Angora: Efficient fuzzing by principled search
P Chen, H Chen - 2018 IEEE Symposium on Security and …, 2018 - ieeexplore.ieee.org
Fuzzing is a popular technique for finding software bugs. However, the performance of the
state-of-the-art fuzzers leaves a lot to be desired. Fuzzers based on symbolic execution …
state-of-the-art fuzzers leaves a lot to be desired. Fuzzers based on symbolic execution …
PermPair: Android Malware Detection Using Permission Pairs
The Android smartphones are highly prone to spreading the malware due to intrinsic
feebleness that permits an application to access the internal resources when the user grants …
feebleness that permits an application to access the internal resources when the user grants …
Deeprefiner: Multi-layer android malware detection system applying deep neural networks
As malicious behaviors vary significantly across mobile malware, it is challenging to detect
malware both efficiently and effectively. Also due to the continuous evolution of malicious …
malware both efficiently and effectively. Also due to the continuous evolution of malicious …
Droidevolver: Self-evolving android malware detection system
Given the frequent changes in the Android framework and the continuous evolution of
Android malware, it is challenging to detect malware over time in an effective and scalable …
Android malware, it is challenging to detect malware over time in an effective and scalable …
Diane: Identifying fuzzing triggers in apps to generate under-constrained inputs for iot devices
Internet of Things (IoT) devices have rooted themselves in the everyday life of billions of
people. Thus, researchers have applied automated bug finding techniques to improve their …
people. Thus, researchers have applied automated bug finding techniques to improve their …
Monet: a user-oriented behavior-based malware variants detection system for android
Android, the most popular mobile OS, has around 78% of the mobile market share. Due to its
popularity, it attracts many malware attacks. In fact, people have discovered around 1 million …
popularity, it attracts many malware attacks. In fact, people have discovered around 1 million …
{CacheD}: Identifying {Cache-Based} timing channels in production software
Side-channel attacks recover secret information by analyzing the physical implementation of
cryptosystems based on non-functional computational characteristics, eg time, power, and …
cryptosystems based on non-functional computational characteristics, eg time, power, and …
EveDroid: Event-aware Android malware detection against model degrading for IoT devices
With the proliferation of the smart Internet of Things (IoT) devices based on Android system,
malicious Android applications targeting for IoT devices have received more and more …
malicious Android applications targeting for IoT devices have received more and more …
Jucify: A step towards android code unification for enhanced static analysis
Native code is now commonplace within Android app packages where it co-exists and
interacts with Dex bytecode through the Java Native Interface to deliver rich app …
interacts with Dex bytecode through the Java Native Interface to deliver rich app …
Jn-saf: Precise and efficient ndk/jni-aware inter-language static analysis framework for security vetting of android applications with native code
Android allows application developers to use native language (C/C++) to implement a part
or the complete program. Recent research and our own statistics show that native payloads …
or the complete program. Recent research and our own statistics show that native payloads …