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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 mechanisms
40. detection method
41. detection methods
42. detection of anomalous end user nodes
43. detection of hydrogen isotopes
44. distributed detection
45. early detection
46. early intrusion detection
47. energy detection
48. error detection
49. ESI-MS and IM detection
50. Event detection
51. extraction and detection methods
52. face detection
53. Face Manipulation Detection
54. failure detection
55. fall detection
56. fault detection
57. fault detection and diagnoses
58. fault detection and diagnosis
59. Fish detection
60. fouling detection
61. harmonic detection
62. hepatitis C virus (HCV) detection
63. hubs detection
64. IED detection
65. image-based crack detection
66. indicident detection and response
67. indirect UV absorbance detection
68. intrusion detection
69. intrusion detection system
70. intrusion detection system (IDS)
71. intrusion detection systems
72. island detection
73. islanding detection
74. label-free detection
75. lane detection
76. LED fluorescence detection
77. leg detection
78. light detection and ranging
79. light detection and ranging (LiDAR)
80. Light Detection and Ranging (LiDAR) point cloud
81. limit of detection
82. lock-in detection
83. loop-closure detection
84. marker detection
85. money laundering detection systems
86. monitoring and detection
87. multi-classed object detection
88. Multi-valued Simulation for Hazard Detection in Digital Circuits
89. mutant detection
90. network anomaly detection
91. network intrusion detection system
92. nodules detection
93. object detection
94. oil-spill detection
95. outlier’s detection methods
96. outliers detection
97. peak detection
98. phytoplankton detection methods
99. plagiarism detection
100. position detection
101. precursor detection
102. protein detection
103. proton detection
104. radar detection
105. ramp event detection
106. recycled FPGA detection
107. residual current detection
108. robust detection
109. scene text detection
110. short-circuit detection
111. small molecule detection
112. speech activity detection
113. Suicidal ideation detection
114. synchronous detection
115. topic detection
116. tyre detection
117. unmanned aerial vehicle detection systems
118. unsupervised outlier detection
119. UV detection
120. vehicle detection
121. vortex detection
122. 3D lane detection

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