To cope with the increasing variability and sophistication of modern attacks, machine learning has been widely adopted as a statistically-sound tool for malware detection. However, its security ...against well-crafted attacks has not only been recently questioned, but it has been shown that machine learning exhibits inherent vulnerabilities that can be exploited to evade detection at test time. In other words, machine learning itself can be the weakest link in a security system. In this paper, we rely upon a previously-proposed attack framework to categorize potential attack scenarios against learning-based malware detection tools, by modeling attackers with different skills and capabilities. We then define and implement a set of corresponding evasion attacks to thoroughly assess the security of Drebin, an Android malware detector. The main contribution of this work is the proposal of a simple and scalable secure-learning paradigm that mitigates the impact of evasion attacks, while only slightly worsening the detection rate in the absence of attack. We finally argue that our secure-learning approach can also be readily applied to other malware detection tasks.
•Machine learning aided Android malware classification.•OWASP Seraphimdroid Android app.•Source code analysis utilizing a bag-of-words representation model.•Android file decompiling and machine ...learning-based malware detection.
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The widespread adoption of Android devices and their capability to access significant private and confidential information have resulted in these devices being targeted by malware developers. Existing Android malware analysis techniques can be broadly categorized into static and dynamic analysis. In this paper, we present two machine learning aided approaches for static analysis of Android malware. The first approach is based on permissions and the other is based on source code analysis utilizing a bag-of-words representation model. Our permission-based model is computationally inexpensive, and is implemented as the feature of OWASP Seraphimdroid Android app that can be obtained from Google Play Store. Our evaluations of both approaches indicate an F-score of 95.1% and F-measure of 89% for the source code-based classification and permission-based classification models, respectively.
•Mobile and cloud computing are advantageous to use in a smart factory environment.•A mobile Android OS based manufacturing execution system (MES) is proposed.•The information generated in the mobile ...MES is combined with data from MTConnect.•Valuable information to create a factory digital twin is gathered using the MES.•The concept was tested in a small manufacturing facility.
The availability of data from a manufacturing operation can be used to enable an increase in capability, adaptability, and awareness of the process. In current cyber-physical systems, data are collected from pieces of manufacturing equipment and used to drive useful change and affect production output. The data gathered typically describe the operating state of the equipment, such as a machine tool, and can be provided using standard protocols. One such protocol, known as MTConnect, is becoming increasingly popular to collect data from machine tools. Other useful data can be collected from production personnel using a Manufacturing Execution System (MES) to monitor process output, consumable usage, and operator productivity. However, MTConnect data and MES data usually reside in separate systems that may be proprietary and expensive. This paper describes the development and implementation of a new MES, powered by Android devices and cloud computing tools, that combines MTConnect data with production data collected from operators; the proposed MES is particularly suitable for small manufacturing enterprises, as it is low-cost and easily implementable. A case study using the MES to track a production run of titanium parts is presented, and data from the MES are correlated with MTConnect data from a machine tool. This work is integral to realizing a complete digital model of the shop floor, known as the Shop Floor Digital Twin, that can be used for production control and optimization.
Administration is a fundamental need of society. The implementation is still not practical and simple,resulting in a domino effect that can have an impact on other sectors such as the economy. The ...demographic condition of Krisik Village shows that time inefficiency will result in a lot of losses. Moreover, the absorption of existing village funds shows that the use of paper for administration is still very large which is not in accordance with the 13th point of the Sustainable Development Goals, coupled with the COVID-19 pandemic which has exacerbated the situation with the imposition of various restrictions on sectors in society. This is an urgency for a solution that facilitates the community in the administration sector and the Krisik Village needs a solution to facilitate the administrative process in terms of distribution delivery and management by the village apparatus in order to create an effective, efficient, and face-to-faceminimal system. Based on the needs and conditions of Krisik Village, an online administration solution, namely "Smart Village: Empowerment of Krisik Villages in Blitar Regency through an Intelligent Information System for Application-Based Online Community Administration Services", is an application that can accommodate administrative processes at the village level using the Android system.
The purpose of this study is to produce Android -based shoulder and wrist. This research was conducted on students of the Faculty of Sports Sciences and North Sumatra PON athletes in December 2022. ...Types of research used in this study were development research with Research & Development (R&D) research designs from Borg and Gall. This research was conducted with 9 research stages, namely, (1) Research and Information Collecting, (2) Planning, (3) Developing Preminary Form of Product, (4) Preminary Field Testing, (5) Main Product Revision, (6) Main Field Testing, (7) Operational Product Revision, (8) Operational Field Testing, (9) Final Product Revision. The population in this study by using students of the Faculty of Sports Science and the North Sumatra Taekwondo Pelatda athlete. The technique of picking up using purposive sampling with a trial of phase I of 20 FIK students and the phase II trial of 30 athletes in North Sumatra Taekwondo Pelatda. Furthermore, from the trial of phase I, totaling 20 people showed 96% with very feasible criteria, then from the phase II trial of 30 North Sumatra Taekwondo Pelatda athletes showed 91% with a very decent category. From the results of research /feasibility tests conducted by test experts and measurements, IT experts and sports academics show 96% with a very feasible category, so that it can be used. On the basis of the data obtained, the development of Android -based shoulder and wrist test equipment is declared feasible to be developed as a test tool and measurement of shoulder muscle and wrist.
Tujuan utama penelitian ini adalah untuk menghasilkan media pembelajaran bulutangkis berbasis aplikasi android bagi mahasiswa. Metode penelitian yang digunakan adalah penelitian pengembangan ...(research and development) mengadopsi langkah-langkah penelitian pengembangan dari Borg and Gall tapi hanya sampai pada langkah menghasilkan produk belum menguji keefektifan produk tersebut. Hasil penilaian dari hasil validator ahli bulutangkis sebesar 94% ada pada kategori sangat baik, hasil validator ahli media pembelajaran sebesar 84% ada dalam kategori baik, dan hasil validator ahli teknologi sebesar 90% ada dalam kategori baik. Dengan demikian dapat disimpulkan bahwa berdasarkan hasil angket validasi pakar ahli bulutangkis, media, dan teknologi, bahwa rancangan media pembelajaran bulutangkis berbasis aplikasi android untuk meningkatkan teknik dasar bulutangkis pada mahasiswa dinyatakan layak dengan persentase 89%.
Technology is everyplace we go in moment's life. So, scholars of seminaries or sodalities, or universities bear an operation that supports smartphones to get all types of information related to ...examination, lecture notes, placement, systems regarding announcement, events, transportation, etc. Rather of calling systems because nearly all mobile druggies have smartphones currently. This being system takes a pupil list and allocates administrators to scholars. Using a manual system in the management and allocation of projects to students is characterized by many problems, including the Inability of the project Guide to know that a title has been approved already for a student. Difficulty and inappropriate documentation of allocated project topics. Ineffective in entering, updating, and retrieving records of allocated projects. Difficulty in accessing the project Guide for approval of the topic. Duplication in project topics approved for students. We designed an operation to attain the demand of scholars. The main ideal of the pupil design allocation system is to make a system that will give information for each pupil. Projects can efficiently be allocated to students without delay, and topic conflict between students in the same department will not arise here. Pupil updates can be fluently penetrated if the database system is enhanced. This design will give a fruitful way to manage data at a low cost. The Student Project Allocation contains colorful options similar as login/logout, viewing and streamlining data, etc. It'll be secure. Data can be used by only those with an id and word while maintaining the data.
Trauma merupakan tekanan emosional dan psikologis yang pada umumnya karena kejadian yang tidak menyenangkan atau pengalaman yang berkaitan dengan kekerasan. Secara umum, ada banyak faktor yang bisa ...menyebabkan seseorang mengalami trauma, termasuk peristiwa menyedihkan, mengguncang jiwa, hingga mengancam nyawa. Ini karena kejadian traumatis dapat menyebabkan gangguan streess pasca trauma (PTSD). Untuk mengatasi kesulitan ini, peneliti melakukan pengembangan sebuah aplikasi berbasis Android yang berfungsi sebagai media deteksi awal PTSD dan juga sebagai media informasi yang berkaitan dengan penanganan PTSD. Aplikasi ini dikembangkan menggunakan metode Test Driven Development dan menggunakan Kotlin dan XML sebagai bahasa pemograman dan layouting aplikasi serta, menggunakan Firebase sebagai back end nya. Test Driven Development sendiri merupakan pengembangan perangkat lunak yang menekankan testing sebelum coding yang dimana menggunakan pendekatan Agile dan Extreme Programming.Dengan pengujian Black Box Testing aplikasi dapat berjalan dengan baik dan aplikasi ini memiliki nilai SUS (System Usability Scale) rata-rata sebesar 89.75. Aplikasi telah dipublikasi ke dalam Play Store dengan status pengujian terbuka. Dengan demikian, aplikasi “MentalFirst” ini diharapkan dapat membantu masyarakat dapat melakukan deteksi awal dan mendapatkan informasi yang berkaitan dengan PTSD.
The mobile apps market is one of the fastest growing areas in the information technology. In digging their market share, developers must pay attention to building robust and reliable apps. In fact, ...users easily get frustrated by repeated failures, crashes, and other bugs; hence, they abandon some apps in favor of their competition. In this paper we investigate how the fault- and change-proneness of APIs used by Android apps relates to their success estimated as the average rating provided by the users to those apps. First, in a study conducted on 5,848 (free) apps, we analyzed how the ratings that an app had received correlated with the fault- and change-proneness of the APIs such app relied upon. After that, we surveyed 45 professional Android developers to assess (i) to what extent developers experienced problems when using APIs, and (ii) how much they felt these problems could be the cause for unfavorable user ratings. The results of our studies indicate that apps having high user ratings use APIs that are less fault- and change-prone than the APIs used by low rated apps. Also, most of the interviewed Android developers observed, in their development experience, a direct relationship between problems experienced with the adopted APIs and the users' ratings that their apps received.
•The accuracy of the proposed model was calculated as high as 0.9.•A novel 1-dimensional CNN model was proposed.•The features were automatically selected thanks to the proposed model.•The experiments ...were conducted on the de facto datasets.•We shed light on the insights of Android malware through the conducted experiments.
Smartphones have become an integral part of our daily lives thanks to numerous reasons. While benefitting from what they offer, it is critical to be aware of the existence of malware in the Android ecosystem and be away from them. To this end, an end-to-end and highly effective Android malware detection framework based on CNN, namely, DroidMalwareDetector, was proposed within this study. Unlike most of the related work, DroidMalwareDetector was specifically designed to (i) automate feature extraction and selection, (ii) propose a novel CNN that operates with 1-dimensional data, and (iii) use intents and API calls alongside the widely used permissions to perform comprehensive malware analysis. The proposed framework was trained and evaluated on the constructed dataset, which consisted of 14,386 apps from the de-facto standard datasets. The proposed framework’s efficiency in terms of distinguishing malware from benign apps was revealed thanks to the conducted experiments. According to the experimental result, the accuracy of the proposed framework was calculated as high as 0.9, which was higher than the accuracy values obtained from a wide range of machine learning algorithms. The insights which were gained through the conducted experiments were revealed as another contribution to the research field.
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