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malware detection (võtmesõna)

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Kirjeid leitud 9
Vaata veel.. (1/141)
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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. AI-based fault detection
11. amoxicillin detection
12. anomaly detection
13. anomaly detection for system logs
14. antibiotic detection
15. antibiotics detection
16. aspect detection
17. asynchronous fault detection
18. attack detection
19. barotrauma detection system
20. Barotrauma detection system sensors
21. behaviour-based intrusion detection systems
22. body detection
23. botnet detection
24. capacitively coupled conductivity detection
25. change detection
26. chemical detection
27. community detection
28. compu ter-aided detection(CAD)
29. computer-aided detection
30. computer‐aided detection
31. contactless conductivity detection
32. contactless conductivity detection (C4D)
33. crack detection
34. crash detection
35. cyber intrusion detection
36. deepfake detection
37. defect detection
38. dementia detection
39. detection
40. detection efficiency
41. detection engineering
42. detection mechanisms
43. detection method
44. detection methods
45. detection of anomalous end user nodes
46. detection of hydrogen isotopes
47. distributed detection
48. early detection
49. early intrusion detection
50. electronic warfare activity detection
51. energy detection
52. error detection
53. ESI-MS and IM detection
54. evaluation of explainable AI intrusion detection
55. Event detection
56. extraction and detection methods
57. face detection
58. Face Manipulation Detection
59. failure detection
60. fall detection
61. fault detection
62. fault detection and classification
63. fault detection and diagnoses
64. fault detection and diagnosis
65. fault detection and diagnostics (FDD)
66. Fish detection
67. fouling detection
68. hardware trojan detection
69. harmonic detection
70. health care IoMT intrusion detection
71. hepatitis C virus (HCV) detection
72. hubs detection
73. hybrid fault detection
74. IED detection
75. image-based crack detection
76. indicident detection and response
77. indirect UV absorbance detection
78. intrusion detection
79. intrusion detection system (IDS)
80. intrusion detection systems
81. intrusion detection systems (IDS)
82. island detection
83. islanding detection
84. label-free detection
85. lane detection
86. lane line detection
87. LED fluorescence detection
88. leg detection
89. light detection and ranging
90. light detection and ranging (LiDAR)
91. Light Detection and Ranging (LiDAR) point cloud
92. limit of detection
93. LLM-based template detection from security event logs
94. lock-in detection
95. loop-closure detection
96. marker detection
97. molecular detection
98. money laundering detection systems
99. monitoring and detection
100. multi-classed object detection
101. Multi-valued Simulation for Hazard Detection in Digital Circuits
102. mutant detection
103. network anomaly detection
104. network intrusion detection system
105. nodules detection
106. object detection
107. oil-spill detection
108. outlier’s detection methods
109. outliers detection
110. peak detection
111. photovoltaic fault detection algorithms
112. phytoplankton detection methods
113. plagiarism detection
114. position detection
115. precursor detection
116. propaganda detection
117. protein detection
118. proton detection
119. radar detection
120. ramp event detection
121. Real-time occupancy detection
122. recycled FPGA detection
123. residual current detection
124. robust detection
125. scene text detection
126. short-circuit detection
127. Side-Channel Attack Detection
128. signal anomaly detection
129. small molecule detection
130. speech activity detection
131. Suicidal ideation detection
132. synchronous detection
133. Template detection from event logs
134. topic detection
135. tyre detection
136. unmanned aerial vehicle detection systems
137. unsupervised outlier detection
138. UV detection
139. vehicle detection
140. vortex detection
141. 3D lane detection

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