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1. Advances in Hardware Trojan Detection
Computer, ISSN 0018-9162, 01/2019, Volume 52, Issue 6
Malware
Journal Article
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2. Anti-Virtualization in Dynamic Analysis of Malicious Code
by Jian-Ping Mo and Ling-Yun Ying and Pu-Rui Su and Jia-Jie Wang
Jisuanji Xitong Yingyong = Computer Systems and Applications, ISSN 1003-3254, 01/2018, Issue 12
Anti-virtualization is currently an important factor affecting the overall acquisition of sample behaviour data by a dynamic analysis system of malicious code.... 
Malware
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3. Full Text PROPUESTA DE SELLADO DE TIEMPO INDEPENDIENTE DE UNA AUTORIDAD CERTIFICADORA
by Romel Vera Cadena and Rayner Durango
3C Tecnologia, 01/2017, Volume 6, Issue 4, p. 24
EL SELLADO DE TIEMPO CONFIABLE SE EMPLEA PARA CERTIFICAR QUE UN DOCUMENTO INFORMaTICO SE ENCUENTRE iNTEGRO DESDE LA FECHA EN QUE SE REGISTRo, SIN EMBARGO, EL... 
Malware
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4. Full Text A survey of similarities in banking malware behaviours
by Black, Paul and Gondal, Iqbal and Layton, Robert
Computers & Security, ISSN 0167-4048, 08/2018, Volume 77, pp. 756 - 772
Banking malware are a class of information stealing malicious software that target the financial industry. Banking malware families have become persistent with... 
Malware components | Banking malware | Malware similarity | Malware analysis | Malware capabilities | COMPUTER SCIENCE, INFORMATION SYSTEMS | Surveys | Usage | Applications programming | Banks (Finance) | Spyware
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5. Full Text Manufacturing compromise
: the emergence of exploit-as-a-service
by Grier, Chris and Ballard, Lucas and Caballero, Juan and Chachra, Neha and Dietrich, Christian and Levchenko, Kirill and Mavrommatis, Panayiotis and McCoy, Damon and Nappa, Antonio and Pitsillidis, Andreas and Provos, Niels and Rafique, M and Rajab, Moheeb and Rossow, Christian and Thomas, Kurt and Paxson, Vern and Savage, Stefan and Voelker, Geoffrey
Proceedings of the 2012 ACM conference on computer and communications security, ISSN 1543-7221, 10/2012, pp. 821 - 832
We investigate the emergence of the exploit-as-a-service model for driveby browser compromise. In this regime, attackers pay for an exploit kit or service to... 
malware | Security | Malware
Conference Proceeding
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6. Full Text Malware architectural view with performance analysis in network at its activation state
by Kapat, Sisira Kumar and Tripathy, Satya Narayan
Advances in Intelligent Systems and Computing, ISSN 2194-5357, 2019, Volume 768, pp. 207 - 216
Prepending malware | Position-independent malware | Malware architecture | Independent malware | Appending malware | Categories of malware
Conference Proceeding
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7. Full Text The rise of “malware”: Bibliometric analysis of malware study
by Razak, Mohd Faizal Ab and Anuar, Nor Badrul and Salleh, Rosli and Firdaus, Ahmad
Journal of Network and Computer Applications, ISSN 1084-8045, 11/2016, Volume 75, pp. 58 - 76
Malicious software (malware) is a computer program designed to create harmful and undesirable effects. It considered as one of the many dangerous threats for... 
Malware | Mobile malware | Bibliometric analysis | Malware analysis | Intrusion detection system
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8. Full Text MALWARE DETECTION METHOD BASED ON THE PROGRAM DISTRIBUTION PROCESS ANALYSIS
by I. A. Zikratov and R. S. Vasilenko
Nauchno-Tekhnicheskii Vestnik Informatsionnykh Tekhnologii, Mekhaniki i Optiki, ISSN 2226-1494, 03/2012, Volume 12, Issue 2
The main problems of traditional methods of malicious software detection, based on the virus databases updatingare analyzed. Alternative methods based on cloud... 
Malware
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9. Full Text Android Security: A Survey of Issues, Malware Penetration, and Defenses
by Faruki, Parvez and Bharmal, Ammar and Laxmi, Vijay and Ganmoor, Vijay and Gaur, Manoj Singh and Conti, Mauro and Rajarajan, Muttukrishnan
IEEE Communications Surveys & Tutorials, ISSN 1553-877X, 2015, Volume 17, Issue 2, pp. 998 - 1022
Smartphones have become pervasive due to the availability of office applications, Internet, games, vehicle guidance using location-based services apart from... 
Google | Android Malware | Obfuscation | Humanoid robots | Tutorials | Malware | Dynamic Analysis | Behavioral Analysis | Androids | Static Analysis | Smart phones | Stealth Malwar | SYSTEM | stealth malware | static analysis | COMPUTER SCIENCE, INFORMATION SYSTEMS | Android malware | behavioral analysis | dynamic analysis | TELECOMMUNICATIONS | obfuscation
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10. Bugs
by Dunn, Antony, 1973
2009, Oxford poets, ISBN 1903039959, 63
Insects | Malware (Computer software) | Diseases
Book
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11. Technology and the law on the use of force
: new security challenges in the twenty-first century
by Maogoto, Jackson Nyamuya, 1975- author
2016, 1, Routledge research in international law, ISBN 9781138245228, 111 pages
As governmental and non-governmental operations become progressively supported by vast automated systems and electronic data flows, attacks of government... 
War (International law) | Prevention | Information warfare (International law) | Cyberterrorism | Malware (Computer software) | Law and legislation | Computer networks | Cyber intelligence (Computer security) | Computer security | Security measures | International Relations | International Law - Law | Public International Law | War & Conflict Studies | War
Book
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12. Full Text Correction: Homology analysis of malware based on ensemble learning and multifeatures
by Xue, Di and Li, Jingmei and Wu, Weifei and Tian, Qiao and Wang, JiaXiang
PLoS ONE, ISSN 1932-6203, 10/2019, Volume 14, Issue 10, p. e0223679
[This corrects the article DOI: 10.1371/journal.pone.0211373.]. 
Homology | Malware
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13. Full Text An opcode-based technique for polymorphic Internet of Things malware detection
by Darabian, Hamid and Dehghantanha, Ali and Hashemi, Sattar and Homayoun, Sajad and Choo, Kim-Kwang Raymond
Concurrency Computation, ISSN 1532-0626, 2019, p. e5173
polymorphic malware | IoT security | malware detection | IoT malware
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14. Seven deadliest social network attacks
by Timm, Carl and Perez, Richard, 1969 October 17 and Ely, Adam and Books24x7, Inc
2010, 1, Syngress seven deadliest attacks series, ISBN 9781597495455, xxi, 133
Seven Deadliest Social Network Attacks provides a comprehensive view into how social networking attacks have impacted the livelihood and lives of adults and... 
Prevention | Web 2.0 | Malware (Computer software) | Computer networks | Computer security | Computer crimes | Security measures | Online social networks | Security
Book
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15. A framework for generating malware threat intelligence
by Gandotra, Ekta and Bansal, Divya and Sofat, Sanjeev
Scalable Computing, ISSN 1895-1767, 2017, Volume 18, Issue 3, pp. 195 - 205
Malware | Threat intelligence | Malware analysis | Malware detection | Malware threat level
Journal Article
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16. Full Text PUMA: Permission usage to detect malware in android
by Sanz, Borja and Santos, Igor and Laorden, Carlos and Ugarte-Pedrero, Xabier and Bringas, Pablo Garcia and Álvarez, Gonzalo
Advances in Intelligent Systems and Computing, ISSN 2194-5357, 2013, Volume 189, pp. 289 - 298
mobile malware | malware detection | machine learning | Android
Conference Proceeding
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17. Full Text Breaking bad: Forecasting adversarial android bad behavior
by Li, Shang and Kumar, Srijan and Dumitras, Tudor and Subrahmanian, V.S
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN 0302-9743, 2018, Volume 11170, pp. 405 - 431
Cybersecurity | Mobile malware | Malware detection | Deception | Android
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18. Full Text Detecting malware evolution using support vector machines
by Wadkar, Mayuri and Di Troia, Fabio and Stamp, Mark
Expert Systems With Applications, ISSN 0957-4174, 04/2020, Volume 143, p. 113022
Malware families typically evolve over a period of time. Differences between malware samples within a single family can originate from various code... 
Feature analysis, malware evolution | Malware | Support vector machine
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19. Full Text Improved information on astrophysical S-factor for the 10B(p, α0)7Be reaction using the Trojan Horse method
by Cvetinović, A and Spitaleri, C and Spartá, R and Rapisarda, G.G and Puglia, S.M.R and La Cognata, M and Cherubini, S and Guardo, G.L and Gulino, M and Lamia, L and Pizzone, R.G and Romano, S and Sergi, M.L and Tumino, A
EPJ Web of Conferences, ISSN 2101-6275, 06/2018, Volume 184, p. 02002
The 10B(p,α0)7Be reaction has been studied by applying the Trojan Horse method to the 2H(10B,α0 7Be)n reaction. The bare-nucleus astrophysical S(E)-factor in... 
Malware
Conference Proceeding
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20. Full Text Using probabilistic generative models for ranking risks of Android apps
by Peng, Hao and Gates, Chris and Sarma, Bhaskar and Li, Ninghui and Qi, Yuan and Potharaju, Rahul and Nita-Rotaru, Cristina and Molloy, Ian
Proceedings of the 2012 ACM conference on computer and communications security, ISSN 1543-7221, 10/2012, pp. 241 - 252
One of Android's main defense mechanisms against malicious apps is a risk communication mechanism which, before a user installs an app, warns the user about... 
mobile | risk | malware | data mining | Risk | Malware | Data mining | Mobile
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