Search Results - "GEHANI, Ashish"

IOSPReD: I/O Specialized Packaging of Reduced Datasets and Data-Intensive Applications for Efficient Reproducibility by Niddodi, Chaitra, Gehani, Ashish, Malik, Tanu, Mohan, Sibin, Rilee, Michael Lee

“…The data generated by large scale scientific systems such as NASA's Earth Observing System Data and Information System is expected to increase substantially…”
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Trimmer: Application Specialization for Code Debloating by Sharif, Hashim, Abubakar, Muhammad, Gehani, Ashish, Zaffar, Fareed

“…With the proliferation of new hardware architectures and ever-evolving user requirements, the software stack is becoming increasingly bloated. In practice,…”
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autoMPI: Automated Multiple Perspective Attack Investigation With Semantics Aware Execution Partitioning by Alhanahnah, Mohannad, Ma, Shiqing, Gehani, Ashish, Ciocarlie, Gabriela F., Yegneswaran, Vinod, Jha, Somesh, Zhang, Xiangyu

“…Multiple Perspective attack Investigation ( MPI ) is a technique to partition application dependencies based on high-level semantics. It facilitates provenance…”
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TRACE: Enterprise-Wide Provenance Tracking for Real-Time APT Detection by Irshad, Hassaan, Ciocarlie, Gabriela, Gehani, Ashish, Yegneswaran, Vinod, Lee, Kyu Hyung, Patel, Jignesh, Jha, Somesh, Kwon, Yonghwi, Xu, Dongyan, Zhang, Xiangyu

“…We present TRACE, a comprehensive provenance tracking system for scalable, real-time, enterprise-wide APT detection. TRACE uses static analysis to identify…”
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Trimmer: An Automated System for Configuration-Based Software Debloating by Ahmad, Aatira Anum, Noor, Abdul Rafae, Sharif, Hashim, Hameed, Usama, Asif, Shoaib, Anwar, Mubashir, Gehani, Ashish, Zaffar, Fareed, Siddiqui, Junaid Haroon

“…Software bloat has negative implications for security, reliability, and performance. To counter bloat, we propose Trimmer , a static analysis-based system for…”
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Provenance-based Workflow Diagnostics Using Program Specification by Nakamura, Yuta, Malik, Tanu, Kanj, Iyad, Gehani, Ashish

“…Workflow management systems (WMS) help automate and coordinate scientific modules and monitor their execution. WMSes are also used to repeat a workflow…”
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Analytical models for risk-based intrusion response by Caskurlu, Bugra, Gehani, Ashish, Bilgin, Cemal Cagatay, Subramani, K.

“…Risk analysis has been used to manage the security of systems for several decades. However, its use has been limited to offline risk computation and manual…”
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Analytical models for risk-based intrusion response : Specail issue on 'Towards a Science of Cyber Security' by CASKURLU, Bugra, GEHANI, Ashish, BILGIN, Cemal Cagatay, SUBRAMANI, K

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SoK: Software Debloating Landscape and Future Directions by Alhanahnah, Mohannad, Boshmaf, Yazan, Gehani, Ashish

“…Software debloating seeks to mitigate security risks and improve performance by eliminating unnecessary code. In recent years, a plethora of debloating tools…”
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Data Mining-Based Ethereum Fraud Detection by Jung, Eunjin, Le Tilly, Marion, Gehani, Ashish, Ge, Yunjie

“…The popularity of blockchain-based currencies, such as Bitcoin and Ethereum, has grown among enthusiasts since 2009. Relying on the anonymity provided by the…”
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Kondo: Efficient Provenance-Driven Data Debloating by Modi, Aniket, Tikmany, Rohan, Malik, Tanu, Komondoor, Raghavan, Gehani, Ashish, D'Souza, Deepak

“…Isolation increases upfront costs of provisioning containers. This is due to unnecessary software and data in container images. While several static and…”
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Access-Based Carving of Data for Efficient Reproducibility of Containers by Tikmany, Rohan, Modi, Aniket, Atiq, Raffay, Reyad, Moaz, Gehani, Ashish, Malik, Tanu

“…Scientific applications often depend on data produced from computational models. Model-generated data can be prohibitively large. Current mechanisms for…”
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ICEMAN: A System for Efficient, Robust and Secure Situational Awareness at the Network Edge by Wood, Samuel, Mathewson, James, Joy, Joshua, Stehr, Mark-Oliver, Minyoung Kim, Gehani, Ashish, Gerla, Mario, Sadjadpour, Hamid, Garcia-Luna-Aceves, J. J.

“…Situational awareness applications in disaster response and tactical scenarios require efficient communication without a managed infrastructure. In principle,…”
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BLADE: Towards Scalable Source Code Debloating by Ali, Muaz, Habib, Rumaisa, Gehani, Ashish, Rahaman, Sazzadur, Uzmi, Zartash

“…Existing source code debloaters fall short due to low scalability and high runtime overhead when applied in dynamic cloud settings, where instances are spun up…”
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Optimized Rollback and Re-computation by Lakhani, H., Tahir, R., Aqil, A., Zaffar, F., Tariq, D., Gehani, A.

“…Large data processing tasks can be effected using workflow management systems. When either the input data or the programs in the pipeline are modified, the…”
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Bonsai: Balanced Lineage Authentication by Gehani, A., Lindqvist, U.

“…The provenance of a piece of data is of utility to a wide range of applications. Its availability can be drastically increased by automatically collecting…”
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PACED: Provenance-based Automated Container Escape Detection by Abbas, Mashal, Khan, Shahpar, Monum, Abdul, Zaffar, Fareed, Tahir, Rashid, Eyers, David, Irshad, Hassaan, Gehani, Ashish, Yegneswaran, Vinod, Pasquier, Thomas

“…The security of container-based microservices relies heavily on the isolation of operating system resources that is provided by namespaces. However,…”
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CHEX: Multiversion Replay with Ordered Checkpoints by Manne, Naga Nithin, Satpati, Shilvi, Malik, Tanu, Bagchi, Amitabha, Gehani, Ashish, Chaudhary, Amitabh

“…In scientific computing and data science disciplines, it is often necessary to share application workflows and repeat results. Current tools containerize…”
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Fine-grained tracking of Grid infections by Gehani, A, Baig, B, Mahmood, S, Tariq, D, Zaffar, F

“…Previous distributed anomaly detection efforts have operated on summary statistics gathered from each node. This has the advantage that the audit trail is…”
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Xanthus: Push-button Orchestration of Host Provenance Data Collection by Han, Xueyuan, Mickens, James, Gehani, Ashish, Seltzer, Margo, Pasquier, Thomas

“…Host-based anomaly detectors generate alarms by inspecting audit logs for suspicious behavior. Unfortunately, evaluating these anomaly detectors is hard. There…”
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