Security of Emergent Properties in Ad-Hoc Networks cambridge04, EBOOK
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Security of Emergent Properties in Ad-Hoc Networks
Virgil D. Gligor
Electrical and Computer Engineering Department
University of Maryland
College Park, Maryalnd 20742
Extended Abstract
The notion of ad-hoc networking refers to the spontaneous formation of a network of computing nodes
without reliance on a specic infrastructure. Typical ad-hoc networks consist of mobile nodes — ranging from
laptops and pocket PCs to miniature sensor devices — with widely dierent computation and communication
capabilities. Node mobility may be limited to deployment, as in the case of some sensor networks, or may
continue throughout the lifetime of the network, as is the case in mobile ad-hoc networks (MANETs). Ad-hoc
networks may also be formed by application-level software agents executing on top of a xed communication
infrastructure. In such networks, node mobility can take the guise of software-agent migration among
dierent hosts, or even of autonomous peers (e.g., principals, domains) joining or leaving peer-to-peer (P2P)
networks formed without the benet of a separate, xed collaboration infrastructure.
Ad-hoc networks emerge through the collaboration of every node with its neighbors which usually in-
volves sharing resources, communication links, and applications. For example, in mobile ad-hoc networks,
a topology emerges as every node exchanges information with its neighbors to establish connectivity and
forwards packets to its neighbors toward chosen destinations to establish the routing infrastructure. The
basic infrastructure thus created is highly dynamic not only because of node mobility but also because of
lack of guaranteed network connectivity. For instance, sensor-node deployment cannot usually guarantee
direct connectivity between all pairs of nodes due to sensor scattering. Further, the node membership to
the network that emerges after deployment may change in time because sensor nodes exhaust their power
and are replaced by new nodes that are scattered in the same geographical area. In contrast, in ad-hoc
networks formed at application levels of the Internet, membership is typically unaected by unreliable link-
layer communication or by power exhaustion. Instead, dynamic node-membership changes can be caused
by potentially unanticipated joins and departures of autonomous nodes; e.g., joins and departures of mobile
software agents in an application-level network, or of autonomous domains in a P2P network. At these levels,
collaboration infrastructures must be created and changed by the network nodes themselves usually based
on a dynamically-negotiated sharing of objects and applications.
A common characteristic of all ad-hoc networks is that of emergent properties. Intuitively, emergent
properties are features that cannot be provided by individual network nodes themselves but instead result
from interaction and collaboration among network nodes. Although one may think of the creation of an
ad-hoc network as a set of emergent connectivity and routing properties, our primary focus is on the specic
properties that may emerge after the ad-hoc networks are thus established. The emergent properties and
their security characteristics we propose to study are dierent from traditional network properties established
via protocol interactions in several fundamental ways. First, it is possible that neither the time nor the locus
of emergence of these properties can be easily anticipated. Second, the emergence of these properties may be
uncertain, in the sense that it may be probabilistic. Third, these properties may be transient, in the sense
that they may disappear from the ad-hoc network during normal operation and not as a result of exceptional
events; e.g., node or protocol failures.
Although not identied as emergent in the past, several important properties of concurrent and distributed
systems share some characteristics of emergent properties in ad-hoc networks. For example, the place and
time of emergence of some non-transient safety properties, such as deadlocks in distributed systems [1],
cannot be anticipated and their emergence is uncertain; i.e., some detected deadlocks may, in fact, be false
[17]. Similarly, process starvation in some systems with distributed control [10, 11] and many denial of service
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instances [18, 19, 42, 33] also share some characteristics of emergent properties. Emergent properties have also
been identied in system and network security, primarily in the area of policy composition [28, 23, 32, 22, 30].
For instance, even under simple criteria such as conjunction the composition of non-discretionary policies
yields new properties that are not present in the individual policies under composition [29, 41, 20]. In contrast
with the extensive research on such properties in distributed systems, there is relatively little work on the
analysis of such emergent behavior in ad-hoc networks, and even less focusing on the security implications
thereof.
Why Security of Emergent Properties ?
Security analyses of emergent properties in ad-hoc networks is essential for several reasons. First, many
emergent properties represent new features of ad-hoc networks that are fundamental to ensuring network
security and robustness. For instance, these properties may be used to help establish or revoke trust relations
that are necessary for both node and message authentication. Second, some emergent properties are undesir-
able and may lead to security violations and, for this reason, their detection and handling help maintain the
security and robustness of the network. For example, emergent properties may indicate (in a manner which
bypasses traditional intrusion-detection techniques) that a certain network node is captured by an adversary.
Third, inadequate assessment of emergent properties such as false detection may also lead to security and
robustness violations. For example, the false detection of node capture may lead to network partitioning
and denial of service in an ad-hoc network by the unnecessary revocation of node membership. Fourth, the
understanding of the characteristics of emergent properties helps determine the scalability and resilience of
ad-hoc networks. For example, desirable emergent properties (such as establishment of secure communica-
tion paths in sensor networks via random key pre-distribution) may place constraints on the network size
but may also imply resilience of network communications below a certain threshold of compromised nodes
[8]. To illustrate the distinguishing characteristics of emergent properties and their security implications,
we present several examples of desirable and undesirable emergent properties in dierent types of ad-hoc
networks.
Example 1. Trust Establishment in Mobile Ad-hoc Networks.
We view the notion of trust establishment as the application of evaluation metrics to a body of (trust)
evidence. An outcome of trust establishment is a trust relation. A simple example of a trust relation that
needs to be established arises in the context of determining whether some certication authority’s signature
on a public-key certicate asserting an <identity, public key> or <identity, attributes> association repre-
sents su
cient evidence for the validity of that certicate. In traditional public-key infrastructures, the trust
relation that helps guarantee the validity of such a certicate is established between a certicate user and the
signing authority, either directly (e.g., at user registration) or indirectly (e.g., by evaluating multiple trust
relations that form a trust path between the certicate user and the signing authority) [24, 39]. In contrast,
in mobile ad-hoc networks where public-key infrastructures may not exist or may not be accessible due to
connectivity limitations, trust relations may need to be established among nodes after network emergence.
Here, every node could potentially become a “certication authority,” yet the identities, attributes, and
conguration properties of the connected nodes may remain un-veried until network emergence. Hence,
trust establishment has to be based on dynamic evaluation of signed evidence about a node (e.g., location,
identity, and conguration attributes) and not just on statically dened relationships at, or prior to, network
emergence (e.g., on static determination of a node’s trustworthiness derived from its design and implemen-
tation characteristics). This means that neither the time nor the locus of emergence of a trust relation can
be anticipated, the emergence of trust relations becomes uncertain, and trust relations may be transient.
Furthermore, the dynamic establishment of trust relations must be accompanied by the dynamic detection
of undesirable trust relations that may also emerge. It is possible, and indeed very likely, that network
nodes captured by an adversary will introduce false evidence about trust-relation emergence and revoca-
tion. Hence, the design and use of evidence-evaluation metrics must be able to assign very low certainty to
evidence assessed to be questionable while still achieving an acceptable number of false positives [14].
Example 2. Establishing Secure Communication Paths in Distributed Sensor Networks.
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Distributed Sensor Networks (DSNs) are ad-hoc networks formed after large numbers of nodes with very
limited computation, memory, and RF communication capabilities are scattered across potentially hostile
environments where, e.g., communication may be monitored and nodes may be captured and surreptitiously
used by an adversary. DSNs are dynamic in the sense that they allow addition and deletion of sensor
nodes after deployment to grow the network or to replace failing and unreliable nodes [9]. Although DSNs
require cryptographic protection of communications, use of traditional public-key cryptography is usually
not possible due to its excessive energy requirements. Also, pairwise sharing of symmetric keying material
between all network nodes is ruled out by the sensor-memory size constraints anticipated for the foreseeable
future, by the inability to communicate directly with all nodes, and by the need to conne communication
compromise to small neighborhoods of captured nodes. To date, all practical keying schemes require the
pre-distribution of a small number of encryption keys to sensor nodes prior to deployment [15, 8]. All such
schemes rely on a classic emergent property of random graphs (namely, the result of Erdos and Renyı [12, 37]
which assures a path between any pair of nodes with high probability after DSN deployment) to establish
secure node-to-node paths with a small number of shared keys per sensor node. Although anticipated, this
emergent property is probabilistic and its stability can only be guaranteed until a certain number of sensor
nodes fail (e.g., due to battery exhaustion) or are captured by an adversary. Hence, the disappearance of
secure node-to-node paths must be detected to enable connement of secure communication failures and
compromises to small subnetworks.
Example 3. Establishing Common Access States in Dynamic Coalitions.
Dynamic coalitions are peer-to-peer networks of autonomous domains that share resources to enable
the execution of common applications. The shared resources and their permissions are said to form the
common access state of the coalition members. Dynamic coalitions require repeated, on-line negotiations
to establish a common access state [21]. Since coalition membership varies dynamically, o-line, one-time
negotiation of sharing agreements on common access states are ruled out. Further, these negotiations are
dierent from typical client-server trust negotiations [36, 40], since these negotiations have dierent goals,
are peer-to-peer rather than client-server, and cannot necessarily be expected to terminate (successfully or
not) in a xed number of rounds. The negotiation of resource contributions to the common access state
may be conducted by each domain under dierent types of constraints, some of which cannot be revealed
to other members. The satisfaction of all individual constraints and the emergence of a common access
state by access negotiation is a desirable property. However, the emergence of the common access state may
have unintended, undesirable properties such as the unintended revealing of private resources or the private
negotiation constraints of a domain. Reaching a common access state in a dynamic coalition has the typical
characteristics of an emergent property. Although the locus of emergence can be anticipated, the time and
certainty of emergence cannot be guaranteed. Furthermore, the stability of the common access state can
only be guaranteed until a membership change (i.e., the dynamic departure or join of one or more domains).
Example 4. Establishing Secure Routes in Mobile Ad-hoc Networks using Swarm Intelligence
The notion of swarm intelligence has been used for a variety of routing problems [6, 7, 35], the most
recent of which is routing in mobile ad-hoc networks with resource-constrained nodes that change topology
frequently and have unpredictable connectivity [4, 31]. In such routing applications, autonomous agents
simulating ants discover routes between network nodes and construct a trail of local route information in
each node representing ants’ pheromone deposits. As with ant behavior, these autonomous agents proactively
explore and reinforce available routes by updating and propagating routing-table information among network
nodes in an attempt to accurately reect changing tra
c conditions and network connectivity. As a result
of the agent interaction via local route information, the shortest path between two nodes emerges. Routing
algorithms based on swarm intelligence can be executed in parallel and are scalable, fault-tolerant, and
adaptive. However, capture of mobile routing agents by an adversary leads to the denial of routes, while
injection of corrupted agents leads to the autocatalytic proliferation of false routes (i.e., routes which always
include the adversary’s nodes). Hence, in mobile ad-hoc networks where nodes are subject to capture by
adversaries, it becomes important to detect emergent false routes and malicious routing agents, and assess
their impact. Secure route establishment using swarm intelligence has all the typical characteristics of
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emergent properties: namely, neither the time nor the locus of (real or false) route emergence is anticipated,
and route emergence is uncertain and transient.
The common theme of most research in the security of emergent properties of ad-hoc networks is that
of a threat model whereby the adversary may compromise nodes in the network. Unlike most previous
research on ad-hoc networks which limits an adversary to “man-in-the-middle” attacks and relies on end-
to-end security solutions to counter such attacks [34], our research extends the threat model in two ways.
First, we allow that the adversary can, in fact, be one or more of the network nodes. This is clearly the case
since ad-hoc network nodes (e.g., sensors, mobile agents) often operate unattended in hostile environments.
Second, we allow that the impact of the adversary’s actions may extend to network nodes beyond those
captured, and that the adversary’s actions cannot be detected by traditional network intrusion detection
techniques. This is true because emergent properties result from collaboration among multiple nodes and
hence a few miscreant nodes may aect others. It is also a necessary assumption because the communication
patterns of an adversary-operated node — which traditional network intrusion detection techniques focus on
— may be indistinguishable from those of a legitimate node. Although the resilience of dierent protocols
to captured client or server devices [26] and to Byzantine behavior of participants [25, 16] has been the
subject of prior work, the scope and nature of an adversary’s actions must be expanded. For instance, in
contrast to the usual client-server protocols, in ad-hoc networks it is often impractical to design protocols
that would neutralize the adversary’s actions so that other nodes are unaected. Furthermore, the behavior
of an adversary in this environment is not necessarily Byzantine; e.g., it is not necessarily directed toward
the disruption of a multi-party agreement protocol. Instead, the adversary may seek to corrupt data that
compromises the entire application in an undetectable manner. In fact, the adversary’s captured nodes may
collaborate and execute network protocols ipretending to be legitimate network nodes aiming to sabotage
network operation. In this setting, node-to-node and message authentication are insu
cient to counter such
attacks.
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