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malware detection (võtmesõna)

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Kirjeid leitud 9
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ekspordi kõik päringu tulemused (9)
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artikkel ajakirjas EST / artikkel ajakirjas ENG

Android malware concept drift using system calls : detection, characterization and challengesGuerra Manzanares, Alejandro; Luckner, Marcin; Bahsi, HayretdinExpert systems with applications2022 / art. 117200, 19 p. : ill https://doi.org/10.1016/j.eswa.2022.117200 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

artikkel ajakirjas EST / artikkel ajakirjas ENG
Seotud publikatsioonid 1
- Machine learning-based detection and characterization of evolving threats in mobile and IoT Systems = Masinõppepõhine arenevate ohtude tuvastamine ning kirjeldamine mobiilseadmete ja värkvõrkude jaoks
2

artikkel ajakirjas EST / artikkel ajakirjas ENG

Concept drift and cross-device behavior : challenges and implications for effective android malware detectionGuerra Manzanares, Alejandro; Luckner, Marcin; Bahsi, HayretdinComputers & Security2022 / art. 102757, 20 p. : ill https://doi.org/10.1016/j.cose.2022.102757 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

artikkel ajakirjas EST / artikkel ajakirjas ENG
Seotud publikatsioonid 1
- Machine learning-based detection and characterization of evolving threats in mobile and IoT Systems = Masinõppepõhine arenevate ohtude tuvastamine ning kirjeldamine mobiilseadmete ja värkvõrkude jaoks
3

artikkel ajakirjas

Cross-device behavioral consistency : benchmarking and implications for effective android malware detectionGuerra Manzanares, Alejandro; Välbe, MartinMachine Learning with Applications2022 / art. 100357, 15 p. : ill https://doi.org/10.1016/j.mlwa.2022.100357

artikkel ajakirjas
Seotud publikatsioonid 1
- Machine learning-based detection and characterization of evolving threats in mobile and IoT Systems = Masinõppepõhine arenevate ohtude tuvastamine ning kirjeldamine mobiilseadmete ja värkvõrkude jaoks
4

artikkel ajakirjas EST / artikkel ajakirjas ENG

Experts still needed : boosting long-term android malware detection with active learningGuerra-Manzanares, Alejandro; Bahsi, HayretdinJournal of Computer Virology and Hacking Techniques2024 / p. 901 - 918 https://doi.org/10.1007/s11416-024-00536-y Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

artikkel ajakirjas EST / artikkel ajakirjas ENG
5

artikkel ajakirjas EST / artikkel ajakirjas ENG

KronoDroid : time-based hybrid-featured dataset for effective android malware detection and characterizationGuerra Manzanares, Alejandro; Bahsi, Hayretdin; Nõmm, SvenComputers & Security2021 / art. 102399, 32 p https://doi.org/10.1016/j.cose.2021.102399 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

artikkel ajakirjas EST / artikkel ajakirjas ENG
Seotud publikatsioonid 1
- Machine learning-based detection and characterization of evolving threats in mobile and IoT Systems = Masinõppepõhine arenevate ohtude tuvastamine ning kirjeldamine mobiilseadmete ja värkvõrkude jaoks
6

artikkel ajakirjas EST / artikkel ajakirjas ENG

Leveraging the first line of defense : a study on the evolution and usage of android security permissions for enhanced android malware detectionGuerra Manzanares, Alejandro; Luckner, Marcin; Bahsi, HayretdinJournal of Computer Virology and Hacking Techniques2022 / 32 p. : ill https://doi.org/10.1007/s11416-022-00432-3 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

artikkel ajakirjas EST / artikkel ajakirjas ENG
Seotud publikatsioonid 1
- Machine learning-based detection and characterization of evolving threats in mobile and IoT Systems = Masinõppepõhine arenevate ohtude tuvastamine ning kirjeldamine mobiilseadmete ja värkvõrkude jaoks
7

artikkel kogumikus

On the application of active learning to handle data evolution in Android malware detectionGuerra Manzanares, Alejandro; Bahsi, HayretdinDigital forensics and cyber crime : 13th EAI international conference, ICDF2C 2022, Boston, MA, November 16-18, 2022 : proceedings2023 / p. 256-273 https://doi.org/10.1007/978-3-031-36574-4_15

artikkel kogumikus
Seotud publikatsioonid 1
- Machine learning-based detection and characterization of evolving threats in mobile and IoT Systems = Masinõppepõhine arenevate ohtude tuvastamine ning kirjeldamine mobiilseadmete ja värkvõrkude jaoks
8

artikkel ajakirjas EST / artikkel ajakirjas ENG

On the relativity of time : implications and challenges of data drift on long-term effective android malware detectionGuerra Manzanares, Alejandro; Bahsi, HayretdinComputers & Security2022 / art. 102835, 15 p. : ill https://doi.org/10.1016/j.cose.2022.102835 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

artikkel ajakirjas EST / artikkel ajakirjas ENG
Seotud publikatsioonid 1
- Machine learning-based detection and characterization of evolving threats in mobile and IoT Systems = Masinõppepõhine arenevate ohtude tuvastamine ning kirjeldamine mobiilseadmete ja värkvõrkude jaoks
9

artikkel kogumikus

Time-frame analysis of system calls behavior in machine learning-based mobile malware detectionGuerra Manzanares, Alejandro; Nõmm, Sven; Bahsi, Hayretdin2019 International Conference on Cyber Security for Emerging Technologies : CSET 2019, Doha, Qatar, 27 October 2019 through 29 October 20192019 / art. 89049088 ; 8 p. : ill https://doi.org/10.1109/CSET.2019.8904908

artikkel kogumikus
Seotud publikatsioonid 1
- Machine learning-based detection and characterization of evolving threats in mobile and IoT Systems = Masinõppepõhine arenevate ohtude tuvastamine ning kirjeldamine mobiilseadmete ja värkvõrkude jaoks

Kirjeid leitud 9, kuvan 1 - 9

1. malware detection
2. mobile malware detection
3. android malware
4. malware analysis
5. Malware behavior
6. Malware characterization
7. Malware evolution
8. malware reverse engineering
9. mobile malware
10. amoxicillin detection
11. anomaly detection
12. anomaly detection for system logs
13. antibiotic detection
14. antibiotics detection
15. aspect detection
16. asynchronous fault detection
17. attack detection
18. barotrauma detection system
19. behaviour-based intrusion detection systems
20. body detection
21. botnet detection
22. capacitively coupled conductivity detection
23. change detection
24. chemical detection
25. community detection
26. compu ter-aided detection(CAD)
27. computer-aided detection
28. computer‐aided detection
29. contactless conductivity detection
30. contactless conductivity detection (C4D)
31. crack detection
32. crash detection
33. cyber intrusion detection
34. defect detection
35. detection
36. detection efficiency
37. detection engineering
38. detection method
39. detection methods
40. detection of anomalous end user nodes
41. detection of hydrogen isotopes
42. distributed detection
43. early detection
44. early intrusion detection
45. energy detection
46. error detection
47. ESI-MS and IM detection
48. Event detection
49. extraction and detection methods
50. face detection
51. Face Manipulation Detection
52. failure detection
53. fall detection
54. fault detection
55. fault detection and diagnoses
56. fault detection and diagnosis
57. Fish detection
58. fouling detection
59. harmonic detection
60. hepatitis C virus (HCV) detection
61. hubs detection
62. IED detection
63. image-based crack detection
64. indicident detection and response
65. indirect UV absorbance detection
66. intrusion detection
67. intrusion detection system
68. intrusion detection system (IDS)
69. intrusion detection systems
70. island detection
71. islanding detection
72. label-free detection
73. LED fluorescence detection
74. leg detection
75. light detection and ranging
76. light detection and ranging (LiDAR)
77. Light Detection and Ranging (LiDAR) point cloud
78. limit of detection
79. lock-in detection
80. loop-closure detection
81. marker detection
82. money laundering detection systems
83. monitoring and detection
84. multi-classed object detection
85. Multi-valued Simulation for Hazard Detection in Digital Circuits
86. mutant detection
87. network anomaly detection
88. network intrusion detection system
89. nodules detection
90. object detection
91. oil-spill detection
92. outlier’s detection methods
93. outliers detection
94. peak detection
95. phytoplankton detection methods
96. plagiarism detection
97. position detection
98. precursor detection
99. protein detection
100. proton detection
101. radar detection
102. ramp event detection
103. recycled FPGA detection
104. residual current detection
105. robust detection
106. scene text detection
107. short-circuit detection
108. small molecule detection
109. speech activity detection
110. Suicidal ideation detection
111. synchronous detection
112. tyre detection
113. unmanned aerial vehicle detection systems
114. unsupervised outlier detection
115. UV detection
116. vehicle detection
117. vortex detection
118. 3D lane detection

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