1. Design, Analysis, and
Implementation of ARPKI: an Attack-Resilient Public-Key Infrastructure
Abstract: The current Transport
Layer Security (TLS) Public-Key Infrastructure (PKI) is based on a weakest-link
security model that depends on over a thousand trust roots. The recent history
of malicious and compromised Certification Authorities has fueled the desire
for alternatives. Creating a new, secure infrastructure is, however, a
surprisingly challenging task due to the large number of parties involved and
the many ways that they can interact. A principled approach to its design is
therefore mandatory, as humans cannot feasibly consider all the cases that can
occur due to the multitude of interleavings of actions by legitimate parties
and attackers, such as private key compromises (e.g., domain,
Certification Authority, log server, other trusted entities), key revocations,
key updates, etc. We present ARPKI, a PKI architecture that ensures that
certificate-related operations, such as certificate issuance, update,
revocation, and validation, are transparent and accountable. ARPKI efficiently
supports these operations, and gracefully handles catastrophic events such as
domain key loss or compromise. Moreover ARPKI is the first PKI architecture
that is co-designed with a formal model, and we verify its core security
property using the TAMARIN prover. We prove that ARPKI offers extremely strong
security guarantees, where compromising even n _ 1 trusted signing and
verifying entities is insufficient to launch a man-in-the-middle attack.
Moreover, ARPKI’s use deters misbehavior as all operations are publicly
visible. Finally, we present a proof-of-concept implementation that provides
all the features required for deployment. Our experiments indicate that ARPKI
efficiently handles the certification process with low overhead. It does not
incur additional latency to TLS, since no additional round trips are required.
2. CSC-Detector: A System
to Infer Large-Scale Probing Campaigns
Abstract:
This
paper uniquely leverages unsolicited real darknet data to propose a novel
system, CSC-Detector, that aims at identifying Cyber Scanning Campaigns. The
latter define a new phenomenon of probing events that are distinguished by
their orchestration (i.e., coordination) patterns. To achieve its aim,
CSC-Detector adopts three engines. Its fingerprinting engine exploits a unique
observation to extract probing activities from darknet traffic. The system’s
inference engine employs a set of behavioral analytics to generate numerous
significant insights related to the machinery of the probing sources while its
analysis engine exploits the previously obtained inferences to automatically
infer the campaigns. CSC-Detector is empirically evaluated and validated using
240 GB of real darknet data. The outcome discloses 3 recent, previously
unreported large-scale probing campaigns targeting diverse Internet services.
Further, one of those inferred campaigns revealed that the sipscan campaign
that was initially analyzed by CAIDA is arguably still active, yet operating in
a stealthy, very low rate mode. We envision that the proposed system that is
tailored towards darknet data, which is frequently, abundantly and effectively
used to generate cyber threat intelligence, could be used by network security
analysts, emergency response teams and/or observers of cyber events to infer
large-scale orchestrated probing campaigns. This would be utilized for early
cyber attack warning and notification as well as for simplified analysis and
tracking of such events.
3.
D2FL: Design and Implementation of Distributed Dynamic Fault Localization
Abstract: Compromised or
misconfigured routers have been a major concern in large-scale networks. Such
routers sabotage packet delivery, and thus hurt network performance. Data-plane
fault localization (FL) promises to solve this problem. Regrettably, the
path-based FL fails to support dynamic routing, and the neighbor-based FL
requires a centralized trusted administrative controller (AC) or global
clock synchronization in each router and introduces storage
overhead for caching packets. To address these problems, we introduce a
dynamic distributed and low-cost model, D2FL. Using random 2-hop neighborhood
authentication, D2FL supports volatile path without the AC or global clock
synchronization. Besides, D2FL requires only constant tens of KB for caching
which is independent of the packet transmission rate. This is much less than
the cache size of DynaFL or DFL which consumes several MB. The simulations show
that D2FL achieves low false positive and false negative rate with no more than
3% bandwidth overhead. We also implement an open source prototype and evaluate
its effect. The result shows that the performance burden in user space is less
than 10% with the dynamic sampling algorithm.
4. Conditional (t; k)-Diagnosis in Regular
and Irregular Graphs Under the Comparison Diagnosis Model
Abstract: Assume that there are at
most t faulty vertices. A system is conditionally (t;
k)-diagnosable if at least k faulty vertices (or all
faulty vertices if fewer than k faulty vertices remain) can be
identified in each iteration under the assumption that every vertex is adjacent
to at least one fault-free vertex. Let _c(G) be the conditional
vertex connectivity of G, which measures the vertex
connectivity of G according to the assumption that every
vertex is adjacent to at least one fault-free vertex. Let Δ(G) be the
maximum degrees of the given graph G. When a graph G satisfies
the condition that for any pair of vertices with distance two has at least two
common neighbors in G, we show the following two results: 1)
An r-regular network G containing N vertices
is conditionally N+ √ 4_(G)N (r+1)(r1) 2 r+1 ;
_c(G) -diagnosable, where r _ 3 and N
_ (r+1)(25r9) 4_(G) . 2) An
irregular network G containing N vertices is
conditionally ( N Δ(G)+1 1;
_c(G) ) -diagnosable. By applying the above results to
multiprocessor systems, we can measure conditional (t; k)-diagnosabilities
for augmented cubes, folded hypercubes, balanced hypercubes, and exchanged
hypercubes.
5.
On the Efficiency of FHE-based Private Queries
Abstract: Private query processing
is a very attractive problem in the fields of both cryptography and databases.
In this work, we restrict our attention to the efficiency aspect of the
problem, particularly for basic queries with conditions on various combinations
of equality. Without loss of generality, these conditions can be regarded as a
Boolean function, and this Boolean function can then be evaluated at
ciphertexts produced by a fully homomorphic encryption (FHE) scheme without
decryption. From the efficiency perspective, the remaining concern is to
efficiently test the equality function without severely downgrading the
performance of FHE-based querying solutions.
To this end, we first
analyze the multiplicative depth required for an equality test algorithm with
respect to the plaintext space inhabited by general FHE schemes. The primary
reason for this approach is that given an equality test algorithm, its
efficiency is measured in terms of the multiplicative depth required to
construct its arithmetic circuit expression. Indeed, the implemented equality
test algorithm dominates the entire performance of FHE-based query solutions,
apart from the performance of the underlying FHE scheme. Then, we measure the
multiplicative depth considering an FHE scheme that takes an extension field as
its plaintext space and that supports the depth-free evaluation of Frobenius
maps. According to our analysis, when the plaintext space of an FHE scheme is a
field of characteristic 2, the equality test algorithm for `-bit messages
requires the lowest multiplicative depth dlog `e. Furthermore, we design a set
of private query protocols for conjunctive, disjunctive, and threshold queries
based on the equality test algorithm. Similarly, applying the equality test
algorithm over F2` , our querying protocols require the minimum depths. More
specifically, a multiplicative depth of dlog `e + dlog (1 + _)e is required for
conjunctive and disjunctive queries, and a depth of dlog `e + 2dlog (1 + _)e is
required for threshold conjunctive queries, when their query conditions have _
attributes to be compared. Finally, we provide a communication-efficient
version of our solutions, though with additional computational costs, when an upper
bound _ (0 _ _ _ 1) on the selectivity of a database is given. Consequently, we
reduce the communication cost from n to approximately b_nc ciphertexts with
dlog ne additional depth when the database consists of n tuples.
Abstract: Ubiquitous computing is
resulting in a proliferation of cyber-physical systems (CPS) that host or
manage valuable physical and digital assets. These assets can be harmed by malicious
agents through both cyber-enabled or physically-enabled attacks, particularly
ones that exploit the often ignored interplay between the cyber and physical
world. The explicit representation of spatial topology is key to supporting
adaptive security policies. In this paper we explore the use of Bigraphical
Reactive Systems to model the topology of cyber and physical spaces and their
dynamics. We utilise such models to perform speculative threat analysis through
model checking to reason about the consequences of the evolution of topological
configurations on the satisfaction of security requirements. We further propose
an automatic planning technique to identify an adaptation strategy enacting
security policies at runtime to prevent, circumvent, or mitigate possible
security requirements violations. We evaluate our approach using a case study
concerned with countering insider threats in a building automation system.
7. Physical Attestation
in the Smart Grid for Distributed State Verification
Abstract: A cyber-physical system
(CPS) integrates a physical infrastructure with cyber computation for improved
performance and reliability. Most CPSs are distributed systems in which several
cyber processes cooperate to control a set of physical resources. An individual
process does not have the complete system state, and must communicate over some
network to share information with its peers. It is vital that processes share
accurate state information to ensure that the distributed system makes the
correct control decisions. Failure in a CPS can result in physical consequences
such as damage to the machines or harm to the humans involved in the system
operation. These consequences can be severe in critical infrastructures such as
water distribution, transportation, or the electric power grid.
8. Rmind: a Tool for
Cryptographically Secure Statistical Analysis
Abstract: Secure multi-party
computation is a practical cryptographic method for processing confidential
data. Research progress has led to its use in privacy-preserving statistical
analysis. Implementations of simple statistical analysis functions have been
published, but no comprehensive tool has been built. We describe and implement
a suite of most used statistical analysis functions in the privacy-preserving
setting including simple statistics, t-test, chi-squared test, Wilcoxon tests
and linear regression. We give descriptions of the privacy-preserving
algorithms and benchmark results that show an order of magnitude improvement
over previous work.
9. Rumor Source Identification
in Social Networks with Time-varying Topology
Abstract: Identifying rumor sources
in social networks plays a critical role in limiting the damage caused by them
through the timely quarantine of the sources. However, the temporal variation
in the topology of social networks and the ongoing dynamic processes challenge
our traditional source identification techniques that are considered in static
networks. In this paper, we borrow an idea from criminology and propose a novel
method to overcome the challenges. First, we reduce the time-varying networks
to a series of static networks by introducing a time-integrating window.
Second, instead of inspecting every individual in traditional techniques, we
adopt a reverse dissemination strategy to specify a set of suspects of the real
rumor source. This process addresses the scalability issue of source
identification problems, and therefore dramatically promotes the efficiency of
rumor source identification. Third, to determine the real source from the suspects,
we employ a novel microscopic rumor spreading model to calculate the maximum
likelihood (ML) for each suspect. The one who can provide the largest ML
estimate is considered as the real source. The evaluations are carried out on
real social networks with time-varying topology. The experiment results show
that our method can reduce 60% − 90% of the source seeking area in various
time-varying social networks. The results further indicate that our method can
accurately identify the real source, or an individual who is very close to the
real source. To the best of our knowledge, the proposed method is the first
that can be used to identify rumor sources in time-varying social networks.
10. SieveQ: A Layered BFT
Protection System for Critical Services
Abstract: Firewalls play a crucial
role in assuring the security of today’s critical infrastructures, forming a
first line of defense by being placed strategically at the front-end of the
networks. Sometimes, however, they have exploitable weaknesses, allowing an
adversary to bypass them in different ways. Therefore, their design should
include improved resilience capabilities to allow them to operate correctly in
highly adverse environments. This paper proposes SieveQ, a message queue
service that protects and regulates the access to critical systems, in a way
similar to an application-level firewall. SieveQ achieves fault and intrusion
tolerance by employing an architecture based on two filtering layers, enabling
efficient removal of invalid messages at early stages and decreasing the costs
associated with Byzantine Fault-Tolerant (BFT) replication of previous
solutions. Our experimental evaluation shows that SieveQ improves existing
replicated-firewalls resilience in the presence of corrupted messages by faulty
nodes. Furthermore, it accommodates high loads, as it is able to handle sixteen
times more security events per second than what was processed by the SIEM
employed in the 2012 Summer Olympic Games.
11.
Symbolic Synthesis of Timed Models with Strict 2-Phase Fault Recovery
Abstract: In this article, we focus
on efficient synthesis of fault-tolerant timed models from their
fault-intolerant version. Although the complexity of the synthesis problem is
known to be polynomial time in the size of the time-abstract bisimulation of
the input model, the state of the art currently lacks synthesis algorithms that
can be efficiently implemented. This is in part due to the fact that synthesis
is in general a challenging problem and its complexity is significantly
magnified in the context of timed systems. We propose an algorithm that takes
as input a timed automaton, a set of fault actions, and a set of safety and
bounded-time response properties, and utilizes a space-efficient symbolic
representation of the timed automaton (called z one graph) to synthesize a
fault-tolerant timed automaton as output. The output automaton satisfies strict
phased recovery, where it is guaranteed that the output model behaves similarly
to the input model in the absence of faults and in the presence of faults,
fault recovery is achieved in two phases, each satisfying certain safety and
timing constraints.
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