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

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