D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 73 Citations 32,339 244 World Ranking 694 National Ranking 419

Research.com Recognitions

Awards & Achievements

2018 - IEEE Fellow For contributions to the application of formal methods to security

2016 - ACM Fellow For contributions to verification, programming languages, and software engineering.

2014 - ACM Distinguished Member

Overview

What is he best known for?

The fields of study he is best known for:

  • Operating system
  • Programming language
  • Artificial intelligence

Somesh Jha spends much of his time researching Theoretical computer science, Computer security, Model checking, Malware and Data mining. His Theoretical computer science study integrates concerns from other disciplines, such as Finite-state machine, Algorithm, Programming language and State. In his study, which falls under the umbrella issue of Computer security, Blacklist, Spoofing attack and Computer network is strongly linked to The Internet.

His work deals with themes such as Distributed computing, Cryptography, Temporal logic, Boolean function and Binary decision diagram, which intersect with Model checking. The Malware study combines topics in areas such as Adversarial system, Adversary and Machine learning, Deep learning. His Data mining research is multidisciplinary, incorporating perspectives in Process, Set, Cluster analysis, Exploit and Estimation.

His most cited work include:

  • The Limitations of Deep Learning in Adversarial Settings (1805 citations)
  • Practical Black-Box Attacks against Machine Learning (1521 citations)
  • Distillation as a Defense to Adversarial Perturbations Against Deep Neural Networks (1458 citations)

What are the main themes of his work throughout his whole career to date?

His scientific interests lie mostly in Theoretical computer science, Computer security, Artificial intelligence, Data mining and Adversarial system. Somesh Jha focuses mostly in the field of Theoretical computer science, narrowing it down to topics relating to Algorithm and, in certain cases, DFA minimization. His work in Malware, Intrusion detection system, Computer security model, Security service and Cryptography is related to Computer security.

In most of his Artificial intelligence studies, his work intersects topics such as Machine learning. Data mining connects with themes related to Signature in his study. Somesh Jha has researched Model checking in several fields, including Distributed computing, State space and Temporal logic.

He most often published in these fields:

  • Theoretical computer science (21.93%)
  • Computer security (21.05%)
  • Artificial intelligence (14.62%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (14.62%)
  • Artificial neural network (8.48%)
  • Robustness (7.60%)

In recent papers he was focusing on the following fields of study:

His main research concerns Artificial intelligence, Artificial neural network, Robustness, Adversarial system and Theoretical computer science. Somesh Jha interconnects Machine learning and Key in the investigation of issues within Artificial intelligence. His Robustness research incorporates themes from Discrete mathematics and Adversary.

His Adversarial system research includes themes of Class, Pixel and Statistical classification. Somesh Jha has included themes like Space, Differential privacy and Dimension in his Theoretical computer science study. His research in Adversarial machine learning intersects with topics in Contextual image classification and Computer security.

Between 2018 and 2021, his most popular works were:

  • Locally Differentially Private Heavy Hitter Identification (27 citations)
  • Answering Multi-Dimensional Analytical Queries under Local Differential Privacy (25 citations)
  • Robust Attribution Regularization (17 citations)

In his most recent research, the most cited papers focused on:

  • Operating system
  • Programming language
  • Artificial intelligence

The scientist’s investigation covers issues in Artificial intelligence, Machine learning, Differential privacy, Robustness and Artificial neural network. His work on Adversarial system, Deep learning and Inference as part of general Artificial intelligence study is frequently linked to Attribution, therefore connecting diverse disciplines of science. His Machine learning research includes elements of Clinical decision support system and Training set.

As a part of the same scientific family, Somesh Jha mostly works in the field of Differential privacy, focusing on Server and, on occasion, Distributed computing, Class, Software framework and Encryption. In his research, Encoding, Adversary and Code is intimately related to Theoretical computer science, which falls under the overarching field of Robustness. His study in Artificial neural network is interdisciplinary in nature, drawing from both Time complexity, Statistical classification and Cryptography.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

The Limitations of Deep Learning in Adversarial Settings

Nicolas Papernot;Patrick McDaniel;Somesh Jha;Matt Fredrikson.
ieee european symposium on security and privacy (2016)

1609 Citations

Automated generation and analysis of attack graphs

O. Sheyner;J. Haines;S. Jha;R. Lippmann.
ieee symposium on security and privacy (2002)

1577 Citations

Distillation as a Defense to Adversarial Perturbations Against Deep Neural Networks

Nicolas Papernot;Patrick McDaniel;Xi Wu;Somesh Jha.
ieee symposium on security and privacy (2016)

1214 Citations

Practical Black-Box Attacks against Machine Learning

Nicolas Papernot;Patrick McDaniel;Ian Goodfellow;Somesh Jha.
computer and communications security (2017)

1213 Citations

Counterexample-guided abstraction refinement for symbolic model checking

Edmund Clarke;Orna Grumberg;Somesh Jha;Yuan Lu.
Journal of the ACM (2003)

1050 Citations

Semantics-aware malware detection

M. Christodorescu;S. Jha;S.A. Seshia;D. Song.
ieee symposium on security and privacy (2005)

975 Citations

Static analysis of executables to detect malicious patterns

Mihai Christodorescu;Somesh Jha.
usenix security symposium (2003)

821 Citations

Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures

Matt Fredrikson;Somesh Jha;Thomas Ristenpart.
computer and communications security (2015)

681 Citations

Two formal analyses of attack graphs

S. Jha;O. Sheyner;J. Wing.
ieee computer security foundations symposium (2002)

675 Citations

Modular verification of software components in C

S. Chaki;E.M. Clarke;A. Groce;S. Jha.
IEEE Transactions on Software Engineering (2004)

647 Citations

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Best Scientists Citing Somesh Jha

Edmund M. Clarke

Edmund M. Clarke

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Peng Liu

Peng Liu

Chinese Academy of Sciences

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Sushil Jajodia

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Yang Liu

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Daniel Kroening

Daniel Kroening

Amazon (United States)

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Yuval Elovici

Yuval Elovici

Ben-Gurion University of the Negev

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Angelos D. Keromytis

Angelos D. Keromytis

Georgia Institute of Technology

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Lingyu Wang

Lingyu Wang

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Michael K. Reiter

Michael K. Reiter

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Wenke Lee

Wenke Lee

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Christopher Kruegel

Christopher Kruegel

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Patrick McDaniel

Patrick McDaniel

Pennsylvania State University

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Helmut Veith

Helmut Veith

TU Wien

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