Neuzz: Efficient fuzzing with neural program smoothing

D She, K Pei, D Epstein, J Yang… - 2019 IEEE Symposium …, 2019 - ieeexplore.ieee.org
Fuzzing has become the de facto standard technique for finding software vulnerabilities.
However, even state-of-the-art fuzzers are not very efficient at finding hard-to-trigger …

Neuro-symbolic artificial intelligence: a survey

BP Bhuyan, A Ramdane-Cherif, R Tomar… - Neural Computing and …, 2024 - Springer
The goal of the growing discipline of neuro-symbolic artificial intelligence (AI) is to develop
AI systems with more human-like reasoning capabilities by combining symbolic reasoning …

Firmware vulnerabilities homology detection based on clonal selection algorithm for IoT devices

D He, X Yu, T Li, S Chan… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
With the wide application of Internet of Things (IoT) devices, security attacks against their
firmware often occur, which has attracted more attention from the research community …

[ΒΙΒΛΙΟ][B] Adaptive and Effective Fuzzing: a Data-Driven Approach

D She - 2023 - search.proquest.com
Security vulnerabilities have a large real-world impact, from ransomware attacks costing
billions of dollars every year to sensitive data breaches in government, military and industry …

DATA CONFIDENTIALITY FOR ALL: NEW METHODS IN ATTACK AND DEFENSE

MA Zinkus - 2024 - jscholarship.library.jhu.edu
For the past half-century since the advent of modern cryptography, perhaps most distinctly
demarcated by Diffie and Hellman in 1976, dramatic advances in cryptographic theory and …