnegie-mellon-made-a-special-pair-of-glasses-that-lets-you-steal-a-digital-identity/AI Can Be Fooled
• Model poisoning Darpa
- noise -
https://www.darpa.mil/attachments/AIFull.pdf
• Noise Introduction
Proof of Concept
https://iotsecurity.eecs.umich.edu/#roadsigns
https://arxiv.org/abs/1707.08945
• Reinforcement
TAY Microsoft
- reinforcement -
http://images.complex.com/complex/image/upload/t_in_content_image/tay-hitler_o4kq62.jpgAI Can Also Be Poorly Implemented
https://www.theverge.com/2018/1/12/16882408/google-racist-gorillas-photo-recognition-algorithm-ai
• Poor Categories
Google
- categories -
• Overfitting
• Convergence of views Underfitting
vs overfitting
https://hackernoon.com/memorizing-is-not-learning-6-tricks-to-prevent-overfitting-in-machine-learning-820b091dc42AI risks go beyond "traditional" security
• Privacy
̶ GDPR - Data Protection & Right To Be Forgotten
̶ Welcome to 1984 !
• Transparency
̶ Am I currently scrutinized by an AI ?
̶ Can you explain why your bot made this decision ?
• Accountability
̶ An autonomous car accident occurs : Who is responsible ?
̶ What about a robot purchasing illegal items on the darkweb ?
https://www.independent.co.uk/arts-entertainment/art/news/swiss-artists-programme-laptop-to-make-random-purchases-from-the-dark-web-a6761891.html
• EthicsEthics & Responsability
You are "driving" your autonomous car.
Suddenly in a curve…
No escape …Ethics & Responsability
Who would you hurt?
- The black car?
- The white car?
- Yourself?Ethics & Responsability
The audience usually chooses the white car.
After all, it should not be driving this side of the road.Ethics & Responsability
What if the black one has a single driver, while the white one conveys 2 babies + their mom ?Ethics & Responsability
You do not know it, but your car's thermal camera does…Ethics & Responsability
Moral can even be evaluated online…
Who would you hurt?
- The black car?
- The white car?
- Yourself?
http://moralmachine.mit.edu/AI & Security : The Good, the Bad and the Ugly
• The Good : AI improves security
• The Bad : AI becomes a weapon for attackers
• The Ugly : AI applications can be attacked
In the end, the Good wins !Attacks against AI: Countermeasures
Data Security
Training data & privacy
Model Security
Robust and resilient models
Operations Security
Detect and eliminate adversarial inputs
Non-trusted
Trusted SME
Robust Models Actor
Detection
Training Training
Data
1. Data Security 2. Model Security 3. Operations SecurityZoom Into Model Security
https://securityintelligence.com/adversarial-ai-as-new-attack-vector-opens-researchers-aim-to-defend-against-it/
eXplainable Artificial Intelligence (XAI)3 Guiding Principles For Cybersecurity XXXX By Design Think about security since the inception phase Include privacy, transparency, ethics in the design process XXXX By Default Deny everything to everyone by default Grant access when it is required - on a Need-To-Know basis XXXX Impact Assessment GDPR introduced the PIA : Privacy Impact Assessment Reuse an extend the concept Apply these 3 principles to AI
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