A Comprehensive Investigation of Model Driven Architecture (MDA) for Reverse Engineering

CAD and CAE model update on manufactured shapes is a key process in the industry 4.0, where design, manufacturing and maintenance are integrated elements. Digital Twin models, together with Reverse Engineering (RE) techniques, allow tracking components performances during production and verifying the compliance with design requirements during the component lifetime. The need to have RE processes with a small impact on the production is driving the development of these models towards numerical techniques with fast computing performances. In this context, morphing techniques, largely deployed in the field of CAE models update, represent a valuable alternative to conventional RE techniques, because of their reduced computational time and capability to preserve the initial topology of the model. In the work presented in this paper, Radial Basis Function morphing technique has been used for the update of ITER Winding Pack CAD model on scan data acquired from the manufactured component.

In this chapter, we present methodologies and technologies for automating reverse engineering (RE) through digital imaging and computer vision. We begin this chapter with a definition of RE in terms of generating computer-aided design (CAD) models from existing objects and components. We use the term computer-aided reverse engineering (CARE) to describe this process. With this definition, we present a brief overview of the traditional approach to RE using coordinate measuring machines (CMMs). Then, we begin the main focus of the chapter where we explore digital imaging and computer vision as an alternative to CMMs. This exploration begins with data acquisition, where we present laser-based range scanners as a promising approach. For these scanners, we explain and highlight differences in data resolution and scanning rates and contrast those to CMM performance. Next, we present a processing pipeline for creating CAD models using these scanners. This processing includes tasks such as view registration, surface integration, patch reconstruction, model fitting, noise removal, and other functions. This chapter explains these topics to help the reader understand their importance in designing an RE imaging system and the impact that various parameters have on modeling accuracy.

Model Driven Engineering (MDE) received a lot of attention in the last years, both from academia and industry. However, there is still a debate on which basic concepts form the foundation of MDE. The Model Driven Architecture (MDA) from the OMG does not provided clear answers to this question. This standard instead provides a complex set of interdependent technologies. This paper is the first of a series aiming at defining the foundations of MDE independently from a particular technology. A megamodel is introduced in this paper and incrementally refined in further papers from the series. This paper is devoted to a single concept, the concept of model, and to a single relation, the RepresentationOf relation. The lack of strong foundations for the MDA 4-layers meta-pyramid leads to a common mockery: ``So, MDA is just about Egyptology?!''. This paper is the pilot of the series called ``From Ancient Egypt to Model Driven Engineering''. The various episodes of this series show that Egyptology is actually a good model to study MDE.

Reverse engineering (RE) is one of the major security threats to the semiconductor industry due to the involvement of untrustworthy parties in an increasingly globalized chip manufacturing supply chain. RE efforts have already been successful in extracting device level functionalities from an integrated circuit (IC) with very limited resources. Camouflaging is an obfuscation method that can thwart such RE. Existing work on IC camouflaging primarily involves transformable interconnects and/or covert gates where variation in doping and dummy contacts hide the circuit structure or build cells that look alike but have different functionalities. Emerging solutions, such as polymorphic gates based on a giant spin Hall effect and Si nanowire field effect transistors (FETs), are also promising but add significant area overhead and are successfully decamouflaged by the satisfiability solver (SAT)-based RE techniques. Here, we harness the properties of two-dimensional (2D) transition-metal dichalcogenides (TMDs) including MoS2, MoSe2, MoTe2, WS2, and WSe2 and their optically transparent transition-metal oxides (TMOs) to demonstrate area efficient camouflaging solutions that are resilient to SAT attack and automatic test pattern generation attacks. We show that resistors with resistance values differing by 5 orders of magnitude, diodes with variable turn-on voltages and reverse saturation currents, and FETs with adjustable conduction type, threshold voltages, and switching characteristics can be optically camouflaged to look exactly similar by engineering TMO/TMD heterostructures, allowing hardware obfuscation of both digital and analog circuits. Since this 2D heterostructure devices family is intrinsically camouflaged, NAND/NOR/AND/OR gates in the circuit can be obfuscated with significantly less area overhead, allowing 100% logic obfuscation compared to only 5% for complementary metal oxide semiconductor (CMOS)-based camouflaging. Finally, we demonstrate that the largest benchmarking circuit from ISCAS'85, comprised of more than 4000 logic gates when obfuscated with the CMOS-based technique, is successfully decamouflaged by SAT attack in <40 min; whereas, it renders to be invulnerable even in more than 10 h when camouflaged with 2D heterostructure devices, thereby corroborating our hypothesis of high resilience against RE. Our approach of connecting material properties to innovative devices to secure circuits can be considered as a one of a kind demonstration, highlighting the benefits of cross-layer optimization.

We present Ares, a reverse engineering technique for assisting in the analysis of data recovered for the investigation of mobile and embedded systems. The focus of investigations into insider activity is most often on the data stored on the insider's computers and digital device - call logs, email messaging, calendar entries, text messages, and browser history - rather than on the status of the system's security. Ares is novel in that it uses a data-driven approach that incorporates natural language processing techniques to infer the layout of input data that has been created according to some unknown specification. While some other reverse engineering techniques based on instrumentation of executables offer high accuracy, they are hard to apply to proprietary phone architectures. We evaluated the effectiveness of Ares on call logs and contact lists from ten used Nokia cell phones. We created a rule set by manually reverse engineering a single Nokia phone. Without modification to that grammar, Ares parsed most phones' data with 90% of the accuracy of a commercial forensics tool based on manual reverse engineering, and all phones with at least 50% accuracy even though the endianess for one phone changed.

In the reverse engineering area, while the reconstruction of surfaces from scanned or digitised data has been developed, a geometric model of an existing object is often unavailable. This paper presents a new approach to the reconstruction of a surface. The proposed methodology finds the basic parts of the surface and blends surfaces between them. Each basic geometric part is divided into triangular patches which are compared using normal vectors for face grouping. Each group is categorised into analytical surfaces such as a part of a cylinder, a sphere or a cone, and plane shapes to represent the basic geometric surface. Each basic geometric surface is then implemented to the infinitive surface (unbounded plane, cylinder, cone, or sphere: cylinder, cone, and sphere are full shapes of analytical surfaces). The infinitive surface's intersections are trimmed by boundary representation model reconstruction. The proposed methodology has several advantages such as computational efficiency and automatic functional modelling in reverse engineering. Reverse engineering should be the 3D equipment of the photocopying process.

The extract, transform, and load (ETL) process is at the core of data warehousing architectures. As such, the success of data warehouse (DW) projects is essentially based on the proper modeling of the ETL process. As there is no standard model for the representation and design of this process, several researchers have made efforts to propose modeling methods based on different formalisms, such as unified modeling language (UML), ontology, model-driven architecture (MDA), model-driven development (MDD), and graphical flow, which includes business process model notation (BPMN), colored Petri nets (CPN), Yet Another Workflow Language (YAWL), CommonCube, entity modeling diagram (EMD), and so on. With the emergence of Big Data, despite the multitude of relevant approaches proposed for modeling the ETL process in classical environments, part of the community has been motivated to provide new data warehousing methods that support Big Data specifications. In this paper, we present a summary of relevant works related to the modeling of data warehousing approaches, from classical ETL processes to ELT design approaches. A systematic literature review is conducted and a detailed set of comparison criteria are defined in order to allow the reader to better understand the evolution of these processes. Our study paints a complete picture of ETL modeling approaches, from their advent to the era of Big Data, while comparing their main characteristics. This study allows for the identification of the main challenges and issues related to the design of Big Data warehousing systems, mainly involving the lack of a generic design model for data collection, storage, processing, querying, and analysis.

Feature models have been used since the 90's to describe software product lines as a way of reusing common parts in a family of software systems. In 2010, a systematic literature review was published summarizing the advances and settling the basis of the area of Automated Analysis of Feature Models (AAFM). From then on, different studies have applied the AAFM in different domains.AAFM has been applied in different activities along the Software Product Line (SPL) process such as product configuration and derivation, reverse engineering or SPL testing. As the field evolves, there is a need to evaluate the trends in the area and discover where the AAFM is being applied. Systematic Literature Reviews (SLRs) and Systematic Mapping Study (SMS) are the main techniques used to crawl the knowledge in a scientific area and candidates to discover the aforementioned tendencies. While SLRs are suitable to summarize the state of a research area by providing mostly qualitative information, SMSs focus on providing quantitative information and a categorization of the corpus that enables the identification of trends and research opportunities.We present a SMS to identify the evolution and trends in the application of the AAFM since 2010. Concretely, we have performed a search on different databases of AAFM-related papers. We selected 423 primary sources (papers) that followed the defined inclusion and exclusion criteria. The primary sources were classified according to different variability facets that were found during the reading and key-wording phase. It is important to remark that before 2010, AAFM was not well defined and it was referenced using an amalgam of names and concepts. Therefore, we consider that in 2010 the concept of AAFM was coined and then used in different domains and scenarios. This paper studies how AAFM has been used since its definition.First, we found six different variability facets where the AAFM is being applied that define the tendencies: product configuration and derivation; testing and evolution; reverse engineering; multi-model variability-analysis; variability modelling and variability-intensive systems. We also confirmed that there is a lack of industrial evidence in most of the cases. Finally, we present where and when the papers have been published and who are the authors and institutions that are contributing to the field. We observed that the maturity is proven by the increment in the number of journals published along the years as well as the diversity of conferences and workshops where papers are published.We also observed that there are only a few industrial and real evidences of the application of AAFM techniques in most of the cases. We detect in detail where and when the papers have been published and who are the authors and institutions that are contributing to the field. We saw that the maturity is proven by the increment in the number of journals published along the years as well as the diversity of conferences and workshops where papers are presented. Finally, we devise some research opportunities and applications in the future as well as synergies with other research areas. We also suggest some synergies with other areas such as cloud or mobile computing among others that can motivate further research in the future.The reader can find the full text of this paper at https://doi.org/10.1007/s00607-018-0646-1

Systematic Reviews of the Literature: So What? Why Bother? Who Cares

Today, there are many hackers trying to break software using reverse engineering tech- niques. To better protect software, we need to understand reverse engineering methods. This project presents a tool that automatically analyzes executable code in a manner simi- lar to the way an attack might analyze code. Using reverse engineering techniques, executables can be disassembled to yield an as- sembly code representation of the program. Assembly code is much more human reada- ble than binary code. With assembly code, an attacker can attempt to modify the program to do something other than what was intended by the developer. The tool that we have developed allows the user to specify any two points in the assembly code, and then attempts to find a valid execution path between the two speci- fied points. That is, the goal of this project is to develop a tool that will automatically find a path between two given points in the assembly code, say, point A and point B, and then modify the executable so that if point A is reached, then point B will be reached later.

Context: UML has been the de facto standard notation for modeling object-oriented software systems since its appearance in 1997. UML diagrams are important for maintainers of a system, especially when the software was developed by a different team. These diagrams of the system are not always available, however, and are commonly recovered using Reverse Engineering (RE) techniques. When obtained through RE, UML diagrams have a high level of detail as compared to those developed in the forward design activity. Method: In this paper we report on a comparison of the attitude and performance of maintainers when using these two kinds of diagrams during the maintenance of source code. Our findings were obtained by carrying out a controlled experiment with 40 students of a Master's degree in Computer Science. Results: The results show a preference for forward design diagrams but do not display significant differences in task performance. The post-experiment survey results have led us to conclude that the subjects did not consider RE diagrams helpful; they found them difficult to understand, particularly the sequence diagrams. In the case of forward design diagrams, subjects considered sequence diagrams as useful, but they did not really employ them. Conclusions: Based on our findings, as regards performance of maintainers, there are no objective results which favor the use of one of these types of diagram in particular, i.e., UML diagrams which come from forwards design, on the one hand, and diagrams obtained from RE, on the other. Subjective opinions do, however, lead us to recommend the use of diagrams created during design. Nevertheless, we realize that the results should be considered as preliminary ones; further replications of this experiment are planned, using students and professionals, the aim being to obtain more conclusive results.

Traditionally, power integrity engineer uses simulated transient current profile, icc(t) from the Circuit Designer as input to power delivery network, PDN to simulate worst case transient power noise. However, it is extremely difficult to simulate the maximum current profile from large circuit or logic block. It increases the difficulties when the circuit/ logic run at random application. The paper discusses the reverse engineering method to regenerate high speed stimulus current from the given PDN and measured voltage waveform. The paper firstly verified that the reverse engineering method proven to be accurate in HSPICE simulation. Then measurement technique is applied to an Intelreg Core 2 Duo Processor running stress test under various random applications. The paper also discusses the precision and reproducibility of high speed current profile, icc(t) by using this reverse engineering technique. The finding enables the transient power simulation of a PDN can be done without depending on the simulated CKT/ Logic block icc(t) data. The method also improves the correlation work to be done between the pre-silicon simulated icc(t) with the measurement data from the lab.

The CAN (Controller Area Network) bus connects different Electronic Control Units (ECU) inside a vehicle. Valuable information about the state of the vehicle is present on this bus and is useful to track driver behaviour, the health of the vehicle, etc. However, the configuration of this bus is not publicly disclosed by the car manufacturers. Therefore, reverse engineering techniques need to be applied. Nevertheless, performing these techniques manually is cumbersome and time consuming. In this paper, we propose an automation of the analysis steps of reverse engineering in order to improve and facilitate the process. Two approaches of automation are discussed, namely an arithmetic approach and machine learning using classification. In conclusion, we show that reverse engineering of CAN bus traffic is at least partially possible by applying machine learning techniques and the performance of the classifiers increases when adding additional features to the analysis.

Measuring method for abrasive volume of biomimetic embossed surfaces using reverse engineering

Model driven architecture (MDA), which takes platform independent modeling and platform specific transforming as its core technologies, is a software development method and standards system using modeling newly issued by OMG. It analyzes the basic theorem of ROSE, and point out deficiency the model transformation from PIM to PSM. This paper presents a vision of mapping method from PIM to PSM based on XMI/XML platform, using UML. UML profile and MOF makes up PIM and designs theorem of transformation through XMI.