| Nome |
# |
|
Detecting malicious activities with user-agent-based profiles, file e384c42e-67c6-d4b2-e053-9f05fe0a1d67
|
3.401
|
|
Click vs. Linux: Two Efficient Open-Source IP Network Stacks for Software Routers, file e384c42d-f39f-d4b2-e053-9f05fe0a1d67
|
3.104
|
|
Inside Dropbox: Understanding Personal Cloud Storage Services, file e384c42e-2614-d4b2-e053-9f05fe0a1d67
|
2.438
|
|
Reducing Power Consumption in Backbone Networks, file e384c42e-056b-d4b2-e053-9f05fe0a1d67
|
2.223
|
|
Detailed Analysis of Skype Traffic, file e384c42d-fd9b-d4b2-e053-9f05fe0a1d67
|
2.179
|
|
DNS to the rescue: Discerning Content and Services in a Tangled Web, file e384c42e-2618-d4b2-e053-9f05fe0a1d67
|
2.173
|
|
Power-Aware Routing and Wavelength Assignment in Optical Networks, file e384c42e-05cc-d4b2-e053-9f05fe0a1d67
|
2.166
|
|
KISS: Stochastic Packet Inspection Classifier for UDP Traffic, file e384c42e-103b-d4b2-e053-9f05fe0a1d67
|
1.978
|
|
The Cost of the "S" in HTTPS, file e384c42e-3a17-d4b2-e053-9f05fe0a1d67
|
1.797
|
|
Energy-aware Backbone Networks: a Case Study, file e384c42e-056e-d4b2-e053-9f05fe0a1d67
|
1.738
|
|
Experiences of Internet Traffic Monitoring with Tstat, file e384c42e-17da-d4b2-e053-9f05fe0a1d67
|
1.685
|
|
Personal cloud storage: Usage, performance and impact of terminals, file e384c42e-5cfc-d4b2-e053-9f05fe0a1d67
|
1.657
|
|
Characterization of ISP Traffic: Trends, User Habits, and Access Technology Impact, file e384c42e-164a-d4b2-e053-9f05fe0a1d67
|
1.507
|
|
The Internet-Wide Impact of P2P Traffic Localization on ISP Profitability, file e384c42e-25ac-d4b2-e053-9f05fe0a1d67
|
1.279
|
|
Considering Transmission Impairments in Wavelength Routed Networks, file e384c42d-f2a1-d4b2-e053-9f05fe0a1d67
|
1.238
|
|
Network Awareness of P2P Live Streaming Applications: A Measurement Study, file e384c42e-09b5-d4b2-e053-9f05fe0a1d67
|
1.155
|
|
Reviewing Traffic ClassificationData Traffic Monitoring and Analysis, file e384c42e-295f-d4b2-e053-9f05fe0a1d67
|
1.050
|
|
Impact of Access Line Capacity on Adaptive Video Streaming Quality - A Passive Perspective, file e384c42f-3741-d4b2-e053-9f05fe0a1d67
|
1.041
|
|
Systematic Mining of Associated Server Herds for Malware Campaign Discovery, file e384c42e-5cfe-d4b2-e053-9f05fe0a1d67
|
981
|
|
Macroscopic view of malware in home networks, file e384c42e-67c1-d4b2-e053-9f05fe0a1d67
|
964
|
|
Considering transmission impairments in configuring wavelength routed optical networks, file e384c42d-f2a5-d4b2-e053-9f05fe0a1d67
|
961
|
|
CLUE: Clustering for Mining Web URLs, file e384c42f-6d88-d4b2-e053-9f05fe0a1d67
|
923
|
|
Live Traffic Monitoring with Tstat: Capabilities and Experiences, file e384c42e-17ff-d4b2-e053-9f05fe0a1d67
|
918
|
|
Exploring the cloud from passive measurements: The Amazon AWS case, file e384c42e-2961-d4b2-e053-9f05fe0a1d67
|
856
|
|
Benchmarking personal cloud storage, file e384c42e-296d-d4b2-e053-9f05fe0a1d67
|
821
|
|
The Online Tracking Horde: A View from Passive Measurements, file e384c42e-3a6e-d4b2-e053-9f05fe0a1d67
|
791
|
|
Demonstrating the Impact of P2P Streaming on Video Quality, file e384c42e-0d39-d4b2-e053-9f05fe0a1d67
|
788
|
|
Large-scale network traffic monitoring with DBStream, a system for rolling big data analysis, file e384c42e-3602-d4b2-e053-9f05fe0a1d67
|
783
|
|
Measurement of IPTV traffic from an Operative Network, file e384c42e-056d-d4b2-e053-9f05fe0a1d67
|
771
|
|
P2P-TV systems under adverse network conditions: a measurement study, file e384c42d-fda7-d4b2-e053-9f05fe0a1d67
|
754
|
|
Five Years at the Edge: Watching Internet From the ISP Network, file e384c431-9094-d4b2-e053-9f05fe0a1d67
|
749
|
|
Boosting the Performance of PC-based Software Routers with FPGA-enhanced Network Interface Cards, file e384c42d-fab8-d4b2-e053-9f05fe0a1d67
|
741
|
|
How Much Can The Internet Be Greened?, file e384c42e-0464-d4b2-e053-9f05fe0a1d67
|
724
|
|
PoliSave: Efficient Power Management of Campus PCs, file e384c42e-1801-d4b2-e053-9f05fe0a1d67
|
723
|
|
GRiDA: A green distributed algorithm for backbone networks, file e384c42e-1549-d4b2-e053-9f05fe0a1d67
|
713
|
|
Personal Cloud Storage Benchmarks and Comparison, file e384c42f-7aa2-d4b2-e053-9f05fe0a1d67
|
702
|
|
Comparing P2PTV Traffic Classifiers, file e384c42e-0e7b-d4b2-e053-9f05fe0a1d67
|
682
|
|
Network Connectivity Graph for Malicious Traffic Dissection, file e384c42e-67c3-d4b2-e053-9f05fe0a1d67
|
682
|
|
Investigating Overlay Topologies and Dynamics of P2P-TV Systems: The Case of SopCast, file e384c42e-154a-d4b2-e053-9f05fe0a1d67
|
676
|
|
Web User Session Characterization via Clustering Techniques, file e384c42d-ed97-d4b2-e053-9f05fe0a1d67
|
643
|
|
Energy Profiling of ISP Points of Presence, file e384c42e-1994-d4b2-e053-9f05fe0a1d67
|
642
|
|
Two Schemes to Reduce Latency in Short Lived TCP Flows, file e384c42e-0465-d4b2-e053-9f05fe0a1d67
|
636
|
|
Dissecting Video Server Selection Strategies in the YouTube CDN, file e384c42e-14ea-d4b2-e053-9f05fe0a1d67
|
636
|
|
Five Years at the Edge: Watching Internet from the ISP Network, file e384c430-7556-d4b2-e053-9f05fe0a1d67
|
629
|
|
TCP smart framing: a segmentation algorithm to reduce TCP latency, file e384c42d-e5c4-d4b2-e053-9f05fe0a1d67
|
628
|
|
Building a Cooperative P2P-TV Application over a Wise Network: the Approach of the European FP-7 STREP NAPA-WINE, file e384c42e-0227-d4b2-e053-9f05fe0a1d67
|
628
|
|
Impact of adverse network conditions on P2P-TV systems: Experimental evidence, file e384c42e-14e6-d4b2-e053-9f05fe0a1d67
|
623
|
|
Automatic protocol field inference for deeper protocol understanding, file e384c42e-67cc-d4b2-e053-9f05fe0a1d67
|
623
|
|
Network Friendly P2P-TV: The Napa-Wine Approach, file e384c42e-1800-d4b2-e053-9f05fe0a1d67
|
620
|
|
Web User-session Inference by Means of Clustering Techniques, file e384c42e-05d7-d4b2-e053-9f05fe0a1d67
|
612
|
|
Efficient Uplink Bandwidth Utilization in P2P-TV Streaming Systems, file e384c42e-0d3b-d4b2-e053-9f05fe0a1d67
|
596
|
|
Energy saving and network performance: a trade-off approach, file e384c42e-03d9-d4b2-e053-9f05fe0a1d67
|
591
|
|
Multistage Switching Architectures for Software Routers, file e384c42d-f538-d4b2-e053-9f05fe0a1d67
|
574
|
|
Modeling sleep modes gains with random graphs, file e384c42e-14e7-d4b2-e053-9f05fe0a1d67
|
574
|
|
A Distributed Architecture for the Monitoring of Clouds and CDNs: Applications to Amazon AWS, file e384c42e-3a7a-d4b2-e053-9f05fe0a1d67
|
567
|
|
Stochastic Packet Inspection for TCP Traffic1, file e384c42e-0e5b-d4b2-e053-9f05fe0a1d67
|
561
|
|
Passive characterization of sopcast usage in residential ISPs, file e384c42e-154b-d4b2-e053-9f05fe0a1d67
|
561
|
|
The Quest for Bandwidth Estimation Techniques for large-scale Distributed Systems, file e384c42e-03da-d4b2-e053-9f05fe0a1d67
|
557
|
|
Passive analysis of TCP anomalies, file e384c42e-0228-d4b2-e053-9f05fe0a1d67
|
555
|
|
Unsupervised Detection of Web Trackers, file e384c42e-dccc-d4b2-e053-9f05fe0a1d67
|
539
|
|
Experiences of Cloud Storage Service Monitoring: Performance Assessment and Comparison, file e384c42e-d30a-d4b2-e053-9f05fe0a1d67
|
536
|
|
Using Passive Measurements to Demystify Online Trackers, file e384c42e-c78e-d4b2-e053-9f05fe0a1d67
|
528
|
|
NetCluster: A clustering-based framework to analyze internet passive measurements data, file e384c42e-296a-d4b2-e053-9f05fe0a1d67
|
519
|
|
Experimental comparison of neighborhood filtering strategies in unstructured P2P-TV systems, file e384c42e-260b-d4b2-e053-9f05fe0a1d67
|
518
|
|
Gold Mining in a River of Internet Content Traffic, file e384c42e-2f3f-d4b2-e053-9f05fe0a1d67
|
511
|
|
mPlane: an intelligent measurement plane for the internet, file e384c42e-355f-d4b2-e053-9f05fe0a1d67
|
505
|
|
Routing with Deceptive Information, file e384c42d-f30b-d4b2-e053-9f05fe0a1d67
|
499
|
|
Energy efficiency in access and aggregation networks: From current traffic to potential savings, file e384c42e-2f00-d4b2-e053-9f05fe0a1d67
|
499
|
|
Network Awareness of P2P Live Streaming Applications, file e384c42e-0706-d4b2-e053-9f05fe0a1d67
|
498
|
|
A New Class of QoS Routing Strategies Based on Network Graph Reduction, file e384c42d-f309-d4b2-e053-9f05fe0a1d67
|
474
|
|
Aggregation of Statistical Data from Passive Probes: Techniques and Best Practices, file e384c42e-2f3b-d4b2-e053-9f05fe0a1d67
|
474
|
|
Benchmark and comparison of tracker-blockers: Should you trust them?, file e384c42f-9659-d4b2-e053-9f05fe0a1d67
|
474
|
|
SeLINA: a Self-Learning Insightful Network Analyzer, file e384c42f-13a8-d4b2-e053-9f05fe0a1d67
|
470
|
|
NetCluster: a Clustering-Based Framework for Internet Tomography, file e384c42e-02bc-d4b2-e053-9f05fe0a1d67
|
463
|
|
Modeling sleep mode gains in energy-aware networks, file e384c42e-2969-d4b2-e053-9f05fe0a1d67
|
450
|
|
Traffic Monitoring and Analysis, file e384c42e-0fd5-d4b2-e053-9f05fe0a1d67
|
449
|
|
On the intertwining between capacity scaling and TCP congestion control, file e384c42e-1992-d4b2-e053-9f05fe0a1d67
|
449
|
|
Multilevel bandwidth measurements and capacity exploitation in gigabit passive optical networks, file e384c42e-2fa0-d4b2-e053-9f05fe0a1d67
|
449
|
|
Neighborhood Filtering Strategies for Overlay Construction in P2P-TV Systems: Design and Experimental Comparison, file e384c42e-331f-d4b2-e053-9f05fe0a1d67
|
449
|
|
Optimal Scheduling and Routing for Maximum Network Throughput, file e384c42e-0278-d4b2-e053-9f05fe0a1d67
|
444
|
|
Evidences Behind Skype Outage, file e384c42e-06a2-d4b2-e053-9f05fe0a1d67
|
442
|
|
CrowdSurf: Empowering Transparency in the Web, file e384c42e-67ca-d4b2-e053-9f05fe0a1d67
|
428
|
|
KISS: Stochastic Packet Inspection Classifier for UDP Traffic, file e384c42e-103a-d4b2-e053-9f05fe0a1d67
|
421
|
|
SeLeCT: Self-Learning Classifier
for Internet Traffic, file e384c42e-27c7-d4b2-e053-9f05fe0a1d67
|
420
|
|
Traffic Analysis with Off-the-Shelf Hardware: Challenges and Lessons Learned, file e384c42f-7067-d4b2-e053-9f05fe0a1d67
|
420
|
|
QoE in Pull Based P2P-TV Systems: Overlay Topology Design Tradeoff, file e384c42e-103c-d4b2-e053-9f05fe0a1d67
|
406
|
|
Leveraging client-side DNS failure patterns to identify malicious behaviors, file e384c42e-67c8-d4b2-e053-9f05fe0a1d67
|
404
|
|
Network Friendly P2P Streaming: The NAPA-WINE Architecture, file e384c42e-0d37-d4b2-e053-9f05fe0a1d67
|
400
|
|
Understanding Skype Signaling, file e384c42e-16a7-d4b2-e053-9f05fe0a1d67
|
400
|
|
Self-learning classifier for internet traffic, file e384c42e-31dd-d4b2-e053-9f05fe0a1d67
|
395
|
|
Control and Management Plane in a Multi-stage Software Router Architecture, file e384c42e-0291-d4b2-e053-9f05fe0a1d67
|
393
|
|
Program chairs' message, file e384c42f-e88c-d4b2-e053-9f05fe0a1d67
|
384
|
|
User Patience and the Web: a hands-on investigation, file e384c42d-eed2-d4b2-e053-9f05fe0a1d67
|
379
|
|
Chunk Distribution in Mesh-Based Large-Scale P2P Streaming Systems: A Fluid Approach, file e384c42e-056a-d4b2-e053-9f05fe0a1d67
|
372
|
|
Comparison of energy efficiency in PSTN and VoIP systems, file e384c42e-1991-d4b2-e053-9f05fe0a1d67
|
371
|
|
TUCAN: Twitter User Centric ANalyzer, file e384c42e-2e10-d4b2-e053-9f05fe0a1d67
|
358
|
|
Cloud storage service benchmarking: Methodologies and experimentations2014 IEEE 3rd International Conference on Cloud Networking (CloudNet), file e384c42e-3a16-d4b2-e053-9f05fe0a1d67
|
358
|
|
CrowdSurf: Empowering Informed Choices in the Web, file e384c42f-78ec-d4b2-e053-9f05fe0a1d67
|
357
|
|
Users’ Fingerprinting Techniques from TCP Traffic, file e384c42f-804a-d4b2-e053-9f05fe0a1d67
|
357
|
|
Understanding VoIP from Backbone Measurements, file e384c42d-f9c7-d4b2-e053-9f05fe0a1d67
|
340
|
| Totale |
80.570 |
Archivio Istituzionale della Ricerca