Threats and Solutions to Mobile Devices

Mobile devices have now surpassed personal computers (PC) in terms of popularity. Smartphones now come with powerful multi-core processors, loaded with considerable amounts of memory and are capable of carrying out complex operations with relative ease. However, this increase in technology has meant that it has now become susceptible to some of the same problems that P

Threats and Solutions to Mobile Devices

Mobile devices have now surpassed personal computers (PC) in terms of popularity. Smartphones now come with powerful multi-core processors, loaded with considerable amounts of memory and are capable of carrying out complex operations with relative ease. However, this increase in technology has meant that it has now become susceptible to some of the same problems that PC‘s face. In this paper, I will talk about the malware, virus and other security problems facing mobile devices and their possible solutions

Social Data Mining for Crime Intelligence

With the advancement of the Internet and related technologies, many traditional crimes have made the leap to digital environments. The successes of data mining in a wide variety of disciplines have given birth to crime analysis. Traditional crime analysis is mainly focused on understanding crime patterns, however, it is unsuitable for identifying and monitoring emerging crimes. The true nature of crime remains buried in unstructured content that represents the hidden story behind the data. User feedback leaves valuable traces that can be utilised to measure the quality of various aspects of products or services and can also be used to detect, infer, or predict crimes. Like any application of data mining, the data must be of a high quality standard in order to avoid erroneous conclusions. This thesis presents a methodology and practical experiments towards discovering whether (i) user feedback can be harnessed and processed for crime intelligence, (ii) criminal associations, structures, and roles can be inferred among entities involved in a crime, and (iii) methods and standards can be developed for measuring, predicting, and comparing the quality level of social data instances and samples. It contributes to the theory, design and development of a novel framework for crime intelligence and algorithm for the estimation of social data quality by innovatively adapting the methods of monitoring water contaminants. Several experiments were conducted and the results obtained revealed the significance of this study in mining social data for crime intelligence and in developing social data quality filters and decision support systems

On Generating Gadget Chains for Return-Oriented Programming

With the increased popularity of embedded devices, low-level programming languages like C and C++ are currently experiencing a strong renewed interest. However, these languages are, meaning that programming errors may lead to undefined behaviour, which, in turn, may be exploited to compromise a system's integrity. Many programs written in these languages contain such programming errors, most infamous of which are buffer overflows. In order to fight this, there exists a large range of mitigation techniques designed to hinder exploitation, some of which are integral parts of most major operating systems' security concept. Even the most sophisticated mitigations, however, can often be bypassed by modern exploits, which are based on the principle of code reuse: they assemble, or chain, together existing code fragments (known as gadgets) in a way to achieve malicious behaviour. This technique is currently the cornerstone of modern exploits. In this dissertation, we present ROPocop, an approach to mitigate code-reuse attacks. ROPocop is a configurable, heuristic-based detector that monitors program execution and raises an alarm if it detects suspicious behaviour. It monitors the frequency of indirect branches and the length of basic blocks, two characteristics in which code-reuse attacks differ greatly from normal program behaviour. However, like all mitigations, ROPocop has its weaknesses and we show that it and other similar approaches can be bypassed in an automatic way by an aware attacker. To this end, we present PSHAPE, a practical, cross-platform framework to support the construction of code-reuse exploits. It offers two distinguishing features, namely it creates concise semantic summaries for gadgets, which allow exploit developers to assess the utility of a gadget much quicker than by going through the individual assembly instructions. And secondly, PSHAPE automatically composes gadgets to construct a chain of gadgets that can invoke any arbitrary function with user-supplied parameters. Invoking a function is indeed the most common goal of concurrent exploits, as calling a function such as mprotect greatly simplifies later steps of exploitation. For a mitigation to be viable, it must detect actual attacks reliably while at the same time avoiding false positives and ensuring that protected applications remain usable, i.e., do not crash or become very slow. In the tested sample set of applications, ROPocop detects and stops all twelve real attacks with no false positives. When executed with ROPocop, real-world programs exhibit only some slight input lag at startup but otherwise remain responsive. Yet, we further show how PSHAPE can be used to fully automatically create exploits that bypass various mitigations, for example, ROPocop itself. We also show gadgets PSHAPE found easily, that have great relevance in real exploits, and which previously required intense manual searches to find. Lastly, using PSHAPE, we also discovered a new and very useful gadget type that greatly simplifies gadget chaining

Dynamic Laser Fault Injection Aided by Quiescent Photon Emissions in Embedded Microcontrollers: Apparatus, Methodology and Attacks

Internet of Things (IoT) is becoming more integrated in our daily life with the increasing number of embedded electronic devices interacting together. These electronic devices are often controlled by a Micro-Controller Unit (MCU). As an example, it is estimated that today’s well-equipped automobile uses more than 50 MCUs. Some MCUs contain cryptographic co-processors to enhance the security of the exchanged and stored data with a common belief that the data is secured and safe. However many MCUs have been shown to be vulnerable to Fault Injection (FI) attacks. These attacks can reveal shared secrets, firmware, and other confidential information. In addition, this extracted information obtained by attacks can lead to identification of new vulnerabilities which may scale to attacks on many devices. In general, FI on MCUs corrupt data or corrupt instructions. Although it is assumed that only authorized personnel with access to cryptographic secrets will gain access to confidential information in MCUs, attackers in specialized labs nowadays may have access to high-tech equipment which could be used to attack these MCUs. Laser Fault Injection (LFI) is gaining more of a reputation for its ability to inject local faults rather than global ones due to its precision, thus providing a greater risk of breaking security in many devices. Although publications have generally discussed the topic of security of MCUs, attack techniques are diverse and published LFI provides few and superficial details about the used experimental setup and methodology. Furthermore, limited research has examined the combination of both LFI and Photo-Emission Microscopy (PEM), direct modification of instructions using the LFI, control of embedded processor resets using LFI, and countermeasures which simultaneously thwart other aspects including decapsulation and reverse engineering (RE). This thesis contributes to the study of the MCUs’ security by analyzing their susceptibility to LFI attacks and PEM. The proposed research aims to build a LFI bench from scratch allowing maximum control of laser parameters. In addition, a methodology for analysis of the Device Under Attack (DUA) in preparation for LFI is proposed, including frontside/backside decapsulation methods, and visualization of the structure of the DUA. Analysis of attack viability of different targets on the DUA, including One-Time Programmable (OTP) memory, Flash memory and Static Random Access Memory (SRAM) was performed. A realistic attack of a cryptographic algorithm, such as Advanced Encryption Standard (AES) using LFI was conducted. On the other hand, countermeasures to the proposed attack techniques, including decapsulation/RE, LFI and PEM, were discussed. This dissertation provides a summary for the necessary background and experimental setup to study the possibility of LFI and PEM in different DUAs of two different technologies, specifically PIC16F687 and ARM Cortex-M0 LPC1114FN28102. Attacks performed on on-chip peripherals such as Universal Asynchronous Receiver/Transmitter (UART) and debug circuity reveal new vulnerabilities. This research is important for understanding attacks in order to design countermeasures for securing future hardware