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Synopsis
Use of mobile phones for getting to the web has extended broadly, anyway paying little heed to basic advances in processor power and exchange speed, using PDAs for examining isn't equivalent to work region scrutinizing. Content constituents and page arrangements are used to perform static goals to decide vindictiveness in the page content space. The investigation way centers on building an enhanced framework to distinguish malignant destinations consistently by joining of Dynamic recognizable proof methodologies. In the continuous separated from utilizing since quite a while ago settled static methodologies recommended already the dynamic examination bases on API Calls Observation and Filtration and furthermore for each malware family a plan of precedents are recognized, every model addressed a changed watched variation of the first malware record. The present work additionally centers on examining the executable page contents for malevolent code identification for API calls present in the content. Exploratory outcomes demonstrate that the enhanced strategy performs superior to past methodology that centers on just static examination.
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Malware Detection By Using Logistic Regression With Dynamic Analysis
Published by
LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200082642
ISBN 13: 9786200082640
New
Softcover
Seller: Books Puddle, New York, NY, U.S.A.
Seller rating 4 out of 5 stars
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Malware Detection By Using Logistic Regression With Dynamic Analysis
Published by
LAP LAMBERT Academic Publishing Apr 2019, 2019
ISBN 10: 6200082642
ISBN 13: 9786200082640
New
Taschenbuch
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Use of mobile phones for getting to the web has extended broadly, anyway paying little heed to basic advances in processor power and exchange speed, using PDAs for examining isn't equivalent to work region scrutinizing. Content constituents and page arrangements are used to perform static goals to decide vindictiveness in the page content space. The investigation way centers on building an enhanced framework to distinguish malignant destinations consistently by joining of Dynamic recognizable proof methodologies. In the continuous separated from utilizing since quite a while ago settled static methodologies recommended already the dynamic examination bases on API Calls Observation and Filtration and furthermore for each malware family a plan of precedents are recognized, every model addressed a changed watched variation of the first malware record. The present work additionally centers on examining the executable page contents for malevolent code identification for API calls present in the content. Exploratory outcomes demonstrate that the enhanced strategy performs superior to past methodology that centers on just static examination. 56 pp. Englisch. Seller Inventory # 9786200082640
Quantity: 2 available
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Malware Detection By Using Logistic Regression With Dynamic Analysis
Published by
LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200082642
ISBN 13: 9786200082640
New
Softcover
Seller: Majestic Books, Hounslow, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. Print on Demand. Seller Inventory # 401424442
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Malware Detection By Using Logistic Regression With Dynamic Analysis
Published by
LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200082642
ISBN 13: 9786200082640
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Use of mobile phones for getting to the web has extended broadly, anyway paying little heed to basic advances in processor power and exchange speed, using PDAs for examining isn't equivalent to work region scrutinizing. Content constituents and page arrangements are used to perform static goals to decide vindictiveness in the page content space. The investigation way centers on building an enhanced framework to distinguish malignant destinations consistently by joining of Dynamic recognizable proof methodologies. In the continuous separated from utilizing since quite a while ago settled static methodologies recommended already the dynamic examination bases on API Calls Observation and Filtration and furthermore for each malware family a plan of precedents are recognized, every model addressed a changed watched variation of the first malware record. The present work additionally centers on examining the executable page contents for malevolent code identification for API calls present in the content. Exploratory outcomes demonstrate that the enhanced strategy performs superior to past methodology that centers on just static examination. Seller Inventory # 9786200082640
Quantity: 1 available
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Malware Detection By Using Logistic Regression With Dynamic Analysis
Published by
LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200082642
ISBN 13: 9786200082640
New
Softcover
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Malware Detection By Using Logistic Regression With Dynamic Analysis
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LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200082642
ISBN 13: 9786200082640
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Paperback. Condition: Brand New. 56 pages. 8.66x5.91x0.13 inches. In Stock. Seller Inventory # zk6200082642
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Malware Detection By Using Logistic Regression With Dynamic Analysis
Published by
LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200082642
ISBN 13: 9786200082640
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Seller: moluna, Greven, Germany
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Gupta DeepaliMiss Deepali Gupta is research scholar perusing her M.Tech degree in computer science in Vishwavidyalaya Engineering College Ambikapur.Her interests include Artificial intelligence, Data Mining.Use of mobile phones f. Seller Inventory # 290225580
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Malware Detection By Using Logistic Regression With Dynamic Analysis
Published by
LAP LAMBERT Academic Publishing Apr 2019, 2019
ISBN 10: 6200082642
ISBN 13: 9786200082640
New
Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Neuware -Use of mobile phones for getting to the web has extended broadly, anyway paying little heed to basic advances in processor power and exchange speed, using PDAs for examining isn't equivalent to work region scrutinizing. Content constituents and page arrangements are used to perform static goals to decide vindictiveness in the page content space. The investigation way centers on building an enhanced framework to distinguish malignant destinations consistently by joining of Dynamic recognizable proof methodologies. In the continuous separated from utilizing since quite a while ago settled static methodologies recommended already the dynamic examination bases on API Calls Observation and Filtration and furthermore for each malware family a plan of precedents are recognized, every model addressed a changed watched variation of the first malware record. The present work additionally centers on examining the executable page contents for malevolent code identification for API calls present in the content. Exploratory outcomes demonstrate that the enhanced strategy performs superior to past methodology that centers on just static examination.Books on Demand GmbH, Überseering 33, 22297 Hamburg 56 pp. Englisch. Seller Inventory # 9786200082640
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