Sistem Deteksi Nomor Telepon dan Rekening Bank Terindikasi Penipuan Berbasis Aplikasi Android dan Web

Hampir setiap pengguna ponsel pernah menerima panggilan atau pesan masuk dari nomor telepon yang tidak dikenal. Terkadang, panggilan atau pesan masuk demikian adalah penipuan untuk menjebak pengguna ponsel melakukan transfer uang ke rekening bank. Pengguna ponsel rentan menjadi sasaran tindakan kriminal karena sulit mendeteksi nomor telepon dan rekening bank yang dipakai untuk penipuan. Penelitian ini dimaksudkan untuk menghasilkan solusi aplikasi Android agar pengguna dapat berbagi laporan penipuan, menelusuri riwayat laporan nomor telepon dan rekening bank tertentu yang terindikasi dipakai untuk penipuan, serta mendeteksi dan memblokir panggilan masuk yang berisiko dengan tetap menghargai privasi pengguna. Aplikasi Android didukung dengan situs web khusus untuk mengelola informasi yang dibutuhkan. Keseluruhan sistem dikembangkan melalui proses berulang dan bertahap dengan metode Rapid Application Development (RAD) dan beberapa alat pengembangan yaitu: MariaDB, Kotlin, Android Studio, dan Laravel 7. Aplikasi Android dan situs web yang dihasilkan masing-masing telah melewati 37 dan 17 kasus uji dalam pengujian blackbox sehingga telah layak dipakai untuk meningkatkan kenyamanan pengguna dalam menggunakan ponsel karena mampu mendeteksi nomor telepon dan rekening bank yang terindikasi penipuan.Almost every cellphone user has received incoming calls or messages from unknown phone numbers. Sometimes, these are scam calls or messages to trap cellphone users doing money transfers to bank accounts. Mobile phone users are vulnerable to this criminal act because they are hard to detect the phone numbers and bank accounts used for scams. This research aims to produce an Android app solution so that users can share scam reports, browse the report history of specific phone numbers and bank accounts used for scams, and detect and block risky incoming calls while respecting user privacy. The Android app is supported with a dedicated website to manage the required information. The entire system was developed through an iterative and gradual process using the Rapid Application Development (RAD) method and several development tools: MariaDB, Kotlin, Android Studio, and Laravel 7. The Android application and website have passed 37 and 17 test cases in black box testing. Systems have been suitable for increasing user convenience in using a mobile phone because they can detect scam-indicated phone numbers and bank accounts

How Smart is your Android Smartphone?

Smart phones are ubiquitous today. These phones generally have access to sensitive personal information and, consequently, they are a prime target for attackers. A virus or worm that spreads over the network to cell phone users could be particularly damaging. Due to a rising demand for secure mobile phones, manufacturers have increased their emphasis on mobile security. In this project, we address some security issues relevant to the current Android smartphone framework. Specifically, we demonstrate an exploit that targets the Android telephony service. In addition, as a defense against the loss of personal information, we provide a means to encrypt data stored on the external media card. While smartphones remain vulnerable to a variety of security threats, this encryption provides an additional level of security

InternalBlue - Bluetooth Binary Patching and Experimentation Framework

Bluetooth is one of the most established technologies for short range digital wireless data transmission. With the advent of wearables and the Internet of Things (IoT), Bluetooth has again gained importance, which makes security research and protocol optimizations imperative. Surprisingly, there is a lack of openly available tools and experimental platforms to scrutinize Bluetooth. In particular, system aspects and close to hardware protocol layers are mostly uncovered. We reverse engineer multiple Broadcom Bluetooth chipsets that are widespread in off-the-shelf devices. Thus, we offer deep insights into the internal architecture of a popular commercial family of Bluetooth controllers used in smartphones, wearables, and IoT platforms. Reverse engineered functions can then be altered with our InternalBlue Python framework---outperforming evaluation kits, which are limited to documented and vendor-defined functions. The modified Bluetooth stack remains fully functional and high-performance. Hence, it provides a portable low-cost research platform. InternalBlue is a versatile framework and we demonstrate its abilities by implementing tests and demos for known Bluetooth vulnerabilities. Moreover, we discover a novel critical security issue affecting a large selection of Broadcom chipsets that allows executing code within the attacked Bluetooth firmware. We further show how to use our framework to fix bugs in chipsets out of vendor support and how to add new security features to Bluetooth firmware

Typical Phone Use Habits: Intense Use Does Not Predict Negative Well-Being

Not all smartphone owners use their device in the same way. In this work, we uncover broad, latent patterns of mobile phone use behavior. We conducted a study where, via a dedicated logging app, we collected daily mobile phone activity data from a sample of 340 participants for a period of four weeks. Through an unsupervised learning approach and a methodologically rigorous analysis, we reveal five generic phone use profiles which describe at least 10% of the participants each: limited use, business use, power use, and personality- & externally induced problematic use. We provide evidence that intense mobile phone use alone does not predict negative well-being. Instead, our approach automatically revealed two groups with tendencies for lower well-being, which are characterized by nightly phone use sessions.Comment: 10 pages, 6 figures, conference pape