SoK: Security and Privacy in Implantable Medical Devices and Body Area Networks 0 Fall 2014 Presenter: Kun Sun, Ph.D. Michael Rushanan*, Denis Foo Kune,

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Presentation transcript:

SoK: Security and Privacy in Implantable Medical Devices and Body Area Networks 0 Fall 2014 Presenter: Kun Sun, Ph.D. Michael Rushanan*, Denis Foo Kune, Colleen M. Swanson, Aviel D. Rubin, s&p14 Thank Michael for sharing the slides.

What is an Implantable Medical Device?  The FDA strictly defines a medical device  Device  Embedded system that can sense and actuate  Implantable  Surgically placed inside of a patient’s body  Medical  Provides diagnosis and therapy for numerous health conditions 1

IMD are not your typical PCs 2

3

 There exists resource limitations  The battery limits computation and is not rechargeable  There are safety and utility concerns  The IMD must be beneficial to the patient and elevate patient safety above all else  Security and privacy mechanisms must not adversely affect the patient or therapy  Lack of security mechanisms may have severe consequences  IMD’s provide safety-critical operation  Must fail-open in the context of an emergency 4

Research Questions  How do we provide security and privacy mechanisms that adequately consider safety and utility?  When do we use traditional security and privacy mechanisms or invent new protocols?  How do we formally evaluate security and privacy mechanisms?  Novel attack surfaces 5

A Healthcare Story Alice 6 Cardiac Carl NursePatient

Cardiac Carl’s Condition  Atrial Fibrillation  Implantable Cardioverter Defibrillator  His ICD is safety-critical 7 Cardiac Carl Atrial Fib.

Alice and Carl’s Relationship Nurse Alice 8 visits accesses ICD w/ programmer receives private data adjusts therapy Where are the security and privacy mechanisms? Cardia c Carl

Alice and Carl’s Relationship Mallory 9 Hacker Elite

Alice Mallory and Carl’s Relationship Nurse Alice 10 Cardia c Carl Mallor y wireless communication [Halperin, S&P, 08], [Li, HealthCom, 11] eavesdro p forge modify jam

Attack Surfaces 11 Cardia c Carl

Red Herring?  Insulin pump: a self-contained controller  Most wireless communication is one direction  Read data from IMD  No write to IMD (like Dick Cheney’s)  malware  Similar to Industrial Control System  Can read data from sensors  No write to control the actuators  Stuxnet on Iran’s nuclear plant 12

Security and Privacy Mechanisms  Security and Privacy mechanisms exist in standards  Medical Implant Communication Services  Wireless Medical Telemetry Service  These mechanisms are optional  Interoperability might take priority of security 13 [Foo Kune, MedCOMM, 12]

14 Biometrics and Physiological ValuesOut-of-BandDistance BoundingSoftware/MalwareExternal DevicesAnomaly Detection Future WorkTelemetry Interface

Research Challenges  Access to Implantable Medical Devices  Is much harder then getting other components  Reproducibility  Limited analysis of attacks and defenses  Do not use meat-based human tissue simulators  Do use a calibrated saline solution at 1.8 g/L at 21 ◦C  The complete design is described in the ANSI/AAMI PC69:2007 standard [92, Annex G] 15

Security and Privacy Mechanisms  Biometric and Physiological Values  Key generation and agreement  Electrocardiogram (ECG)  Heart activity signal  Interpulse interval  Time between heartbeats 16

H2H Authentication Protocol Nurse Alice 17 [Rostami, CCS, 13] Cardia c Carl measure ECG α measure ECG β send ECG measurement β send ECG measurement α TLS without certs

H2H Authentication Protocol  Adversarial Assumptions  Active attacker with full network control  The attacker cannot:  Compromise the programmer  Engage in a denial-of-service  Remotely measure ECG to weaken authentication 18 [Rostami, CCS, 13]

Physiological Values as an Entropy Source  How do ECG-based protocols work in practice?  Age, Exertion, Noise  ECG-based protocols rely on an analysis of ideal data in an unrealistic setting  Data sample is close to their ideal distribution  Very accurate estimate of distribution characteristics  Extract randomness using the estimate on the same data sample  Observability  Using video processing techniques to extract ECG-signals 19 [Rostami, S&P, 2013] [Chang, HealthTech, 2012] [Poh, Biomedical Engineering, 11]

20 Future Work

Trusted Sensor Interface  Current systems trust their analog sensor inputs  This assumption may not always hold  Forging signals using electromagnetic interference  Inject cardiac waveform 21 [Foo Kune, S&P, 2013]

Neurosecurity  Neurostimulators  What are the new attack surfaces  What are the implications of recording and transmitting brainwaves  Brain computer interfaces  Cognitive recognition could leak:  Passwords, personal information 22 [Martinovic, USENIX, 2012], [Denning, Neurosurg Focus, 09]

Questions?  IMDs are becoming more common  Improving patient outcome  Research gaps exists  Software  Sensor Interface  Areas for future work include  Physiological values as an Entropy Source  Trusted Sensor Interface  Neurosecurity 23