SelectedWorks - Thomas H. Austin

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Selected Works of Thomas H. Austin

Assistant Professor, Computer Science

Dr. Austin is an Assistant Professor in the Department of Computer Science at San José State University.

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About Thomas H. Austin

Dr. Austin is an Assistant Professor in the Department of Computer Science at San José State University.

Contribution to Book

Designing a Secure Programming Language

Handbook of Information and Communication Security (2010)

Thomas H. Austin

In this chapter, we will review security issues from the perspective of a language designer. Preventing inexperienced or careless programmers ...

Articles (17)

TontineCoin: Survivor-based Proof-of-Stake

Peer-to-Peer Networking and Applications (2022)

Chris Pollett, Thomas H. Austin, Katerina Potika, Justin Rietz, et al.

Proof-of-Stake cryptocurrencies avoid many of the computational and environmental costs associated with Proof-of-Work protocols. However, they must address the nothing-at-stake ...

A Blockchain-Based Tamper-Resistant Logging Framework

Communications in Computer and Information Science (2022)

Thomas H. Austin and Fabio Di Troia

Since its introduction in Bitcoin, the blockchain has proven to be a versatile data structure. In its role as an ...

Crowdfunding Non-fungible Tokens on the Blockchain

Communications in Computer and Information Science (2022)

Sean Basu, Kimaya Basu and Thomas H. Austin

Non-fungible tokens (NFTs) have been used as a way of rewarding content creators. Artists publish their works on the blockchain ...

BioBlockchain: Useful Proof-of-Work with Multiple Sequence Alignment

Communications in Computer and Information Science (2021)

Yan Chen, Thomas H. Austin and Philip Heller

Although Bitcoin is a successful electronic cash system, mining bitcoin wastes computation resources since the proof-of-work requires the miners to ...

SpartanGold: A Blockchain for Education, Experimentation, and Rapid Prototyping

Communications in Computer and Information Science (2021)

Thomas H. Austin

Since the introduction of Bitcoin and the blockchain, the cryptocurrency space has seen rapid innovation in both academic research and ...

Clustering for malware classification

Journal of Computer Virology and Hacking Techniques (2017)

Swathi Pai, Fabio Di Troia, Corrado Aaron Visaggio, Thomas H. Austin, et al.

In this research, we apply clustering techniques to the malware classification problem. We compute clusters using the well-known K-means and Expectation ...

A comparison of static, dynamic, and hybrid analysis for malware ...

Journal of Computer Virology and Hacking Techniques (2017)

Anusha Damodaran, Fabio Di. Troia, Corrado A. Vissagio, Thomas H. Austin, et al.

In this research, we compare malware detection techniques based on static, dynamic, and hybrid analysis. Specifically, we train Hidden Markov ...

SocioBot: a Twitter-based botnet

International Journal of Security and Networks (2017)

Thomas H. Austin

A botnet is a collection of computers controlled by a botmaster, often used for malicious activity. Social media provides an ...

Clustering versus SVM for malware detection

Journal of Computer Virology and Hacking Techniques (2016)

Usha Narra, Fabio Di Troia, Visaggio Aaron Corrado, Thomas H. Austin, et al.

Previous work has shown that cluster analysis can be used to effectively classify malware into meaningful families. In this research, ...

Precise, dynamic information flow for database-backed applications

ACM SIGPLAN Notices (2016)

Jean Yang, Travis Hance, Thomas H. Austin, Armando Solar-Lezama, et al.

We present an approach for dynamic information flow control across the application and database. Our approach reduces the amount of ...

Support vector machines and malware detection

Journal of Computer Virology and hacking Techniques (2016)

Mark Stamp, Tanuvir Singh, Fabio Di Troia, Visaggio A. Corrado, et al.

In this research, we test three advanced malware scoring techniques that have shown promise in previous research, namely, Hidden Markov ...

Singular value decomposition and metamorphic detection

Journal of Computer Virology and Hacking Techniques (2015)

Ranjith Kumar Jidigam, Thomas H. Austin and Mark Stamp

Metamorphic malware changes its internal structure with each infection, while maintaining its original functionality. Such malware can be difficult to ...

Compression-based analysis of metamorphic malware

International Journal of Security and Networks (2015)

Jared Lee, Thomas H. Austin and Mark Stamp

Recent work has shown that a technique based on structural entropy measurement provides an effective means of detecting metamorphic malware. ...

Dueling hidden Markov Models for virus analysis

Journal of Computer Virology and Hacking Techniques (2014)

Ashwin Kalbhor, Thomas H. Austin, Eric Filiol, S'ebastien Josse, et al.

Recent work has presented hidden Markov models (HMMs) as a compelling option for malware identification. However, some advanced metamorphic malware ...

Hidden Markov models for malware classification

Journal of Computer Virology and Hacking Techniques (2014)

Chinmayee Annachhatre, Thomas H. Austin and Mark Stamp

Previous research has shown that hidden Markov model (HMM) analysis is useful for detecting certain challenging classes of malware. In ...

Hunting for Metamorphic JavaScript malware

Journal of Computer Virology and Hacking Techniques (2014)

Mangesgh Musale, Thomas H. Austin and Mark Stamp

The Internet plays a major role in the propagation of malware. A recent trend is the infection of machines through ...

Metamorphic code generation from LLVM bytecode

Journal of Computer Virology and Hacking Techniques (2013)

Teja Tamboli, Thomas H. Austin and Mark Stamp

Metamorphic software changes its internal structure across generations with its functionality remaining unchanged. Metamorphism has been employed by malware writers ...

Contribution to Book

SharedWealth: Disincentivizing Mining Pools Through Burning and Minting

Business Information Systems Workshops, BIS 2020 (2020)

Thomas H. Austin, Paul Merrill and Justin Rietz

Bitcoin has provided a framework for a decentralized currency system. However, the irregular payouts of its winner-takes-all reward strategy have ...

Contribution to Book

TontineCoin: Murder-Based Proof-of-Stake

2020 IEEE International Conference on Decentralized Applications and Infrastructures (DAPPS) (2020)

Chris Pollett, Thomas H. Austin, Katerina Potika and Justin Rietz

Proof-of-stake cryptocurrencies avoid many of the computational and environmental costs associated with proof-of-work protocols. However, they must address the nothing-at-stake ...

Contribution to Book

Ping-Pong Governance: Token Locking for Enabling Blockchain Self-governance

Mathematical Research for Blockchain Economy (2020)

Paul Merrill, Thomas H. Austin, Justin Rietz and Jon Pearce

Updating blockchain-based protocols remains a significant challenge. If the community does not come to an agreement, a hard-fork can occur, ...

Lock and Load: A Model for Free Blockchain Transactions through ...

2019 IEEE International Conference on Decentralized Applications and Infrastructures (DAPPCON) (2019)

Paul Merrill, Thomas H. Austin, Jenil Thakker, Younghee Park, et al.

Bitcoin introduced the world to blockchain-based cryptocurrencies, and Ethereum highlighted their value in building distributed applications (dApps). However, the development ...

Autocorrelation Analysis of Financial Botnet Traffic

2nd International Workshop on Formal Methods for Security Engineering (ForSE 2018) (2018)

Prathiba Nagarajan, Fabio Di. Troia, Thomas H. Austin and Mark Stamp

A botnet consists of a network of infected computers that can be controlled remotely via a command and control (C&C) ...

Using Precise Taint Tracking for Auto-sanitization

PLAS 2017 - Proceedings of the 2017 Workshop on Programming Languages and Analysis for Security, co-located with CCS 2017 (2017)

Tejas Saoji, Thomas H. Austin and Cormac Flanagan

Taint analysis has been used in numerous scripting languages such as Perl and Ruby to defend against various form of ...

Contribution to Book

Advanced Transcriptase for JavaScript Malware

MALCON 2016 (2016)

Mark Stamp, Fabio Di Troia, Visaggio Aaron Corrado and Thomas H. Austin