7 citations · 17 across the 6 of their papers we have counts for
6 papers
Generating Comprehensive Data with Protocol Fuzzing for Applying Deep Learning to Detect Network Attacks
Qingtian Zou, Anoop Singhal, Xiaoyan Sun +1
Network attacks have become a major security concern for organizations worldwide and have also drawn attention in the academics. Recently, researchers have applied neural networks…
Semantic-preserving Reinforcement Learning Attack Against Graph Neural Networks for Malware Detection
Lan Zhang, Peng Liu, Yoon-Ho Choi +1
As an increasing number of deep-learning-based malware scanners have been proposed, the existing evasion techniques, including code obfuscation and polymorphic malware, are found t…
Logic Bugs in IoT Platforms and Systems: A Review
Wei Zhou, Chen Cao, Dongdong Huo +9
In recent years, IoT platforms and systems have been rapidly emerging. Although IoT is a new technology, new does not mean simpler (than existing networked systems). Contrarily, th…
Using Deep Learning to Solve Computer Security Challenges: A Survey
Yoon-Ho Choi, Peng Liu, Zitong Shang +5
Although using machine learning techniques to solve computer security challenges is not a new idea, the rapidly emerging Deep Learning technology has recently triggered a substanti…
GPT Conjecture: Understanding the Trade-offs between Granularity, Performance and Timeliness in Control-Flow Integrity
Zhilong Wang, Peng Liu
Performance/security trade-off is widely noticed in CFI research, however, we observe that not every CFI scheme is subject to the trade-off. Motivated by the key observation, we as…
Good Motive but Bad Design: Why ARM MPU Has Become an Outcast in Embedded Systems
Wei Zhou, Le Guan, Peng Liu +1
As more and more embedded devices are connected to the Internet, leading to the emergence of Internet-of-Things (IoT), previously less tested (and insecure) devices are exposed to…