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ORCIDRakesh M. Verma
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- affiliation: University of Houston, USA
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2020 – today
- 2024
[c88]Fatima Zahra Qachfar, Bryan Tuck, Rakesh M. Verma:
DetectiveReDASers at HSD-2Lang 2024: A New Pooling Strategy with Cross-lingual Augmentation and Ensembling for Hate Speech Detection in Low-resource Languages. CASE 2024: 199-204- [c87]Dainis Boumber
, Bryan E. Tuck, Rakesh M. Verma, Fatima Zahra Qachfar:
LLMs for Explainable Few-shot Deception Detection. IWSPA@CODASPY 2024: 37-47 - [c86]Casey Hanks, Shanina Ko, Emily Nguyen, Rakesh M. Verma:
Domain Independent Deception Detection: Feature Sets, LIWC Efficacy, and Synthetic Data Challenges. IWSPA@CODASPY 2024: 59-68 - [c85]Dainis Boumber, Fatima Zahra Qachfar, Rakesh M. Verma:
Domain-Agnostic Adapter Architecture for Deception Detection: Extensive Evaluations with the DIFrauD Benchmark. LREC/COLING 2024: 5260-5274 - [c84]Fatima Zahra Qachfar, Rakesh M. Verma:
All Your LLMs Belong to Us: Experiments with a New Extortion Phishing Dataset. DBSec 2024: 241-258 - [c83]Vu Minh Hoang Dang, Rakesh M. Verma:
Data Quality in NLP: Metrics and a Comprehensive Taxonomy. IDA (1) 2024: 217-229 - [c82]Dainis Boumber, Rakesh M. Verma, Fatima Zahra Qachfar:
Blue Sky: Multilingual, Multimodal Domain Independent Deception Detection. SDM 2024: 396-399 - [e11]Hongxin Hu, Andrew H. Sung, Rakesh M. Verma:
Proceedings of the 10th ACM International Workshop on Security and Privacy Analytics, IWSPA 2024, Porto, Portugal, 21 June 2024. ACM 2024 [contents] - [i24]Rakesh M. Verma, Nachum Dershowitz, Victor Zeng, Dainis Boumber, Xuting Liu:
Domain-Independent Deception: A New Taxonomy and Linguistic Analysis. CoRR abs/2402.01019 (2024) - [i23]Fatima Zahra Qachfar, Rakesh M. Verma:
Homograph Attacks on Maghreb Sentiment Analyzers. CoRR abs/2402.03171 (2024) - [i22]Dainis Boumber, Rakesh M. Verma, Fatima Zahra Qachfar:
A Roadmap for Multilingual, Multimodal Domain Independent Deception Detection. CoRR abs/2405.03920 (2024) - [i21]Bryan E. Tuck, Rakesh M. Verma:
Unmasking the Imposters: In-Domain Detection of Human vs. Machine-Generated Tweets. CoRR abs/2406.17967 (2024) - [i20]Rakesh M. Verma, Nachum Dershowitz:
The Pitfalls of Publishing in the Age of LLMs: Strange and Surprising Adventures with a High-Impact NLP Journal. CoRR abs/2407.12026 (2024) - 2023
- [j35]Nachum Dershowitz, Rakesh M. Verma:
Rebutting Rebuttals. Commun. ACM 66(9): 35-41 (2023) - [j34]Samaneh Karimi, Azadeh Shakery, Rakesh M. Verma:
Enhancement of Twitter event detection using news streams. Nat. Lang. Eng. 29(2): 181-200 (2023) - [j33]Shahryar Baki, Rakesh M. Verma:
Sixteen Years of Phishing User Studies: What Have We Learned? IEEE Trans. Dependable Secur. Comput. 20(2): 1200-1212 (2023) - [c81]Parisa Mehdi Gholampour, Rakesh M. Verma:
Adversarial Robustness of Phishing Email Detection Models. IWSPA@CODASPY 2023: 67-76 - [c80]Yunpeng Jack Zhang, Kailai Wang, Lingguang Song, Amaury Lendasse, Houbing Herbert Song, Zhu Han, Rakesh M. Verma, Arlei Silva, Carlos E. Rubio-Medrano, Zhixia Richard Li, Guohui Zhang:
USDOT Tier-1 University Transportation Center for Advancing Cybersecurity Research and Education. MOST 2023: 237-241 - [c79]Fatima Zahra Qachfar, Rakesh M. Verma:
ReDASPersuasion at SemEval-2023 Task 3: Persuasion Detection using Multilingual Transformers and Language Agnostic Features. SemEval@ACL 2023: 2124-2132 - [c78]Bryan Tuck, Fatima Zahra Qachfar, Dainis Boumber, Rakesh M. Verma:
DetectiveRedasers at ArAIEval Shared Task: Leveraging Transformer Ensembles for Arabic Deception Detection. ArabicNLP 2023: 494-501 - [c77]Fatima Zahra Qachfar, Rakesh M. Verma:
ReDASPersuasion at ArAIEval Shared Task: Multilingual and Monolingual Models For Arabic Persuasion Detection. ArabicNLP 2023: 549-557 - [e10]David J. Marchette, Andrew H. Sung, Rakesh M. Verma:
Proceedings of the 9th ACM International Workshop on Security and Privacy Analytics, IWSPA@CODASPY 2023, Charlotte, NC, USA, 26 April 2023. ACM 2023 [contents] - 2022
- [c76]Xin Zhou, Rakesh M. Verma:
Vulnerability Detection via Multimodal Learning: Datasets and Analysis. AsiaCCS 2022: 1225-1227 - [c75]Casey Hanks, Rakesh M. Verma:
Data Quality and Linguistic Cues for Domain-independent Deception Detection. BDCAT 2022: 248-258 - [c74]Fatima Zahra Qachfar, Rakesh M. Verma, Arjun Mukherjee:
Leveraging Synthetic Data and PU Learning For Phishing Email Detection. CODASPY 2022: 29-40 - [c73]Victor Zeng, Xuting Liu, Rakesh M. Verma:
Does Deception Leave a Content Independent Stylistic Trace? CODASPY 2022: 349-351 - [c72]Xin Zhou, Rakesh M. Verma:
Software Vulnerability Detection via Multimodal Deep Learning. STM 2022: 85-103 - [e9]Anupam Joshi, Maribel Fernández, Rakesh M. Verma:
CODASPY '22: Twelveth ACM Conference on Data and Application Security and Privacy, Baltimore, MD, USA, April 24 - 27, 2022. ACM 2022, ISBN 978-1-4503-9220-4 [contents] - [e8]Andrew H. Sung, Rakesh M. Verma, Roland H. C. Yap:
IWSPA@CODASPY 2022: Proceedings of the 2022 ACM on International Workshop on Security and Privacy Analytics, Baltimore, MD, USA, April 27, 2022. ACM 2022, ISBN 978-1-4503-9230-3 [contents] - [i19]Rakesh M. Verma, Nachum Dershowitz, Victor Zeng, Xuting Liu:
Domain-Independent Deception: Definition, Taxonomy and the Linguistic Cues Debate. CoRR abs/2207.01738 (2022) - 2021
- [j32]Samaneh Karimi, Azadeh Shakery, Rakesh M. Verma:
Online news media website ranking using user-generated content. J. Inf. Sci. 47(3) (2021) - [c71]Amartya Hatua, Arjun Mukherjee, Rakesh M. Verma:
On the Feasibility of Using GANs for Claim Verification- Experiments and Analysis. ROMCIR@ECIR 2021: 35-46 - [c70]Amartya Hatua, Arjun Mukherjee, Rakesh M. Verma:
Claim Verification Using a Multi-GAN Based Model. RANLP 2021: 494-503 - [c69]Rakesh M. Verma:
Capacity Expansion in Cybersecurity: Challenges and Prospects. SIGCSE 2021: 1277 - [c68]Rakesh M. Verma, Rangarajan Ray Parthasarathy, Lila Ghemri:
What is the Security Mindset? Can it be Developed? SIGCSE 2021: 1361 - [e7]Anupam Joshi, Barbara Carminati, Rakesh M. Verma:
CODASPY '21: Eleventh ACM Conference on Data and Application Security and Privacy, Virtual Event, USA, April 26-28, 2021. ACM 2021, ISBN 978-1-4503-8143-7 [contents] - [i18]Amartya Hatua, Arjun Mukherjee, Rakesh M. Verma:
Claim Verification using a Multi-GAN based Model. CoRR abs/2103.08001 (2021) - [i17]Shahryar Baki, Rakesh M. Verma:
Sixteen Years of Phishing User Studies: What Have We Learned? CoRR abs/2109.04661 (2021) - 2020
- [j31]Ayman El Aassal, Shahryar Baki, Avisha Das, Rakesh M. Verma:
An In-Depth Benchmarking and Evaluation of Phishing Detection Research for Security Needs. IEEE Access 8: 22170-22192 (2020) - [j30]Avisha Das, Rakesh M. Verma:
Can Machines Tell Stories? A Comparative Study of Deep Neural Language Models and Metrics. IEEE Access 8: 181258-181292 (2020) - [j29]Avisha Das, Shahryar Baki, Ayman El Aassal, Rakesh M. Verma, Arthur Dunbar:
SoK: A Comprehensive Reexamination of Phishing Research From the Security Perspective. IEEE Commun. Surv. Tutorials 22(1): 671-708 (2020) - [c67]Shahryar Baki, Rakesh M. Verma, Omprakash Gnawali:
Scam Augmentation and Customization: Identifying Vulnerable Users and Arming Defenders. AsiaCCS 2020: 236-247 - [c66]Victor Zeng, Xin Zhou, Shahryar Baki, Rakesh M. Verma:
PhishBench 2.0: A Versatile and Extendable Benchmarking Framework for Phishing. CCS 2020: 2077-2079 - [c65]Daniel Lee, Rakesh M. Verma:
Adversarial Machine Learning for Text. IWSPA@CODASPY 2020: 33-34 - [c64]Victor Zeng, Shahryar Baki, Ayman El Aassal, Rakesh M. Verma, Luis Felipe Teixeira De Moraes, Avisha Das:
Diverse Datasets and a Customizable Benchmarking Framework for Phishing. IWSPA@CODASPY 2020: 35-41 - [c63]Elisa Bertino, Anoop Singhal, Srivathsan Srinivasagopalan, Rakesh M. Verma:
Developing A Compelling Vision for Winning the Cybersecurity Arms Race. CODASPY 2020: 220-222 - [c62]Xin Zhou, Rakesh M. Verma:
Phishing Sites Detection from a Web Developer's Perspective Using Machine Learning. HICSS 2020: 1-10 - [c61]Rakesh M. Verma:
Poster: A Modular and Innovative Security Analytics Course. SIGCSE 2020: 1352 - [e6]Rakesh M. Verma, Latifur Khan, Chilukuri K. Mohan:
IWSPA@CODASPY '20: Proceedings ofthe Sixth International Workshop on Security and Privacy Analytics, New Orleans, LA, USA, March 18, 2020. ACM 2020, ISBN 978-1-4503-7115-5 [contents] - [i16]Shahryar Baki, Rakesh M. Verma, Arjun Mukherjee, Omprakash Gnawali:
Less is More: Exploiting Social Trust to Increase the Effectiveness of a Deception Attack. CoRR abs/2006.13499 (2020) - [i15]Avisha Das, Rakesh M. Verma:
Modeling Coherency in Generated Emails by Leveraging Deep Neural Learners. CoRR abs/2007.07403 (2020) - [i14]Daniel Lee, Rakesh M. Verma, Avisha Das, Arjun Mukherjee:
Experiments in Extractive Summarization: Integer Linear Programming, Term/Sentence Scoring, and Title-driven Models. CoRR abs/2008.00140 (2020)
2010 – 2019
- 2019
- [j28]Alan T. Sherman, Josiah Dykstra, Gregory V. Bard, Ankur Chattopadhyay, Filipo Sharevski, Rakesh M. Verma, Ryan Vrecenar, Linda Oliva, Enis Golaszewski, Dhananjay S. Phatak, Travis Scheponik, Geoffrey L. Herman, Dong San Choi, Spencer E. Offenberger, Peter Peterson:
The CATS Hackathon: Creating and Refining Test Items for Cybersecurity Concept Inventories. IEEE Secur. Priv. 17(6): 77-83 (2019) - [c60]Rakesh M. Verma, Victor Zeng, Houtan Faridi:
Data Quality for Security Challenges: Case Studies of Phishing, Malware and Intrusion Detection Datasets. CCS 2019: 2605-2607 - [c59]Houtan Faridi, Srivathsan Srinivasagopalan, Rakesh M. Verma:
Parameter Tuning and Confidence Limits of Malware Clustering. CODASPY 2019: 169-171 - [i13]Alan T. Sherman, Linda Oliva, Enis Golaszewski, Dhananjay S. Phatak, Travis Scheponik, Geoffrey L. Herman, Dong San Choi, Spencer E. Offenberger, Peter Peterson, Josiah Dykstra, Gregory V. Bard, Ankur Chattopadhyay, Filipo Sharevski, Rakesh M. Verma, Ryan Vrecenar:
The CATS Hackathon: Creating and Refining Test Items for Cybersecurity Concept Inventories. CoRR abs/1901.09286 (2019) - [i12]Rakesh M. Verma, Samaneh Karimi, Daniel Lee, Omprakash Gnawali, Azadeh Shakery:
Newswire versus Social Media for Disaster Response and Recovery. CoRR abs/1906.10607 (2019) - [i11]Avisha Das, Rakesh M. Verma:
Automated email Generation for Targeted Attacks using Natural Language. CoRR abs/1908.06893 (2019) - [i10]Samaneh Karimi, Azadeh Shakery, Rakesh M. Verma:
Online News Media Website Ranking Using User Generated Content. CoRR abs/1910.12441 (2019) - [i9]Avisha Das, Shahryar Baki, Ayman El Aassal, Rakesh M. Verma, Arthur Dunbar:
SOK: A Comprehensive Reexamination of Phishing Research from the Security Perspective. CoRR abs/1911.00953 (2019) - 2018
- [j27]Luis F. T. Moraes, Shahryar Baki, Rakesh M. Verma, Daniel Lee:
Identifying reference spans: topic modeling and word embeddings help IR. Int. J. Digit. Libr. 19(2-3): 191-202 (2018) - [j26]Samaneh Karimi, Luis F. T. Moraes, Avisha Das, Azadeh Shakery, Rakesh M. Verma:
Citance-based retrieval and summarization using IR and machine learning. Scientometrics 116(2): 1331-1366 (2018) - [c58]Boris Chernis, Rakesh M. Verma:
Machine Learning Methods for Software Vulnerability Detection. IWSPA@CODASPY 2018: 31-39 - [c57]Rakesh M. Verma:
Security Analytics: Adapting Data Science for Security Challenges. IWSPA@CODASPY 2018: 40-41 - [c56]Gal Egozi, Rakesh M. Verma:
Phishing Email Detection Using Robust NLP Techniques. ICDM Workshops 2018: 7-12 - [c55]Houtan Faridi, Srivathsan Srinivasagopalan, Rakesh M. Verma:
Performance Evaluation of Features and Clustering Algorithms for Malware. ICDM Workshops 2018: 13-22 - [c54]Luis F. T. De Moraes, Avisha Das, Samaneh Karimi, Rakesh M. Verma:
University of Houston @ CL-SciSumm 2018. BIRNDL@SIGIR 2018: 142-149 - [e5]Rakesh M. Verma, Murat Kantarcioglu:
Proceedings of the Fourth ACM International Workshop on Security and Privacy Analytics, IWSPA@CODASPY 2018, Tempe, AZ, USA, March 19-21, 2018. ACM 2018 [contents] - 2017
- [j25]Rakesh M. Verma, Daniel Lee:
Extractive Summarization: Limits, Compression, Generalized Model and Heuristics. Computación y Sistemas 21(4) (2017) - [j24]Alan T. Sherman, Melissa Dark, Agnes H. Chan, Rylan Chong, Thomas H. Morris, Linda Oliva, John A. Springer, Bhavani Thuraisingham, Christopher Vatcher, Rakesh M. Verma, Susanne Wetzel:
INSuRE: Collaborating Centers of Academic Excellence Engage Students in Cybersecurity Research. IEEE Secur. Priv. 15(4): 72-78 (2017) - [j23]Nicholas R. Radcliffe, Luis F. T. Moraes, Rakesh M. Verma:
Uniqueness of Normal Forms for Shallow Term Rewrite Systems. ACM Trans. Comput. Log. 18(2): 17:1-17:20 (2017) - [c53]Shahryar Baki, Rakesh M. Verma, Arjun Mukherjee, Omprakash Gnawali:
Scaling and Effectiveness of Email Masquerade Attacks: Exploiting Natural Language Generation. AsiaCCS 2017: 469-482 - [c52]Rakesh M. Verma, Avisha Das:
What's in a URL: Fast Feature Extraction and Malicious URL Detection. IWSPA@CODASPY 2017: 55-63 - [c51]Rakesh M. Verma, Ayman El Aassal:
Comprehensive Method for Detecting Phishing EmailsUsing Correlation-based Analysis and User Participation. CODASPY 2017: 155-157 - [c50]Vasanthi Vuppuluri, Shahryar Baki, An Nguyen, Rakesh M. Verma:
ICE: Idiom and Collocation Extractor for Research and Education. EACL (Software Demonstrations) 2017: 108-111 - [c49]Samaneh Karimi, Luis F. T. Moraes, Avisha Das, Rakesh M. Verma:
University of Houston @ CL-SciSumm 2017: Positional language Models, Structural Correspondence Learning and Textual Entailment. BIRNDL@SIGIR (2) 2017: 73-85 - [e4]Rakesh M. Verma, Bhavani Thuraisingham:
Proceedings of the 3rd ACM on International Workshop on Security And Privacy Analytics, IWSPA@CODASPY 2017, Scottsdale, Arizona, USA, March 24, 2017. ACM 2017, ISBN 978-1-4503-4909-3 [contents] - [i8]Alan T. Sherman, Melissa Dark, Agnes H. Chan, Rylan Chong, Thomas H. Morris, Linda Oliva, John A. Springer, Bhavani Thuraisingham, Christopher Vatcher, Rakesh M. Verma, Susanne Wetzel:
The INSuRE Project: CAE-Rs Collaborate to Engage Students in Cybersecurity Research. CoRR abs/1703.08859 (2017) - [i7]Rakesh M. Verma, Daniel Lee:
Extractive Summarization: Limits, Compression, Generalized Model and Heuristics. CoRR abs/1704.05550 (2017) - [i6]Luis F. T. Moraes, Shahryar Baki, Rakesh M. Verma, Daniel Lee:
Identifying Reference Spans: Topic Modeling and Word Embeddings help IR. CoRR abs/1708.02989 (2017) - 2016
- [c48]Rakesh M. Verma, Vasanthi Vuppuluri, An Nguyen, Arjun Mukherjee, Ghita Mammar, Shahryar Baki, Reed Armstrong:
Mining the Web for Collocations: IR Models of Term Associations. CICLing (1) 2016: 177-194 - [c47]Luis F. T. Moraes, Shahryar Baki, Rakesh M. Verma, Daniel Lee:
University of Houston at CL-SciSumm 2016: SVMs with tree kernels and Sentence Similarity. BIRNDL@JCDL 2016: 113-121 - [e3]Rakesh M. Verma, Michaël Rusinowitch:
Proceedings of the 2016 ACM on International Workshop on Security And Privacy Analytics, IWSPA@CODASPY 2016, New Orleans, LA, USA, March 11, 2016. ACM 2016, ISBN 978-1-4503-4077-9 [contents] - [i5]Nicholas R. Radcliffe, Luis F. T. Moraes, Rakesh M. Verma:
Uniqueness of Normal Forms for Shallow Term Rewrite Systems. CoRR abs/1607.00431 (2016) - 2015
- [j22]Rakesh M. Verma, Murat Kantarcioglu, David J. Marchette, Ernst L. Leiss, Thamar Solorio:
Security Analytics: Essential Data Analytics Knowledge for Cybersecurity Professionals and Students. IEEE Secur. Priv. 13(6): 60-65 (2015) - [j21]Narasimha K. Shashidhar, Chadi Kari, Rakesh M. Verma:
The Efficacy of Epidemic Algorithms on Detecting Node Replicas in Wireless Sensor Networks. J. Sens. Actuator Networks 4(4): 378-409 (2015) - [c46]Wenyaw Chan, George Cybenko, Murat Kantarcioglu, Ernst L. Leiss, Thamar Solorio, Bhavani Thuraisingham, Rakesh M. Verma:
Panel: Essential Data Analytics Knowledge forCyber-security Professionals and Students. IWSPA@CODASPY 2015: 55-57 - [c45]Rakesh M. Verma, Keith Dyer:
On the Character of Phishing URLs: Accurate and Robust Statistical Learning Classifiers. CODASPY 2015: 111-122 - [c44]Tayfun Tuna, Mahima Joshi, Varun Varghese, Rucha Deshpande, Jaspal Subhlok, Rakesh M. Verma:
Topic based segmentation of classroom videos. FIE 2015: 1-9 - [c43]Zhimin Gao, Nicholas DeSalvo, Pham Dang Khoa, Seung-Hun Kim, Lei Xu, Won Woo Ro, Rakesh M. Verma, Weidong Shi:
Integrity Protection for Big Data Processing with Dynamic Redundancy Computation. ICAC 2015: 159-160 - [c42]Rakesh M. Verma, Vasanthi Vuppuluri:
A New Approach for Idiom Identification Using Meanings and the Web. RANLP 2015: 681-687 - [c41]Rakesh M. Verma, Nirmala Rai:
Phish-IDetector: Message-Id Based Automatic Phishing Detection. SECRYPT 2015: 427-434 - [e2]Stephen Huang, Rakesh M. Verma:
Proceedings of the 2015 ACM International Workshop on International Workshop on Security and Privacy Analytics, IWSPA@CODASPY 2015, San Antonio, TX, USA, March 4, 2015. ACM 2015, ISBN 978-1-4503-3341-2 [contents] - 2014
- [c40]Tanmay Thakur, Rakesh M. Verma:
Catching Classical and Hijack-Based Phishing Attacks. ICISS 2014: 318-337 - 2013
- [c39]Rakesh M. Verma, Nabil Hossain:
Semantic Feature Selection for Text with Application to Phishing Email Detection. ICISC 2013: 455-468 - [c38]Rakesh M. Verma, Bailey E. Basile:
Modeling and analysis of LEAP, a key management protocol for wireless sensor networks. SECON 2013: 65-67 - 2012
- [c37]Rakesh M. Verma, Narasimha K. Shashidhar, Nabil Hossain:
Two-Pronged Phish Snagging. ARES 2012: 174-179 - [c36]Araly Barrera, Rakesh M. Verma:
Combining Syntax and Semantics for Automatic Extractive Single-Document Summarization. CICLing (2) 2012: 366-377 - [c35]Rakesh M. Verma, Narasimha K. Shashidhar, Nabil Hossain:
Detecting Phishing Emails the Natural Language Way. ESORICS 2012: 824-841 - 2011
- [c34]Araly Barrera, Rakesh M. Verma:
Automated extractive single-document summarization: beating the baselines with a new approach. SAC 2011: 268-269 - [c33]Rakesh M. Verma, Wei Guo:
Does Unification Help in Normalization? UNIF 2011: 52-58 - [i4]Araly Barrera, Rakesh M. Verma, Ryan Vincent:
SemQuest: University of Houston's Semantics-based Question Answering System. TAC 2011 - 2010
- [j20]Julian Zinn, Rakesh M. Verma:
A polynomial algorithm for uniqueness of normal forms of linear shallow term rewrite systems. Appl. Algebra Eng. Commun. Comput. 21(6): 459-485 (2010) - [c32]Nicholas R. Radcliffe, Rakesh M. Verma:
Uniqueness of Normal Forms is Decidable for Shallow Term Rewrite Systems. FSTTCS 2010: 284-295 - [c31]Sam Blackshear, Rakesh M. Verma:
R-LEAP+: randomizing LEAP+ key distribution to resist replay and jamming attacks. SAC 2010: 1985-1992 - [i3]Araly Barrera, Rakesh M. Verma:
A Ranking-based Approach for Multiple-document Information Extraction. TAC 2010
2000 – 2009
- 2009
- [j19]Rakesh M. Verma:
Complexity of Normal Form Properties and Reductions for Term Rewriting Problems Complexity of Normal Form Properties and Reductions for Term Rewriting Problems. Fundam. Informaticae 92(1-2): 145-168 (2009) - [c30]Zhiyao Liang, Rakesh M. Verma:
Correcting and Improving the NP Proof for Cryptographic Protocol Insecurity. ICISS 2009: 101-116 - 2008
- [c29]Zhiyao Liang, Rakesh M. Verma:
Improving Techniques for Proving Undecidability of Checking Cryptographic Protocols. ARES 2008: 1067-1074 - [c28]Ping Chen, Rakesh M. Verma, Janet C. Meininger, Wenyaw Chan:
Semantic Analysis of Association Rules. FLAIRS 2008: 270-275 - [c27]Zhiyao Liang, Rakesh M. Verma:
Complexity of Checking Freshness of Cryptographic Protocols. ICISS 2008: 86-101 - [c26]Wenshan Yu, Rakesh M. Verma:
Visualization of rule-based programming. SAC 2008: 1258-1259 - [c25]Rakesh M. Verma:
New Undecidability Results for Properties of Term Rewrite Systems. RULE 2008: 69-85 - [i2]Rakesh M. Verma, David Kent, Ping Chen:
Semantic Multi-Document Update Summarization Techniques. TAC 2008 - 2006
- [c24]Ping Chen, Rakesh M. Verma:
A Query-Based Medical Information Summarization System Using Ontology Knowledge. CBMS 2006: 37-42 - [c23]Michal Armoni, Susan H. Rodger, Moshe Y. Vardi,