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Abhishek Vasisht Bhaskar

dblp:172/8802 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none

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

Security and privacy · 3

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
Malware analysis · 69% Web and mobile security · 25% Systems and software security · 6%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Malware analysis
android unpacking
0.312018
Things You May Not Know About Android (Un)Packers: A Systematic Study based on Whole-System Emulation · NDSS 2018
Malware analysis › mobile malware
mobile malware analysis
0.312018
Things You May Not Know About Android (Un)Packers: A Systematic Study based on Whole-System Emulation · NDSS 2018
Web and mobile security
mobile security
0.312018
Things You May Not Know About Android (Un)Packers: A Systematic Study based on Whole-System Emulation · NDSS 2018
Malware analysis
malware detection
0.212016
Extract Me If You Can: Abusing PDF Parsers in Malware Detectors · NDSS 2016
Systems and software security
vulnerability discovery
0.112016
Extract Me If You Can: Abusing PDF Parsers in Malware Detectors · NDSS 2016

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

whole-system emulation · 0.3
YearPublicationVenuePosition
2018 Things You May Not Know About Android (Un)Packers: A Systematic Study based on Whole-System Emulation
Yue Duan, Mu Zhang 0001, Abhishek Vasisht Bhaskar, Heng Yin 0001, Xiaorui Pan, Tongxin Li 0002, Xueqiang Wang, XiaoFeng Wang 0001
NDSS3
2016 Extract Me If You Can: Abusing PDF Parsers in Malware Detectors
Curtis Carmony, Xunchao Hu, Heng Yin 0001, Abhishek Vasisht Bhaskar, Mu Zhang 0001
NDSS4
2015 Binary Code Continent: Finer-Grained Control Flow Integrity for Stripped Binaries
abstract
Control Flow Integrity (CFI) is an effective technique to mitigate threats such as code-injection and code-reuse attacks in programs by protecting indirect transfers. For stripped binaries, a CFI policy has to be made conservatively due to the lack of source code level semantics. Existing binary-only CFI solutions such as BinCFI and CCFIR demonstrate the ability to protect stripped binaries, but the policies they apply are too permissive, allowing sophisticated code-reuse attacks. In this paper, we propose a new binary-only CFI protection scheme called BinCC, which applies static binary rewriting to provide finer-grained protection for x86 stripped ELF binaries. Through code duplication and static analysis, we divide the binary code into several mutually exclusive code continents. We further classify each indirect transfer within a code continent as either an Intra-Continent transfer or an Inter-Continent transfer, and apply separate, strict CFI polices to constrain these transfers. To evaluate BinCC, we introduce new metrics to estimate the average amount of legitimate targets of each kind of indirect transfer as well as the difficulty to leverage call preceded gadgets to generate ROP exploits. Compared to the state of the art binary-only CFI, BinCFI, the experimental results show that BinCC significantly reduces the legitimate transfer targets by 81.34% and increases the difficulty for adversaries to bypass CFI restriction to launch sophisticated ROP attacks. Also, BinCC achieves a reasonable performance, around 14% of the space overhead decrease and only 4% runtime overhead increase as compared to BinCFI.
Heng Yin 0001, Abhishek Vasisht Bhaskar, Purui Su, Dengguo Feng
ACSAC3