Sankardas Roy
Signal Processing · 2010–2017
A researcher in the Science corpus: 4 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Signal Processing — 39 citations into it
- Computer Networks and Communications — 26 citations into it
- Artificial Intelligence — 18 citations into it
- Software — 16 citations into it
Whom Sankardas Roy trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yajin Zhou
- Michael L. Littman
- Peng Liu
- Robin Sommer
- Jesse Davis
- Nicolas Viennot
- Daniel Arp
- Xuxian Jiang
- Mu Zhang
- Ondřej Lhoták
Who trusts Sankardas Roy overall
Papers from Sankardas Roy's perspective
Ordered by how strongly the researchers Sankardas Roy trusts endorse each paper. Same corpus, a different order for every researcher.
- TaintDroid (USENIX Symposium on Operating Systems Design and Implementation)
- A survey of mobile malware in the wild (Security and Privacy in Smartphones and Mobile Devices)
- Dissecting Android Malware: Characterization and Evolution
- Unsafe exposure analysis of mobile in-app advertisements (Wireless Network Security)
- Analyzing inter-application communication in Android (ACM SIGMOBILE International Conference on Mobile Systems, Applications, and Services)
- Systematic Detection of Capability Leaks in Stock Android Smartphones (Network and Distributed System Security Symposium)
- Semantically Rich Application-Centric Security in Android (Asia-Pacific Computer Systems Architecture Conference)
- Effective inter-component communication mapping in Android with Epicc: an essential step towards holistic security analysis
- CHEX: statically vetting Android apps for component hijacking vulnerabilities (Conference on Computer and Communications Security)
- PScout: analyzing the Android permission specification (Conference on Computer and Communications Security)
Their papers
- A Survey of Game Theory as Applied to Network Security (2010) — 541 citations
- Deep Ground Truth Analysis of Current Android Malware (2017) — 418 citations
- Experimental Study with Real-world Data for Android App Security Analysis using Machine Learning (2015) — 76 citations
- Amandroid: A Precise and General Inter-component Data Flow Analysis Framework for Security Vetting of Android Apps (2014) — 632 citations