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Arti Gupta

dblp:84/9998 · DBLP profile ↗
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5ranked-venue papers
3as first author
4since 2021 · last 2024
0000-0003-1783-1268ORCID · corroborated

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

Artificial intelligence and machine learning · 2 · 1 first-author · 1 since 2021Systems, architecture and hardware · 1 · 1 first-author · 1 since 2021Computer networks · 1 · 1 first-author · 1 since 2021Software engineering, systems software and programming languages · 1 · 1 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
1 paper
Systems and software security · 100%
Software engineering, system software, and programming languages
1 paper
Program verification · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Systems and software security
vulnerability discovery		 0.612022
Hardening attack surfaces with formally proven binary format parsers · PLDI 2022
Program verification › code-level verification
verified parsing		 0.612022
Hardening attack surfaces with formally proven binary format parsers · PLDI 2022

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

formal proof · 1.1
YearPublicationVenuePosition
2024 Integrating Healthcare 4.0 and WBAN: efficient redundancy reduction and adaptive packet scheduling using AR-DRL
Arti Gupta, Vijay Kumar Chaurasiya
 J. Supercomput.1
2023 ISTGCN: Integrated spatio-temporal modeling for traffic prediction using traffic graph convolution network
Arti Gupta, Manish Kumar Maurya, Nikhil Goyal, Vijay Kumar Chaurasiya
 Appl. Intell.1
2023 QoS supported redundancy balanced data transmission scheme for wireless body area network based H-IoT
Arti Gupta, Vijay Kumar Chaurasiya
 Wirel. Networks1
2022 Hardening attack surfaces with formally proven binary format parsers
abstract
With an eye toward performance, interoperability, or legacy concerns, low-level system software often must parse binary encoded data formats. Few tools are available for this task, especially since the formats involve a mixture of arithmetic and data dependence, beyond what can be handled by typical parser generators. As such, parsers are written by hand in languages like C, with inevitable errors leading to security vulnerabilities.
Nikhil Swamy, Tahina Ramananandro, Aseem Rastogi, Irina Spiridonova, Haobin Ni, Dmitry Malloy, Juan Vazquez, Michael Tang, Omar Cardona, Arti Gupta
 PLDI10
2011 A TENGRAM method based part-of-speech tagging of multi-category words in Hindi language
Devendra K. Tayal, Arti Gupta
 Expert Syst. Appl.3