In recent years, mobile apps have become the infrastructure of many popular Internet services. It is now fairly common that a mobile app serves a large number of users across the globe. Different from web- based services whose important program logic is mostly placed on remote servers, many mobile apps require complicated client-side code to perform tasks that are critical to the businesses. The code of mobile apps can be easily accessed by any party after the software is installed on a rooted or jailbroken device. By examining the code, skilled reverse engineers can learn various knowledge about the design and implementation of an app. Real-world cases have shown that the disclosed critical information allows malicious parties to abuse or exploit the app-provided services for unrightful profits, leading to significant financial losses for app vendors.
One of the most viable mitigations against malicious reverse engineering is to obfuscate the software before release. Despite that security by obscurity is typically considered to be an unsound protection methodology, software obfuscation can indeed increase the cost of reverse engineering, thus delivering practical merits for protecting mobile apps.
In this paper, we share our experience of applying obfuscation to multiple commercial iOS apps, each of which has millions of users. We discuss the necessity of adopting obfuscation for protecting modern mobile business, the challenges of software obfuscation on the iOS platform, and our efforts in overcoming these obstacles. Our report can benefit many stakeholders in the iOS ecosystem, including developers, security service providers, and Apple as the administrator of the ecosystem.
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Polymorphic Circuit Generation Using Random Boolean Logic Expansion
Securing applications on untrusted platforms can involve protection
against legitimate end-users who act in the role of malicious
reverse engineers and hackers. Such adversaries have access to
the full execution environment of programs, whether the program
comes in the form of software or hardware. In this paper, we consider
the nature of obfuscating algorithms that perform iterative,
step-wise transformation of programs into more complex forms
that are intended to increase the complexity (time, resources) for
malicious reverse engineers. We consider simple Boolean logic
programs as the domain of interest and examine a specific transformation
technique known as iterative sub-circuit selection and
replacement (ISR), which represents a practical, syntactic approach
for obfuscation. Specifically, we focus on improving the security
of ISR by maximizing the flexibility and potential security of the
replacement step of the algorithm which can be formulated in the
following question: given a selection of Boolean logic gates (i.e., a
sub-circuit), how can we produce a semantically equivalent (polymorphic)
version of the sub-circuit such that the distribution of
potential replacements represents a random, uniform distribution
from the set of all possible replacements. This practical question
is related to the theoretic study of indistinguishability obfuscation,
where a transformer for a class of circuits guarantees that
given any two semantically equivalent circuits from the class, the
distribution of variants from their obfuscation are computationally
indistinguishable. Ideally, polymorphic circuits that follow a
random, uniform distribution provide stronger protection against
malicious analyzers that target identification of distinct patterns as
a basis for deobfuscation and simplification.
In this paper, we introduce a novel approach for polymorphic
circuit replacement called random Boolean logic expansion (RBLE),
which applies Boolean logic laws (of reduction) in reverse. We
compare this approach against another proposed method of polymorphic
replacement that relies on static circuit libraries. As a
contribution, we show the strengths and weaknesses of each approach,
examine initial results from empirical studies to estimate the
uniformity of polymorphic distributions, and provide the argument
for how such algorithms can be readily applied in software contexts.
RBLE provides a unique method to generate polymorphic variants
of arbitrary input, output, and gate size. We report initial findings
for studying variants produced by this method and, from empirical
evaluation, show that RBLE has promise for generating distributions
of unique, uniform circuits when size is unconstrained, but for
targeted size distributions, the approach requires some adjustment
in order to reach potential circuit variants.
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- Award ID(s):
- 1811578
- NSF-PAR ID:
- 10173571
- Date Published:
- Journal Name:
- 35th ACM/SIGAPP Symposium On Applied Computing
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3341105.3374031
