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Hyeon Gy Shon

dblp:298/4026 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2023
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 2 · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
2 papers
Network security · 50% Systems and software security · 50%
Databases, data mining, and information retrieval
2 papers
Information retrieval · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Systems and software security › data security
data leakage prevention
1.222023
Packet Chunking for File Detection · IEEE/ACM Trans. Netw. 2023
Finding Critical Files from a Packet · INFOCOM 2021
Network security › intrusion detection and prevention
intrusion detection
1.222023
Packet Chunking for File Detection · IEEE/ACM Trans. Netw. 2023
Finding Critical Files from a Packet · INFOCOM 2021
Information retrieval › indexing
inverted file
0.322023
Packet Chunking for File Detection · IEEE/ACM Trans. Netw. 2023
Finding Critical Files from a Packet · INFOCOM 2021

Methods — techniques the papers use, named apart from their topics

content-based chunking · 2.3bloom filter · 2.3two-level threshold · 1.3delayed query strategy · 1.0
YearPublicationVenuePosition
2023 Packet Chunking for File Detection
abstract
Network-based intrusion detection and data leakage prevention systems inspect packets to detect if critical files such as malware or confidential documents are transferred. However, this kind of detection requires heavy computing resources in reassembling packets and only well-known protocols can be interpreted. Besides, finding similar files from a storage requires pairwise comparisons. In this paper, we present a new network-based file identification scheme that inspects packets independently without reassembly and finds similar files through inverted indexing instead of pairwise comparison. We use a content-based chunking algorithm to consistently divide both files and packets into multiple byte sequences, called chunks. If a packet is a part of a file, they would have common chunks. The challenging problem is that packet chunking and inverted-index search should be fast and scalable enough for packet processing. The file identification should be accurate although many chunks are noises. In this paper, we use a small Bloom filter and a two-level threshold strategy to solve the problems. To the best of our knowledge, this is the first scheme that identifies a specific critical file from a packet over unknown protocols. Experimental results show that the proposed scheme can successfully identify a critical file from a packet without packet reassembly.
JunNyung Hur, Hyeon Gy Shon, Young Jae Kim, MyungKeun Yoon 0001
IEEE/ACM Trans. Netw.2
2021 Finding Critical Files from a Packet
abstract
Network-based intrusion detection and data leakage prevention systems inspect packets to detect if critical files such as malware or confidential documents are transferred. However, this kind of detection requires heavy computing resources in reassembling packets and only well-known protocols can be interpreted. Besides, finding similar files from a storage requires pairwise comparisons. In this paper, we present a new network-based file identification scheme that inspects packets independently without reassembly and finds similar files through inverted indexing instead of pairwise comparison. We use a contents-based chunking algorithm to consistently divide both files and packets into multiple byte sequences, called chunks. If a packet is a part of a file, they would have common chunks. The challenging problem is that packet chunking and inverted-index search should be fast and scalable enough for packet processing. The file identification should be accurate although many chunks are noises. In this paper, we use a small Bloom filter and a delayed query strategy to solve the problems. To the best of our knowledge, this is the first scheme that identifies a specific critical file from a packet over unknown protocols. Experimental results show that the proposed scheme can successfully identify a critical file from a packet.
JunNyung Hur, Hahoon Jeon, Hyeon Gy Shon, Young Jae Kim, MyungKeun Yoon 0001
INFOCOM3