CIAA-RepDroid: A Fine-Grained and Probabilistic Reputation Scheme for Android Apps Based on Sentiment Analysis of Reviews

To keep its business reliable, Google is concerned to ensure the quality of apps on the store. One crucial aspect concerning quality is security. Security is achieved through Google Play protect and anti-malware solutions. However, they are not totally efficient since they rely on application featur...

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Veröffentlicht in:	Future internet Jg. 12; H. 9; S. 145
Hauptverfasser:	Tchakounté, Franklin, Yera Pagor, Athanase Esdras, Kamgang, Jean Claude, Atemkeng, Marcellin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.09.2020
Schlagworte:	Analysis android application Application programming interface Applications programs Availability Confidentiality Control Data mining Data security Electronic banking Ergonomics Integrity Internet Keywords Machine learning Malware Mobile applications Operating systems (Software) Ratings & rankings reputation Reputations reviews Security aspects security service Sentiment analysis Sentimentality Social networks Software security System effectiveness Cameroon
ISSN:	1999-5903, 1999-5903
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Abstract	To keep its business reliable, Google is concerned to ensure the quality of apps on the store. One crucial aspect concerning quality is security. Security is achieved through Google Play protect and anti-malware solutions. However, they are not totally efficient since they rely on application features and application execution threads. Google provides additional elements to enable consumers to collectively evaluate applications providing their experiences via reviews or showing their satisfaction through rating. The latter is more informal and hides details of rating whereas the former is textually expressive but requires further processing to understand opinions behind it. Literature lacks approaches which mine reviews through sentiment analysis to extract useful information to improve the security aspects of provided applications. This work goes in this direction and in a fine-grained way, investigates in terms of confidentiality, integrity, availability, and authentication (CIAA). While assuming that reviews are reliable and not fake, the proposed approach determines review polarities based on CIAA-related keywords. We rely on the popular classifier Naive Bayes to classify reviews into positive, negative, and neutral sentiment. We then provide an aggregation model to fusion different polarities to obtain application global and CIAA reputations. Quantitative experiments have been conducted on 13 applications including e-banking, live messaging and anti-malware apps with a total of 1050 security-related reviews and 7,835,322 functionality-related reviews. Results show that 23% of applications (03 apps) have a reputation greater than 0.5 with an accent on integrity, authentication, and availability, while the remaining 77% has a polarity under 0.5. Developers should make a lot of effort in security while developing codes and that more efforts should be made to improve confidentiality reputation. Results also show that applications with good functionality-related reputation generally offer a bad security-related reputation. This situation means that even if the number of security reviews is low, it does not mean that the security aspect is not a consumer preoccupation. Unlike, developers put much more time to test whether applications work without errors even if they include possible security vulnerabilities. A quantitative comparison against well-known rating systems reveals the effectiveness and robustness of CIAA-RepDroid to repute apps in terms of security. CIAA-RepDroid can be associated with existing rating solutions to recommend developers exact CIAA aspects to improve within source codes.
AbstractList	To keep its business reliable, Google is concerned to ensure the quality of apps on the store. One crucial aspect concerning quality is security. Security is achieved through Google Play protect and anti-malware solutions. However, they are not totally efficient since they rely on application features and application execution threads. Google provides additional elements to enable consumers to collectively evaluate applications providing their experiences via reviews or showing their satisfaction through rating. The latter is more informal and hides details of rating whereas the former is textually expressive but requires further processing to understand opinions behind it. Literature lacks approaches which mine reviews through sentiment analysis to extract useful information to improve the security aspects of provided applications. This work goes in this direction and in a fine-grained way, investigates in terms of confidentiality, integrity, availability, and authentication (CIAA). While assuming that reviews are reliable and not fake, the proposed approach determines review polarities based on CIAA-related keywords. We rely on the popular classifier Naive Bayes to classify reviews into positive, negative, and neutral sentiment. We then provide an aggregation model to fusion different polarities to obtain application global and CIAA reputations. Quantitative experiments have been conducted on 13 applications including e-banking, live messaging and anti-malware apps with a total of 1050 security-related reviews and 7,835,322 functionality-related reviews. Results show that 23% of applications (03 apps) have a reputation greater than 0.5 with an accent on integrity, authentication, and availability, while the remaining 77% has a polarity under 0.5. Developers should make a lot of effort in security while developing codes and that more efforts should be made to improve confidentiality reputation. Results also show that applications with good functionality-related reputation generally offer a bad security-related reputation. This situation means that even if the number of security reviews is low, it does not mean that the security aspect is not a consumer preoccupation. Unlike, developers put much more time to test whether applications work without errors even if they include possible security vulnerabilities. A quantitative comparison against well-known rating systems reveals the effectiveness and robustness of CIAA-RepDroid to repute apps in terms of security. CIAA-RepDroid can be associated with existing rating solutions to recommend developers exact CIAA aspects to improve within source codes. To keep its business reliable, Google is concerned to ensure the quality of apps on the store. One crucial aspect concerning quality is security. Security is achieved through Google Play protect and anti-malware solutions. However, they are not totally efficient since they rely on application features and application execution threads. Google provides additional elements to enable consumers to collectively evaluate applications providing their experiences via reviews or showing their satisfaction through rating. The latter is more informal and hides details of rating whereas the former is textually expressive but requires further processing to understand opinions behind it. Literature lacks approaches which mine reviews through sentiment analysis to extract useful information to improve the security aspects of provided applications. This work goes in this direction and in a fine-grained way, investigates in terms of confidentiality, integrity, availability, and authentication (CIAA). While assuming that reviews are reliable and not fake, the proposed approach determines review polarities based on CIAA-related keywords. We rely on the popular classifier Naive Bayes to classify reviews into positive, negative, and neutral sentiment. We then provide an aggregation model to fusion different polarities to obtain application global and CIAA reputations. Quantitative experiments have been conducted on 13 applications including e-banking, live messaging and anti-malware apps with a total of 1050 security-related reviews and 7,835,322 functionality-related reviews. Results show that 23% of applications (03 apps) have a reputation greater than 0.5 with an accent on integrity, authentication, and availability, while the remaining 77% has a polarity under 0.5. Developers should make a lot of effort in security while developing codes and that more efforts should be made to improve confidentiality reputation. Results also show that applications with good functionality-related reputation generally offer a bad security-related reputation. This situation means that even if the number of security reviews is low, it does not mean that the security aspect is not a consumer preoccupation. Unlike, developers put much more time to test whether applications work without errors even if they include possible security vulnerabilities. A quantitative comparison against well-known rating systems reveals the effectiveness and robustness of CIAA-RepDroid to repute apps in terms of security. CIAA-RepDroid can be associated with existing rating solutions to recommend developers exact CIAA aspects to improve within source codes. Keywords: reputation; android; application; sentiment analysis; reviews; security service; NLP; Google Play; polarity
Audience	Academic
Author	Tchakounté, Franklin Kamgang, Jean Claude Yera Pagor, Athanase Esdras Atemkeng, Marcellin
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References	Raghuraman (ref_16) 2020; Volume 1045 ref_50 Gajrani (ref_13) 2020; Volume 119 ref_58 Kou (ref_25) 2019; 478 ref_56 ref_55 ref_10 ref_54 ref_53 Alzaylaee (ref_18) 2020; 89 ref_52 ref_51 Tiguiane (ref_11) 2019; 35 ref_59 Taheri (ref_9) 2020; 105 ref_60 Martinelli (ref_12) 2020; 50 Tang (ref_15) 2020; 25 Alazab (ref_8) 2020; 107 ref_24 Abran (ref_23) 2017; 125 ref_21 Abdullah (ref_14) 2020; Volume 978 AISC Khalid (ref_36) 2015; 32 ref_29 ref_26 Haryanto (ref_57) 2019; 161 Pan (ref_7) 2020; 8 ref_35 ref_34 ref_32 ref_31 Wang (ref_17) 2020; 167 ref_30 Tao (ref_46) 2020; 122 ref_39 ref_38 ref_37 Nagappan (ref_22) 2016; 33 Woods (ref_19) 2020; 63 Oyebode (ref_33) 2020; 8 ref_47 Li (ref_27) 2018; 14 Fu (ref_40) 2013; Volume Part F128815 ref_44 Xiao (ref_28) 2020; 163 ref_43 Hatamian (ref_45) 2019; 83 ref_42 ref_41 ref_1 ref_3 ref_2 ref_49 ref_48 Hendrikx (ref_20) 2015; 75 ref_5 ref_4 ref_6
References_xml	– volume: 161 start-page: 715 year: 2019 ident: ref_57 article-title: Facebook analysis of community sentiment on 2019 Indonesian presidential candidates from Facebook opinion data publication-title: Procedia Comput. Sci. doi: 10.1016/j.procs.2019.11.175 – volume: 8 start-page: 116363 year: 2020 ident: ref_7 article-title: A Systematic Literature Review of Android Malware Detection Using Static Analysis publication-title: IEEE Access doi: 10.1109/ACCESS.2020.3002842 – ident: ref_10 doi: 10.1016/B978-0-12-804629-6.00006-7 – ident: ref_5 – ident: ref_55 – ident: ref_41 doi: 10.1145/2884781.2884818 – ident: ref_21 doi: 10.1109/ICEEICT.2014.6919058 – ident: ref_26 doi: 10.1145/3325917.3325941 – volume: 107 start-page: 509 year: 2020 ident: ref_8 article-title: Intelligent mobile malware detection using permission requests and API calls publication-title: Future Gener. Comput. Syst. doi: 10.1016/j.future.2020.02.002 – ident: ref_37 doi: 10.1109/ASE.2015.57 – ident: ref_38 doi: 10.1109/SP.2019.00012 – volume: 63 start-page: 104 year: 2020 ident: ref_19 article-title: Cyber Warranties: Market Fix or Marketing Trick? publication-title: Commun. ACM doi: 10.1145/3360310 – volume: 75 start-page: 184 year: 2015 ident: ref_20 article-title: Reputation systems: A survey and taxonomy publication-title: J. Parallel Distrib. Comput. doi: 10.1016/j.jpdc.2014.08.004 – ident: ref_49 doi: 10.1007/978-981-15-1675-7_2 – ident: ref_50 doi: 10.1007/s42044-020-00068-w – ident: ref_31 doi: 10.1109/IRI.2017.79 – ident: ref_32 doi: 10.20944/preprints202003.0249.v1 – volume: 32 start-page: 70 year: 2015 ident: ref_36 article-title: What do mobile app users complain about? publication-title: IEEE Softw. doi: 10.1109/MS.2014.50 – ident: ref_39 doi: 10.1109/ICSE.2017.18 – ident: ref_42 doi: 10.1145/3180155.3180218 – volume: 105 start-page: 230 year: 2020 ident: ref_9 article-title: Similarity-based Android malware detection using Hamming distance of static binary features publication-title: Future Gener. Comput. Syst. doi: 10.1016/j.future.2019.11.034 – ident: ref_43 doi: 10.1109/ISSRE.2015.7381797 – volume: Volume 978 AISC start-page: 121 year: 2020 ident: ref_14 article-title: Android Ransomware Detection Based on Dynamic Obtained Features publication-title: Advances in Intelligent Systems and Computing doi: 10.1007/978-3-030-36056-6_12 – ident: ref_4 – ident: ref_56 – volume: 8 start-page: 111141 year: 2020 ident: ref_33 article-title: Using Machine Learning and Thematic Analysis Methods to Evaluate Mental Health Apps Based on User Reviews publication-title: IEEE Access doi: 10.1109/ACCESS.2020.3002176 – volume: Volume Part F128815 start-page: 1276 year: 2013 ident: ref_40 article-title: Why people hate your App-Making sense of user feedback in a mobile app store publication-title: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining doi: 10.1145/2487575.2488202 – ident: ref_52 – ident: ref_1 doi: 10.1007/s13369-020-04365-1 – ident: ref_58 doi: 10.1007/978-3-030-06176-0 – volume: 89 start-page: 101663 year: 2020 ident: ref_18 article-title: DL-Droid: Deep learning based android malware detection using real devices publication-title: Comput. Secur. doi: 10.1016/j.cose.2019.101663 – volume: 83 start-page: 332 year: 2019 ident: ref_45 article-title: Revealing the unrevealed: Mining smartphone users privacy perception on app markets publication-title: Comput. Secur. doi: 10.1016/j.cose.2019.02.010 – volume: 125 start-page: 207 year: 2017 ident: ref_23 article-title: A systematic literature review: Opinion mining studies from mobile app store user reviews publication-title: J. Syst. Softw. doi: 10.1016/j.jss.2016.11.027 – volume: 163 start-page: 110533 year: 2020 ident: ref_28 article-title: An Android application risk evaluation framework based on minimum permission set identification publication-title: J. Syst. Softw. doi: 10.1016/j.jss.2020.110533 – ident: ref_59 – ident: ref_53 – volume: 25 start-page: 589 year: 2020 ident: ref_15 article-title: A novel hybrid method to analyze security vulnerabilities in android applications publication-title: Tsinghua Sci. Technol. doi: 10.26599/TST.2019.9010067 – volume: 167 start-page: 110609 year: 2020 ident: ref_17 article-title: Identifying vulnerabilities of SSL/TLS certificate verification in Android apps with static and dynamic analysis publication-title: J. Syst. Softw. doi: 10.1016/j.jss.2020.110609 – volume: 122 start-page: 106290 year: 2020 ident: ref_46 article-title: Identifying security issues for mobile applications based on user review summarization publication-title: Inf. Softw. Technol. doi: 10.1016/j.infsof.2020.106290 – ident: ref_3 – volume: Volume 119 start-page: 73 year: 2020 ident: ref_13 article-title: Effectiveness of state-of-the-art dynamic analysis techniques in identifying diverse Android malware and future enhancements publication-title: Advances in Computers doi: 10.1016/bs.adcom.2020.03.002 – ident: ref_24 – volume: 33 start-page: 86 year: 2016 ident: ref_22 article-title: Examining the Rating System Used in Mobile-App Stores publication-title: IEEE Softw. doi: 10.1109/MS.2015.56 – volume: 50 start-page: 102423 year: 2020 ident: ref_12 article-title: Visualizing the outcome of dynamic analysis of Android malware with VizMal publication-title: J. Inf. Secur. Appl. – ident: ref_34 doi: 10.1109/RE.2014.6912257 – volume: 478 start-page: 461 year: 2019 ident: ref_25 article-title: A review on trust propagation and opinion dynamics in social networks and group decision making frameworks publication-title: Inf. Sci. doi: 10.1016/j.ins.2018.11.037 – volume: 35 start-page: 26 year: 2019 ident: ref_11 article-title: Detection of Android Malware based on Sequence Alignment of Permissions publication-title: Int. J. Comput. (IJC) – ident: ref_6 – ident: ref_51 doi: 10.20944/preprints202007.0646.v1 – ident: ref_29 – ident: ref_54 – ident: ref_48 doi: 10.1109/TPS-ISA48467.2019.00024 – ident: ref_2 – ident: ref_30 doi: 10.1145/2976749.2978343 – ident: ref_47 doi: 10.1109/TrustCom.2012.236 – ident: ref_60 – volume: 14 start-page: 3216 year: 2018 ident: ref_27 article-title: Significant Permission Identification for Machine-Learning-Based Android Malware Detection publication-title: IEEE Trans. Ind. Inform. doi: 10.1109/TII.2017.2789219 – ident: ref_44 doi: 10.1109/DSN.2018.00051 – volume: Volume 1045 start-page: 793 year: 2020 ident: ref_16 article-title: Static and dynamic malware analysis using machine learning publication-title: Advances in Intelligent Systems and Computing doi: 10.1007/978-981-15-0029-9_62 – ident: ref_35 doi: 10.3390/info11030152
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SubjectTerms	Analysis android application Application programming interface Applications programs Availability Confidentiality Control Data mining Data security Electronic banking Ergonomics Integrity Internet Keywords Machine learning Malware Mobile applications Operating systems (Software) Ratings & rankings reputation Reputations reviews Security aspects security service Sentiment analysis Sentimentality Social networks Software security System effectiveness
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Title	CIAA-RepDroid: A Fine-Grained and Probabilistic Reputation Scheme for Android Apps Based on Sentiment Analysis of Reviews
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