iOS Internals Part -2
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Using Cycript for runtime hooking , bypassing locks , making changes to SpringBoard and security analysis
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Data Driven Maintenance | UReason Webinar
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
Advanced control scheme of doubly fed induction generator for wind turbine us...
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Embedded machine learning-based road conditions and driving behavior monitoring
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Design and optimization of ion propulsion drone
Electric propulsion technology is widely used in many kinds of vehicles in recent years, and aircrafts are no exception. Technically, UAVs are electrically propelled but tend to produce a significant amount of noise and vibrations. Ion propulsion technology for drones is a potential solution to this problem. Ion propulsion technology is proven to be feasible in the earth’s atmosphere. The study presented in this article shows the design of EHD thrusters and power supply for ion propulsion drones along with performance optimization of high-voltage power supply for endurance in earth’s atmosphere.
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iOS Internals Part -2
- 2. @whoami ● Anto Joseph ● Works @ Citrix ● Does Security Research on Mobile / iOT and anything Interesting ● Speaker / Trainer @ HITB , HIP , NullCon, g0s, c0c0n, x0rconf etc ● Loves Music ( in my other life , i have been a DJ ) / Food / Bikes etc
- 3. iOS 101 ● Objective C runtime ● Can be written in Objective C / Swift / Native Code ● CodeSigning is important ● Apps are zip file containers containing resources( images / plits) and the binary ● Binary if coming from apple has to be decrypted - use cluth / dump decrypted ● Use class-dump to find out the classes/ methods ● Use cycript to call those methods
- 4. Dynamic Analysis ● URl Schemes - Ios way of doing IPC ● Clipboard - - Ios way of doing IPC ● Network - SSL Trust Killer 2 ● Binary Analysis - Hopper / IDa
- 5. Enter Cycript Cycript allows developers to explore and modify running applications on either iOS or Mac OS X using a hybrid of Objective-C++ and JavaScript syntax through an interactive console that features syntax highlighting and tab completion.
- 6. cy# - commands ● Find all classes ○ cy# ObjectiveC.classes ● Get Instance of a class ○ cy# var blah = new Instance(0x123456) ● Call Methods ○ cy# [classname method_name: arguments] ● Find a class in memory ○ cy# choose(ClassName)
- 7. Demo Time ● Bypassing A Lock ● Making Changes to the SpringBoard
- 8. Thanks