The seminar covered data security, privacy, and applications in emerging body area networks (BANs). Key topics included typical BAN applications in healthcare, research challenges around frequency bands and hardware, and models proposed for secure data storage and access control. Four models were described in detail: one based on redundant residue number systems, one using erasure coding, one using constant data motion, and one using attribute-based encryption to implement fine-grained access control of encrypted health data in BANs.

1. A Seminar on
Data Security, Privacy and Other
Applications in Emerging Body
Area Networks
Narayana Vinayak
B080015EC

2. Layout of the Seminar
 Goals
 Introduction
 Typical Applications
 Research Challenges
 Data Security and Privacy
 Models Proposed

3. Goals
 Understanding BANs
 Appreciating their „potency‟
 Being aware of their current applications
 Understanding the challenges on the horizon
 Understanding models proposed for data
security in BANs

4. Introduction
Definition by IEEE: “A communication
standard optimized for low power devices for their
operation on, in or around the human body (but not
limited to humans) to serve a variety of
applications including medical, consumer
electronics or personal entertainment and other.”
Source: IEEE 802.15

5. Typical Applications
Source: M. Patel and J. Wang, “Applications, Challenges,
And Prospective In Emerging Body Area Networking
Technologies,” IEEE Wireless Communications, Feb. 2010

6. Layout
Source: M. Li and W. Lou, “Data Security And Privacy In
Wireless Body Area Networks,” IEEE Wireless
Communications, Feb. 2010

7. Relevance
* Ageing population; sedentary lifestyle
* WHO stats:
# Diabetics-360 million by 2030
# >2.3 bn. people obese by 2015
# rise in neuro-degenerative diseases
* Fragile healthcare system, rising medical costs
* Shortage of trained health staff in third world

8. Realisation
 Strategically placed wearable or implanted sensor nodes
 Job: sample, process and transmit vital signs
 What signs?
 Heart rate, blood pressure, temperature, pH, respiration etc.
 Where to?
 To a hospital, clinic or a central repository of medical data
 How?
• A gateway device (e.g., a cell phone or a PDA) is used as a
gateway device to connect to infrastructure networks like
WLAN, WPAN etc.

9. Source: Mark A. Hanson et al., “Body Area Sensor Networks:
Challenges and Opportunities,” Computer, Jan. 2009

10. Uses
 Alerting the patient via SMS, alarm or reminder messages
 Close-loop bio-feedback: if high sugar-level, a device
triggers an insulin pump to inject a dose of insulin
(artificial pancreas)
 Long-term medical trend analysis
 Reduction in hospital stays
 Regulation of treatment regimes
 Essence: Offering a paradigm shift from managing
ILLNESS to managing WELLNESS by focusing on
prevention and early detection (pre-emptive defence!)

11. Research Challenges
1. Frequency Band Selection:
1. Most BAN devices need global operability
2. Facility for low-power usage (less crowded)
3. Less stringent rules for flexible usage and adaptability
4. Solutions proposed: Opening up the 2360-2400 MHz spectrum
near ISM for medical BANs and allocating up to 24 MHz in the
413-457 MHz range for medical micropower network
2. Antenna Design:
1. Restrictions on size, material and shape of antenna
2. Hostile RF environment due to changes in wearer‟s age, weight
changes and posture changes
3. During implants only non-corrosive and bio-compatible material
can be used: Platinum or Titanium (both poor) against the usual
copper

12. Source: M. Patel and J. Wang, “Applications, Challenges, And Prospective In
Emerging Body Area Networking Technologies,” IEEE Wireless Communications,
Feb. 2010

13. 3. PHY Protocol Design:
1. Minimize power consumption
2. Solution: Quick turn-around from transmit to receive and fast
wake-up from sleep mode
3. Seamless connectivity in dynamic environments
4. Energy-Efficient Hardware:
1. Today‟s wireless technologies draw relatively high peak current
2. Also rely on duty cycling between sleep and active
3. Solution: Operation on low peak pulse-discharge current from
thin-film (paper) batteries, idle listening, developing a crystal-
less radio*
* Reference: F. Sebastiano et al., “Impulse Based Scheme for crystal-
less ULP Radios”, Proc. IEEE ISCAS, May 2008, pp. 1508-1511.
5. Technical Requirements:
1. Wide variation in data rate, BER, delay tolerance, duty cycle and
lifetime
2. Diverse application environments

14. Source: M. Patel and J. Wang, “Applications, Challenges, And Prospective In
Emerging Body Area Networking Technologies,” IEEE Wireless
Communications, Feb. 2010

15. Source: M. Patel and J. Wang, IEEE Wireless Communications, Feb. 2010

16. Candidate Technologies
Source: M. Patel and J. Wang, “Applications, Challenges, And Prospective In
Emerging Body Area Networking Technologies,” IEEE Wireless Communications,
Feb. 2010

17. Entities Involved in Research
 The IEEE 802.15.6 Task Group is application
developing the first industrial standard for
the Physical and MAC layers for BAN
(done, Feb. 2011) transport
 Major competition: ZigBee and
Bluetooth. network
 Holistic standardization needed for plug-
and-play interoperability
link
 ISO/IEEE 11073 Personal Health Data
Working Group: Standardization of data
exchange between peripheral area physical
network devices and gateway devices

18. Source: M. Patel and J. Wang, “Applications,
Challenges, And Prospective In Emerging Body Area
Networking Technologies,” IEEE Wireless
Communications, Feb. 2010

19. Data Security and Privacy
 Data Security: Data is securely stored and transferred
 Data Privacy: Data can be used only by authorized people
 Application scenario:
◦ Emergency; paramedic reads RFID* tag to get the patient‟s
medical records and his profile.
◦ WBAN is set up with wearable sensors
◦ Nurse reads health data from WBAN and uploads data onto local
network
◦ Patient‟s gateway device is configured with an Access Policy (AP)
that grants access to records (also adapts automatically)
◦ Patient can adjust his AP to hide sensitive data
* Radio Frequency Identification is a standard technology
that uses Radio waves to sense the details of an object for
tracking. It uses RFID tags for this purpose.

20.  Threats Faced by Data within BAN:
◦ Threat from Device Compromise (encrypted data and key in same
node)
◦ Threat from Network Dynamics (fake nodes masquerade real ones)
 Storage Security Requirements:
◦ Confidentiality
◦ Dynamic Integrity Assurance
◦ Dependability
 Access Security Requirements:
◦ Access Control (privacy; Fine-Grained)
◦ Accountability
◦ Revocability
◦ Non-Repudiation
 Other Requirements:
◦ Authentication
◦ Availability
◦ Security-Safety, Security-Efficiency and Security-Usability conflict
resolution

21. Source: M. Li and W. Lou, “Data Security And Privacy In Wireless
Body Area Networks,” IEEE Wireless Communications, Feb. 2010
The above Access Policy reads: “allow access by a doctor
from the surgery department but not Dr. X, or an analyst or
a paramedic, or a nurse who is not an intern.”

22. Models Proposed
Secure and Dependable Data Storage Schemes:
1. Based on Redundant Residue Number System (RRNS)
1. Proposed by Chessa et al.
2. Method: A number representable on a set of h moduli is
represented by h + r moduli, where the extra r moduli are
redundant
3. Source Node S distributes a single file F among n other nodes,
where n=h + r is a random pick
4. S computes F‟s residue vector and distributes each file share to a
different storage node
5. Pros.: Erasure tolerance is s<=r and corruption tolerance is
ceil((r-s)/2)
6. Cons.: Set of moduli can be very large, data integrity not ensured
when number of errors is more than r.

23. 2. Based on Erasure Coding
1. Proposed by Wang et al.
2. Original encrypted data is broken down into n data shares, with
each of them made of a block generated from (n,k) erasure
coding and a share of the secret key using (n,k) secret sharing
3. These data shares are then distributed among the n neighbouring
nodes
4. Dynamic Integrity Check: Each storage node computes and
broadcasts an algebraic signature on one data share; one node
checks its signature against those by other nodes to detect
alterations timely
5. Pros.: Data confidentiality, dependability and dynamic integrity
achieved simultaneously
6. Cons.: No third party (say, the local server) can perform integrity
checks.

24. 3. Based on Constant Data Motion method
1. Proposed by Pietro et al.
2. Idea: Move the data from one sensor node to the next so as to
make it hard for the cracker to „track‟ and „catch‟ the data
3. Found to be very efficient (high data survival probability)
4. Cons.: High communication and storage overhead; less practical
in energy-strained environments
4. Attribute Based Encryption (ABE)
1. Proposed by Li et al.
2. Specifically called the Ciphertext Policy ABE (CP-ABE)
3. Perfectly matches the model of Role-Based Access Control
(RBAC)
4. Each user has a set of roles; patient chooses which roles to grant
access to.
5. When a node in WBAN generates data, the AP is built into the
Ciphertext; splitting a secret among components belonging to
different user attributes; randomized to prevent user-collusion
6. Effectively implements fine-grained access control

25. Physiological Signal-based Key Agreement (PSKA):
 Proposed by Ayan Banerjee et al.
 Requires no a priori deployment of keying material or
initialization
 Inspiration: Dynamic and complex nature of human
physiological signals
 Design goals met:
◦ Length and randomness
◦ Low latency
◦ Distinctiveness
◦ Temporal variance
 Signal used: Electrocardiogram (EKG) commonly

26.  Method used:
 Cons.: It may correct a few differences in feature vectors
but can‟t handle the reordering of or presence of
additional feature vectors; solution: fuzzy vault

27. Fuzzy Vault
 Generate a v-th order polynomial p over the variable x that
encodes the secret S
 Compute the value of the polynomial at different x from
the set A (at the transmitter) and create a set
R= {a, p(a)}
 Add randomly generated set of points called chaff to R,
which don‟t lie on the polynomial; we call R as the vault
 To unlock the vault using set B (at the receiver), construct
a set Q (see example given overleaf)
 Unlocking is possible only if Q has a significant number
of legitimate (non-chaff) points that are on the polynomial
 Mapping to PSKA: Features at sender are set to A and
those at the receiver, in set B

28. Example
Consider the polynomial: p(x) = x + 1; A = {1, 2, 3};
B = {1, 3, 4}
Now, vault R is created by computing the polynomial‟s value
at each point in A and adding chaff-points
So, R = { (1, 2)(2, 3)(3, 4)(4, 7)(6, 9)(7, 12)(8, 5) }
The last four points are chaff-points
To unlock the vault, the set Q is constructed,
Q = { (1, 2)(3, 4)(4, 7) }
As the set Q has two points on the polynomial, we can use it
to reconstruct the first-order polynomial, and thus, unlock
the secret

29. Major References
 M. Patel and J. Wang, “Applications, Challenges, And
Prospective In Emerging Body Area Networking
Technologies,” IEEE Wireless Communications, Feb.
2010, pp. 80-88
 A. Banerjee et al., “PSKA: Usable and Secure Key
Agreement Scheme for Body Area Networks,” IEEE
Transactions On Information Technology In
Biomedicine, Jan. 2010, pp. 60-68
 M. Li and W. Lou, “Data Security And Privacy In
Wireless Body Area Networks,” IEEE Wireless
Communications, Feb. 2010, pp. 51-58
 Others: Cited in the Report

30. Thanks a lot!