most citedGenerating Comprehensive Data with Protocol Fuzzing for Applying Deep Learning to Detect Network Attacks

2 citations · 3 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CR20202 cited

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…

cs.CR20191 cited

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…

cs.CR2019

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…

cs.CR2019

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…

cs.CR2019

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…