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Data Dissemination Protocols in Wireless Sensor Networks : Models, Security and Design

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... Wireless Sensor Networks : Models, Security and Design ... Malware spreads, piggybacked on the broadcast protocol, passing security ... Analytical tool proposed ... – PowerPoint PPT presentation

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Title: Data Dissemination Protocols in Wireless Sensor Networks : Models, Security and Design


1
Data Dissemination Protocols in Wireless Sensor
Networks Models, Security and Design
  • Candidacy Proposal Defense by Pradip De
  • Department of Computer Science and Engineering
  • The University of Texas, Arlington
  • Center for Research in Wireless Mobility and
    Networking

Advisors Sajal K. Das and Yonghe Liu Committee
Members Kalyan Basu, Mohan Kumar, Matthew Wright
2
Organization
  • Data Dissemination in Wireless Sensor Networks
  • Protocol Models and Performance Analysis
  • Security Analysis of Data Dissemination in Sensor
    Networks
  • Design of a Reprogramming Protocol for Mobile
    Sensor Networks
  • Ongoing and Future Work

3
Data Dissemination/Reprogramming in Wireless
Sensor Networks
4
Motivation
  • Sensor Networks operate unattended for months or
    years
  • Little control once deployed
  • Environment changes over time
  • Reprogramming of sensors is essential
  • Evolving requirements
  • Bug fixes after deployment
  • Scale and embedded nature requires network code
    propagation
  • Data dissemination protocols

5
Protocol Design Objectives and Issues
  • Scalability
  • Size of network
  • Data/Code Size disseminated
  • Reliability
  • Robust against packet loss (wireless
    uncertainties)
  • Tolerate topology changes (node failures)
  • Reach all nodes staying uncorrupted
  • Efficiency
  • Rapid propagation required
  • Security
  • Authentication necessary

6
Protocols in the Horizon Trickle Levis et al,
NSDI 2004 Deluge Hui and Culler, SenSys
2004 MNP Kulkarni and Wang, ICDCS 2005
7
Deluge
J. W. Hui and D. Culler. The dynamic behavior of
a data dissemination protocol for network
programming at scale. In Proceedings of the
second International Conference on Embedded
Networked Sensor Systems (SenSys 2004)
8
Deluge Protocol Overview
  • A General Protocol for Bulk Data Dissemination
  • State Machine with strictly local rules
  • Nodes advertise, request data, and broadcast
  • Object divided into contiguous pages, each
    consisting of N packets
  • Allows for spatial multiplexing

9
Objectives of Dissertation
  • Model based performance analysis of data
    propagation over dissemination protocols
  • Rate of information propagation
  • Model based security analysis of network-wide
    dissemination
  • Spread of node compromise in a sensor network
    with secure communication using pairwise keys
  • Malware propagation over data dissemination
    protocols
  • Design of a reprogramming protocol for mobile
    sensor networks
  • Performance analysis of protocol in mobile
    scenario
  • Modeling data/malware propagation over
    dissemination protocols in mobile sensor networks

10
Model Based Comparative Performance Analysis of
Data Dissemination Protocols
11
Model Characteristics and Features
  • An epidemic theoretic model for analysis of data
    propagation over these protocols
  • Analytical tool for studying dissemination
    protocols
  • Measures rate of information propagation
  • Flexibility of model
  • accommodates different dissemination protocols
  • Mechanism for inter-protocol comparison
  • Propagation speed
  • Extent of coverage

12
Sensor Network Model
  • Modeled as an undirected geometric random graph
  • N nodes uniformly randomly distributed
  • Unit Disk Model with transmission radius
  • is the probability of edge existence
    between nodes u and v
  • at distance
  • Node Density
  • where A is the area of the terrain

u
v
13
Epidemic Theory Overview
  • Epidemic Theory
  • Models an infection spread in a population of
    susceptibles
  • Broadly two kinds of modeling techniques
  • Random Graph based spatial model
  • Differential Equation based temporal model
  • Infection Spread Cases
  • Susceptible-Infected-Susceptible (SIS)
  • Susceptible-Infected-Recovered (SIR)
  • Homogeneously mixed population
  • Heterogeneously mixed population

14
Epidemic Theoretic Framework
  • Proposed Framework
  • Design the spread model using network
    characteristics
  • Adopt differential equation based approach
  • Data propagation conforms to No Recovery model
  • Local interactions based on transmission range
  • Estimate the rate of infection (ß) based on
  • Rate of communication paradigm of the broadcast
    protocol
  • Infectivity potential (?) of the data

15
Infection Spread Model
Source Node
Susceptible S(t)
Inoperative R(t)
Infective I(t)
16
Model Derivation
  • No Recovery Based Infection Model
  • Infected nodes cannot be recovered and the
    infection ultimately reaches the whole network
  • Formulation of differential equations for I(t)
    and S(t) based on network parameters
  • At , I(t) N

where
17
Fitting Broadcast Protocols
  • Deluge
  • In the maintenance algorithm, the probability
    of node i broadcasting metadata in each time
    interval
  • is given by
  • where k denotes the advertisement
    threshold in the period
  • and denotes the expected
    number of neighbors of a node i
  • The expected time for a node to receive metadata
    is calculated using
  • The expected time to transmit a page
    in a neighborhood is derived from
    and the infection rate and is given by

where is the infectivity potential of the data
18
Deluge Data Propagation Rate
Simulation
Analytical
19
Summary
  • Performance analysis of broadcast protocols
  • Speed of propagation of data
  • Reachability into network
  • Construction of an epidemic model for data
    propagation
  • Flexible tool to compare different broadcast
    protocols

20
Security Analysis of Network-Wide Data
Dissemination in Sensor Networks
  • Model based security analysis of network-wide
    dissemination
  • Spread of node compromise in a sensor network
    with secure communication using pairwise keys
  • Malware propagation over data dissemination
    protocols

21
Propagation of Node Compromise in Sensor Networks
  • Construction of a model and analysis of the
    spread of node compromise on a sensor network
    based on Epidemic Theory
  • Identify point of outbreak of the process in the
    network
  • Observe the impact of infectivity duration of a
    compromised node on the process
  • Identify critical values of relevant parameters
    to prevent outbreaks

22
Network Model
  • Consider two deployment strategies
  • a basic uniform random deployment strategy
  • A realistic group based deployment strategy
  • Adopt the same model for the physical network
  • An overlay with key sharing probability q based
    on random pairwise key predistribution

23
Topology Model Group Based Deployment
  • A set of 2-dimensional Gaussian Distribution of
    resident points about the deployment point
  • g(x,yj) represents the probability of a node
    belonging to group j to reside within
    transmission range of point x,y

24
Topology Model Group Based Deployment
  • The probability that a node at (x,y) has l
    neighbors is expressed as Nb(l,x,y)
  • Nb(l,x,y) is a function of g(x,yj) and the
    gaussian distributed node location pdf of (x,y)
  • The degree distribution p(k) of a node is given
    by
  • where

25
Analysis Overview
  • Two scenarios
  • No recovery once compromised
  • Nodes recover
  • When nodes do not recover transmissibility is
    expressed only in terms of the infection
    probability
  • Essence of node recovery is captured by
    expressing the transmissibility as a function of
    the average duration of infectivity

26
Primary Analysis Results
  • Average Cluster size as the epidemic attains
    outbreak proportions
  • Average Epidemic size after outbreak results
  • Results observed under both scenarios of without
    node recovery and with node recovery

27
Epidemic size with infection probability
28
Summary
  • Study of spread of node compromise in sensor
    networks
  • Uniform random network model
  • Group deployment based network model
  • The outbreak points for network-wide compromise
    propagation are affected by the deployment
    strategy

29
Vulnerability of Broadcast Protocols to Malware
Propagation
  • Model based security analysis of network-wide
    dissemination
  • Spread of node compromise in a sensor network
    with secure communication using pairwise keys
  • Malware propagation over data dissemination
    protocols

30
Vulnerability of Broadcast Protocols
  • Construct model to estimate vulnerability to
    piggybacked malware spread
  • Compromise propagation after a single or few
    nodes compromised by adversary
  • No Recovery case
  • Use the same model for data propagation
  • Infection ultimately spreads to the entire
    network

31
Attack Model
Malware spreads, piggybacked on the broadcast
protocol, passing security verification at each
stage since source was compromised
Broadcast Protocol wavefront pass
authentication Deploy Malicious Code
Compromised Src Authentication keys captured
32
Model Analysis
  • Imposition of a simultaneous recovery process
  • Parameterized by mean recovery rate of each
    node
  • The infection rate is computed from the
    communication rate of the protocol
  • Construct differential equations to compute the
    sub-populations I(t), S(t), and R(t)

33
Deluge Spreading Time Comparison
Simulation
Analytical
With Recovery
34
Summary
  • Reprogramming protocols are essential for sensor
    networks
  • However, they could be carriers for rapid spread
    of malicious code in sensor network
  • Analytical tool proposed
  • Gain valuable insights into the propagation
    characteristics of malware over different
    broadcast protocols
  • Tool is flexible for comparative studies of
    different broadcast protocols

35
Design of Reprogramming Protocols for Mobile
Sensor Networks
  • Design of a reprogramming protocol for mobile
    sensor networks
  • Performance analysis of protocol in mobile
    scenario
  • Modeling data/malware propagation over
    dissemination protocols in mobile sensor networks

36
Reprogramming Protocols for Mobile Sensor Networks
  • Numerous applications for mobile sensor networks
  • Drawbacks of the existing reprogramming protocols
    for mobile scenarios
  • Location uncertainty due to mobility
  • Inefficiency of page ordered download
  • Dynamic changes in neighborhood node density
  • Protocol should take advantage of mobility

37
ReMo
  • Salient features
  • Based on a periodic metadata broadcast paradigm
  • The probability of broadcast is dynamically
    adjusted based on neighborhood density
  • Regardless of order, pages are downloaded based
    on availability
  • Snoop on neighborhood to construct link quality
    metrics
  • Choose neighbors appropriately for requesting
    downloads based on not only best link quality but
    also high potential of code availability

38
Link Characterization
39
Metadata Broadcast
  • and are the counts of the metadata
    advertisements that are different and same as
    current node
  • The periodic metadata broadcast probability for
    each time slot t is adjusted based on the above
    counts
  • Proportional increase in probability on hearing
    different metadata
  • Probability decreased aggressively on hearing
    same metadata

40
Protocol Components and Operation
  • Page Download Potential (PDP)
  • Based on the pages a node can potentially
    download from a neighbor
  • Neighbor Link Profile (NLP)
  • Aware of the current link quality with each
    neighbor
  • Link Quality estimate is updated as a window mean
    exponentially weighted moving average
  • Node i selects a neighbor j to send a download
    request based on NLP and PDP of j

41
Comparison of Code Update Completion Time
42
Number of Message Transmissions
43
Number of Message Transmissions
44
Number of Message Transmissions
45
Ongoing and Future Work
  • Design of a reprogramming protocol for mobile
    sensor networks
  • Performance analysis of protocol in mobile
    scenario
  • Modeling data/malware propagation over
    dissemination protocols in mobile sensor networks

46
Performance Analysis of Data Dissemination
Protocols in Mobile Sensor Networks
  • Markov Chain based model of the protocol
    operation
  • Borrow ideas from MAC protocol analysis
  • 802.11 MAC models for backoff schemes
  • Derive throughput of data delivery over these
    protocols

47
Modeling of Information Propagation in Mobile
Sensor Networks
  • Analytical model for the data propagation rate in
    mobile sensor network
  • Vulnerability assessment in a mobile scenario
  • Model approach based on epidemic theory
  • Assumption of homogeneous mixing among nodes
    possible

48
Implementation of ReMo
  • Implementation of ReMo on a testbed of SunSPOTs
  • Test the efficacy of the design of ReMo for code
    download under different real world mobility
    conditions
  • Implementation in the Java ME Framework
  • Compilation, Deployment and Execution using Ant
    scripts

49
Thank You
50
Relevant Publications
  • P. De, Y. Liu, and S. K. Das, Modeling Node
    Compromise Spread in Wireless Sensor Networks
    Using Epidemic Theory. In IEEE International
    Symposium on a World of Wireless, Mobile and
    Multimedia Networks (WoWMoM) 2006.
  • P. De, Y. Liu, and S. K. Das, Deployment Aware
    Modeling of Node Compromise Spread in Wireless
    Sensor Networks , under review in ACM
    Transactions on Sensor Networks.
  • P. De, Y. Liu, and S. K. Das, Evaluating
    Broadcast Protocols in Sensor Networks An
    Epidemic Theoretic Framework , poster paper in
    The 3rd IEEE International Conference on
    Distributed Computing in Sensor Systems (DCOSS)
    2007.
  • P. De, Y. Liu, and S. K. Das, An Epidemic
    Theoretic Framework for Evaluating Broadcast
    Protocols in Wireless Sensor Networks, In the
    4th IEEE International Conference on Mobile Ad
    Hoc and Sensor Systems (MASS) 2007
  • P. De, Y. Liu, and S. K. Das, An Epidemic
    Theoretic Framework for Vulnerability Analysis of
    Broadcast Protocols in Wireless Sensor Networks
    , under review in IEEE Transactions on Mobile
    Computing.
  • P. De, Y. Liu, and S. K. Das, Harnessing
    Epidemic Theory to Model Malware Propagation in
    Wireless Sensor Networks, under review in IEEE
    Communications Magazine Special Edition on
    Security in Mobile Ad Hoc and Sensor Networks
  • P. De, Y. Liu, and S. K. Das, ReMo An Energy
    Efficient Reprogramming Protocol for Mobile
    sensor Networks, accepted for publication at The
    6th IEEE International Conference on Pervasive
    Computing and Communications (PerCom) 2008.
  • Work under preparation
  • P. De, Y. Liu, and S. K. Das, An Analytical
    Model for the Performance Analysis of Data
    Dissemination Protocols in Mobile Sensor
    Networks.
  • P. De, Y. Liu, and S. K. Das, Analyzing
    Information Propagation over Data Dissemination
    Protocols in Mobile Sensor Networks.
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