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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. Barotrauma detection system sensors
20. behaviour-based intrusion detection systems
21. body detection
22. botnet detection
23. capacitively coupled conductivity detection
24. change detection
25. chemical detection
26. community detection
27. compu ter-aided detection(CAD)
28. computer-aided detection
29. computer‐aided detection
30. contactless conductivity detection
31. contactless conductivity detection (C4D)
32. crack detection
33. crash detection
34. cyber intrusion detection
35. defect detection
36. detection
37. detection efficiency
38. detection engineering
39. detection method
40. detection methods
41. detection of anomalous end user nodes
42. detection of hydrogen isotopes
43. distributed detection
44. early detection
45. early intrusion detection
46. energy detection
47. error detection
48. ESI-MS and IM detection
49. Event detection
50. extraction and detection methods
51. face detection
52. Face Manipulation Detection
53. failure detection
54. fall detection
55. fault detection
56. fault detection and diagnoses
57. fault detection and diagnosis
58. Fish detection
59. fouling detection
60. harmonic detection
61. hepatitis C virus (HCV) detection
62. hubs detection
63. IED detection
64. image-based crack detection
65. indicident detection and response
66. indirect UV absorbance detection
67. intrusion detection
68. intrusion detection system
69. intrusion detection system (IDS)
70. intrusion detection systems
71. island detection
72. islanding detection
73. label-free detection
74. lane detection
75. LED fluorescence detection
76. leg detection
77. light detection and ranging
78. light detection and ranging (LiDAR)
79. Light Detection and Ranging (LiDAR) point cloud
80. limit of detection
81. lock-in detection
82. loop-closure detection
83. marker detection
84. money laundering detection systems
85. monitoring and detection
86. multi-classed object detection
87. Multi-valued Simulation for Hazard Detection in Digital Circuits
88. mutant detection
89. network anomaly detection
90. network intrusion detection system
91. nodules detection
92. object detection
93. oil-spill detection
94. outlier’s detection methods
95. outliers detection
96. peak detection
97. phytoplankton detection methods
98. plagiarism detection
99. position detection
100. precursor detection
101. protein detection
102. proton detection
103. radar detection
104. ramp event detection
105. recycled FPGA detection
106. residual current detection
107. robust detection
108. scene text detection
109. short-circuit detection
110. small molecule detection
111. speech activity detection
112. Suicidal ideation detection
113. synchronous detection
114. tyre detection
115. unmanned aerial vehicle detection systems
116. unsupervised outlier detection
117. UV detection
118. vehicle detection
119. vortex detection
120. 3D lane detection

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