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Khari, M., Vaishali, Kumar, M..  2016.  Analysis of software security testing using metaheuristic search technique. 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom). :2147–2152.

Metaheuristic search technique is one of the advance approach when compared with traditional heuristic search technique. To select one option among different alternatives is not hard to get but really hard is give assurance that being cost effective. This hard problem is solved by the meta-heuristic search technique with the help of fitness function. Fitness function is a crucial metrics or a measure which helps in deciding which solution is optimal to choose from available set of test sets. This paper discusses hill climbing, simulated annealing, tabu search, genetic algorithm and particle swarm optimization techniques in detail explaining with the help of the algorithm. If metaheuristic search techniques combine some of the security testing methods, it would result in better searching technique as well as secure too. This paper primarily focusses on the metaheuristic search techniques.

Schordan, Markus, Oppelstrup, Tomas, Jefferson, David, Barnes, Jr., Peter D., Quinlan, Dan.  2016.  Automatic Generation of Reversible C++ Code and Its Performance in a Scalable Kinetic Monte-Carlo Application. Proceedings of the 2016 Annual ACM Conference on SIGSIM Principles of Advanced Discrete Simulation. :111–122.

The fully automatic generation of code that establishes the reversibility of arbitrary C/C++ code has been a target of research and engineering for more than a decade as reverse computation has become a central notion in large scale parallel discrete event simulation (PDES). The simulation models that are implemented for PDES are of increasing complexity and size and require various language features to support abstraction, encapsulation, and composition when building a simulation model. In this paper we focus on parallel simulation models that are written in C++ and present an approach and an evaluation for a fully automatically generated reversible code for a kinetic Monte-Carlo application implemented in C++. Although a significant runtime overhead is introduced with our technique, the assurance that the reverse code is generated automatically and correctly, is an enormous win that allows simulation model developers to write forward event code using the entire C++ language, and have that code automatically transformed into reversible code to enable parallel execution with the Rensselaer's Optimistic Simulation System (ROSS).

Fredericks, Erik M..  2016.  Automatically Hardening a Self-adaptive System Against Uncertainty. Proceedings of the 11th International Symposium on Software Engineering for Adaptive and Self-Managing Systems. :16–27.

A self-adaptive system (SAS) can reconfigure to adapt to potentially adverse conditions that can manifest in the environment at run time. However, the SAS may not have been explicitly developed with such conditions in mind, thereby requiring additional configuration states or updates to the requirements specification for the SAS to provide assurance that it continually satisfies its requirements and delivers acceptable behavior. By discovering both adverse environmental conditions and the SAS configuration states that can mitigate those conditions at design time, an SAS can be hardened against uncertainty prior to deployment, effectively extending its lifetime. This paper introduces two search-based techniques, Ragnarok and Valkyrie, for hardening an SAS against uncertainty. Ragnarok automatically discovers adverse conditions that negatively impact an SAS by searching for environmental conditions that explicitly cause requirements violations. Valkyrie then searches for SAS configurations that improve requirements satisficement throughout execution in response to discovered adverse environmental conditions. Together, these techniques can be used to improve the design and implementation of an SAS. We apply each technique to an industry-provided remote data mirroring application that can self-reconfigure in response to unknown or adverse conditions, such as network message delays, network link failures, and sensor noise.

Santos, J. C. S., Tarrit, K., Mirakhorli, M..  2017.  A Catalog of Security Architecture Weaknesses. 2017 IEEE International Conference on Software Architecture Workshops (ICSAW). :220–223.

Secure by design is an approach to developing secure software systems from the ground up. In such approach, the alternate security tactics are first thought, among them, the best are selected and enforced by the architecture design, and then used as guiding principles for developers. Thus, design flaws in the architecture of a software system mean that successful attacks could result in enormous consequences. Therefore, secure by design shifts the main focus of software assurance from finding security bugs to identifying architectural flaws in the design. Current research in software security has been neglecting vulnerabilities which are caused by flaws in a software architecture design and/or deteriorations of the implementation of the architectural decisions. In this paper, we present the concept of Common Architectural Weakness Enumeration (CAWE), a catalog which enumerates common types of vulnerabilities rooted in the architecture of a software and provides mitigation techniques to address them. The CAWE catalog organizes the architectural flaws according to known security tactics. We developed an interactive web-based solution which helps designers and developers explore this catalog based on architectural choices made in their project. CAWE catalog contains 224 weaknesses related to security architecture. Through this catalog, we aim to promote the awareness of security architectural flaws and stimulate the security design thinking of developers, software engineers, and architects.

Shevtsov, Stepan.  2016.  Developing a Reusable Control-based Approach to Build Self-adaptive Software Systems with Formal Guarantees. Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering. :1060–1062.

An increasingly important concern of software engineers is handling uncertainty at runtime. Over the last decade researchers have applied architecture-based self-adaptation approaches to address this concern. However, providing guarantees required by current software systems has shown to be challenging with these approaches. To tackle this challenge, we study the application of control theory to realize self-adaptation and develop novel control-based adaptation mechanisms that guarantee desired system properties. Results are validated on systems with strict requirements.

Baum, Tobias, Liskin, Olga, Niklas, Kai, Schneider, Kurt.  2016.  Factors Influencing Code Review Processes in Industry. Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering. :85–96.

Code review is known to be an efficient quality assurance technique. Many software companies today use it, usually with a process similar to the patch review process in open source software development. However, there is still a large fraction of companies performing almost no code reviews at all. And the companies that do code reviews have a lot of variation in the details of their processes. For researchers trying to improve the use of code reviews in industry, it is important to know the reasons for these process variations. We have performed a grounded theory study to clarify process variations and their rationales. The study is based on interviews with software development professionals from 19 companies. These interviews provided insights into the reasons and influencing factors behind the adoption or non-adoption of code reviews as a whole as well as for different process variations. We have condensed these findings into seven hypotheses and a classification of the influencing factors. Our results show the importance of cultural and social issues for review adoption. They trace many process variations to differences in development context and in desired review effects.

Scofield, Daniel, Miles, Craig, Kuhn, Stephen.  2017.  Fast Model Learning for the Detection of Malicious Digital Documents. Proceedings of the 7th Software Security, Protection, and Reverse Engineering / Software Security and Protection Workshop. :3:1–3:8.

Modern cyber attacks are often conducted by distributing digital documents that contain malware. The approach detailed herein, which consists of a classifier that uses features derived from dynamic analysis of a document viewer as it renders the document in question, is capable of classifying the disposition of digital documents with greater than 98% accuracy even when its model is trained on just small amounts of data. To keep the classification model itself small and thereby to provide scalability, we employ an entity resolution strategy that merges syntactically disparate features that are thought to be semantically equivalent but vary due to programmatic randomness. Entity resolution enables construction of a comprehensive model of benign functionality using relatively few training documents, and the model does not improve significantly with additional training data.

Ben Othmane, Lotfi, Jamil, Ameerah-Muhsina, Abdelkhalek, Moataz.  2019.  Identification of the Impacts of Code Changes on the Security of Software. 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC). 2:569–574.
Companies develop their software in versions and iterations. Ensuring the security of each additional version using code review is costly and time consuming. This paper investigates automated tracing of the impacts of code changes on the security of a given software. To this end, we use call graphs to model the software code, and security assurance cases to model the security requirements of the software. Then we relate assurance case elements to code through the entry point methods of the software, creating a map of monitored security functions. This mapping allows to evaluate the security requirements that are affected by code changes. The approach is implemented in a set of tools and evaluated using three open-source ERP/E-commerce software applications. The limited evaluation showed that the approach is effective in identifying the impacts of code changes on the security of the software. The approach promises to considerably reduce the security assessment time of the subsequent releases and iterations of software, keeping the initial security state throughout the software lifetime.
Todorov, Vassil, Taha, Safouan, Boulanger, Frédéric, Hernandez, Armando.  2019.  Improved Invariant Generation for Industrial Software Model Checking of Time Properties. 2019 IEEE 19th International Conference on Software Quality, Reliability and Security (QRS). :334–341.
Modern automotive embedded software is mostly designed using model-based design tools such as Simulink or SCADE, and source code is generated automatically from the models. Formal proof using symbolic model checking has been integrated in these tools and can provide a higher assurance by proving safety-critical properties. Our experience shows that proving properties involving time is rather challenging when they involve long durations and timers. These properties are generally not inductive and even advanced techniques such as PDR/IC3 are unable to handle them on production models in reasonable time. In this paper, we first present our industrial use case and comment on the results obtained with the existing model checkers. Then we present our invariant generator and methodology for selecting invariants according to physical dimensions. They enable the proof of properties with long-running timers. Finally, we discuss their implementation and benchmarks.
Whitmore, J., Tobin, W..  2017.  Improving Attention to Security in Software Design with Analytics and Cognitive Techniques. 2017 IEEE Cybersecurity Development (SecDev). :16–21.

There is widening chasm between the ease of creating software and difficulty of "building security in". This paper reviews the approach, the findings and recent experiments from a seven-year effort to enable consistency across a large, diverse development organization and software portfolio via policies, guidance, automated tools and services. Experience shows that developing secure software is an elusive goal for most. It requires every team to know and apply a wide range of security knowledge in the context of what software is being built, how the software will be used, and the projected threats in the environment where the software will operate. The drive for better outcomes for secure development and increased developer productivity led to experiments to augment developer knowledge and eventually realize the goal of "building the right security in".

Alami, Adam, Dittrich, Yvonne, Wąsowski, Andrzej.  2018.  Influencers of Quality Assurance in an Open Source Community. Proceedings of the 11th International Workshop on Cooperative and Human Aspects of Software Engineering. :61-68.
ROS (Robot Operating System) is an open source community in robotics that is developing standard robotics operating system facilities such as hardware abstraction, low-level device control, communication middleware, and a wide range of software components for robotics functionality. This paper studies the quality assurance practices of the ROS community. We use qualitative methods to understand how ideology, priorities of the community, culture, sustainability, complexity, and adaptability of the community affect the implementation of quality assurance practices. Our analysis suggests that software engineering practices require social and cultural alignment and adaptation to the community particularities to achieve seamless implementation in open source environments. This alignment should be incorporated into the design and implementation of quality assurance practices in open source communities.
Weir, Charles, Becker, Ingolf, Noble, James, Blair, Lynne, Sasse, Angela, Rashid, Awais.  2019.  Interventions for Software Security: Creating a Lightweight Program of Assurance Techniques for Developers. 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP). :41–50.
Though some software development teams are highly effective at delivering security, others either do not care or do not have access to security experts to teach them how. Unfortunately, these latter teams are still responsible for the security of the systems they build: systems that are ever more important to ever more people. We propose that a series of lightweight in-terventions, six hours of facilitated workshops delivered over three months, can improve a team's motivation to consider security and awareness of assurance techniques, changing its security culture even when no security experts are involved. The interventions were developed after an Appreciative Inquiry and Grounded Theory survey of security professionals to find out what approaches work best. They were then validated in fieldwork with a Participatory Action Research study that de-livered the workshops to three development organizations. This approach has the potential to be applied by many development teams, improving the security of software worldwide.
Bugeja, Joseph, Vogel, Bahtijar, Jacobsson, Andreas, Varshney, Rimpu.  2019.  IoTSM: An End-to-End Security Model for IoT Ecosystems. 2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). :267-272.

The Internet of Things (IoT) market is growing rapidly, allowing continuous evolution of new technologies. Alongside this development, most IoT devices are easy to compromise, as security is often not a prioritized characteristic. This paper proposes a novel IoT Security Model (IoTSM) that can be used by organizations to formulate and implement a strategy for developing end-to-end IoT security. IoTSM is grounded by the Software Assurance Maturity Model (SAMM) framework, however it expands it with new security practices and empirical data gathered from IoT practitioners. Moreover, we generalize the model into a conceptual framework. This approach allows the formal analysis for security in general and evaluates an organization's security practices. Overall, our proposed approach can help researchers, practitioners, and IoT organizations, to discourse about IoT security from an end-to-end perspective.

Palacio, David N., McCrystal, Daniel, Moran, Kevin, Bernal-Cárdenas, Carlos, Poshyvanyk, Denys, Shenefiel, Chris.  2019.  Learning to Identify Security-Related Issues Using Convolutional Neural Networks. 2019 IEEE International Conference on Software Maintenance and Evolution (ICSME). :140–144.
Software security is becoming a high priority for both large companies and start-ups alike due to the increasing potential for harm that vulnerabilities and breaches carry with them. However, attaining robust security assurance while delivering features requires a precarious balancing act in the context of agile development practices. One path forward to help aid development teams in securing their software products is through the design and development of security-focused automation. Ergo, we present a novel approach, called SecureReqNet, for automatically identifying whether issues in software issue tracking systems describe security-related content. Our approach consists of a two-phase neural net architecture that operates purely on the natural language descriptions of issues. The first phase of our approach learns high dimensional word embeddings from hundreds of thousands of vulnerability descriptions listed in the CVE database and issue descriptions extracted from open source projects. The second phase then utilizes the semantic ontology represented by these embeddings to train a convolutional neural network capable of predicting whether a given issue is security-related. We evaluated SecureReqNet by applying it to identify security-related issues from a dataset of thousands of issues mined from popular projects on GitLab and GitHub. In addition, we also applied our approach to identify security-related requirements from a commercial software project developed by a major telecommunication company. Our preliminary results are encouraging, with SecureReqNet achieving an accuracy of 96% on open source issues and 71.6% on industrial requirements.
Izurieta, Clemente, Prouty, Mary.  2019.  Leveraging SecDevOps to Tackle the Technical Debt Associated with Cybersecurity Attack Tactics. 2019 IEEE/ACM International Conference on Technical Debt (TechDebt). :33–37.
Context: Managing technical debt (TD) associated with external cybersecurity attacks on an organization can significantly improve decisions made when prioritizing which security weaknesses require attention. Whilst source code vulnerabilities can be found using static analysis techniques, malicious external attacks expose the vulnerabilities of a system at runtime and can sometimes remain hidden for long periods of time. By mapping malicious attack tactics to the consequences of weaknesses (i.e. exploitable source code vulnerabilities) we can begin to understand and prioritize the refactoring of the source code vulnerabilities that cause the greatest amount of technical debt on a system. Goal: To establish an approach that maps common external attack tactics to system weaknesses. The consequences of a weakness associated with a specific attack technique can then be used to determine the technical debt principal of said violation; which can be measured in terms of loss of business rather than source code maintenance. Method: We present a position study that uses Jaccard similarity scoring to examine how 11 malicious attack tactics can relate to Common Weakness Enumerations (CWEs). Results: We conduct a study to simulate attacks, and generate dependency graphs between external attacks and the technical consequences associated with CWEs. Conclusion: The mapping of cyber security attacks to weaknesses allows operational staff (SecDevOps) to focus on deploying appropriate countermeasures and allows developers to focus on refactoring the vulnerabilities with the greatest potential for technical debt.
Kokaly, S..  2017.  Managing Assurance Cases in Model Based Software Systems. 2017 IEEE/ACM 39th International Conference on Software Engineering Companion (ICSE-C). :453–456.

Software has emerged as a significant part of many domains, including financial service platforms, social networks and vehicle control. Standards organizations have responded to this by creating regulations to address issues such as safety and privacy. In this context, compliance of software with standards has emerged as a key issue. For software development organizations, compliance is a complex and costly goal to achieve and is often accomplished by producing so-called assurance cases, which demonstrate that the system indeed satisfies the property imposed by a standard (e.g., safety, privacy, security). As systems and standards undergo evolution for a variety of reasons, maintaining assurance cases multiplies the effort. In this work, we propose to exploit the connection between the field of model management and the problem of compliance management and propose methods that use model management techniques to address compliance scenarios such as assurance case evolution and reuse. For validation, we ground our approaches on the automotive domain and the ISO 26262 standard for functional safety of road vehicles.

Saarela, Marko, Hosseinzadeh, Shohreh, Hyrynsalmi, Sami, Leppänen, Ville.  2017.  Measuring Software Security from the Design of Software. Proceedings of the 18th International Conference on Computer Systems and Technologies. :179–186.

With the increasing use of mobile phones in contemporary society, more and more networked computers are connected to each other. This has brought along security issues. To solve these issues, both research and development communities are trying to build more secure software. However, there is the question that how the secure software is defined and how the security could be measured. In this paper, we study this problem by studying what kinds of security measurement tools (i.e. metrics) are available, and what these tools and metrics reveal about the security of software. As the result of the study, we noticed that security verification activities fall into two main categories, evaluation and assurance. There exist 34 metrics for measuring the security, from which 29 are assurance metrics and 5 are evaluation metrics. Evaluating and studying these metrics, lead us to the conclusion that the general quality of the security metrics are not in a satisfying level that could be suitably used in daily engineering work flows. They have both theoretical and practical issues that require further research, and need to be improved.

das Dôres, Silvia N., Alves, Luciano, Ruiz, Duncan D., Barros, Rodrigo C..  2016.  A Meta-learning Framework for Algorithm Recommendation in Software Fault Prediction. Proceedings of the 31st Annual ACM Symposium on Applied Computing. :1486–1491.

Software fault prediction is a significant part of software quality assurance and it is commonly used to detect faulty software modules based on software measurement data. Several machine learning based approaches have been proposed for generating predictive models from collected data, although none has become standard given the specificities of each software project. Hence, we believe that recommending the best algorithm for each project is much more important and useful than developing a single algorithm for being used in any project. For achieving that goal, we propose in this paper a novel framework for recommending machine learning algorithms that is capable of automatically identifying the most suitable algorithm according to the software project that is being considered. Our solution, namely SFP-MLF, makes use of the meta-learning paradigm in order to learn the best learner for a particular project. Results show that the SFP-MLF framework provides both the best single algorithm recommendation and also the best ranking recommendation for the software fault prediction problem.

Kokaly, Sahar, Salay, Rick, Cassano, Valentin, Maibaum, Tom, Chechik, Marsha.  2016.  A Model Management Approach for Assurance Case Reuse Due to System Evolution. Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems. :196–206.

Evolution in software systems is a necessary activity that occurs due to fixing bugs, adding functionality or improving system quality. Systems often need to be shown to comply with regulatory standards. Along with demonstrating compliance, an artifact, called an assurance case, is often produced to show that the system indeed satisfies the property imposed by the standard (e.g., safety, privacy, security, etc.). Since each of the system, the standard, and the assurance case can be presented as a model, we propose the extension and use of traditional model management operators to aid in the reuse of parts of the assurance case when the system undergoes an evolution. Specifically, we present a model management approach that eventually produces a partial evolved assurance case and guidelines to help the assurance engineer in completing it. We demonstrate how our approach works on an automotive subsystem regulated by the ISO 26262 standard.

Hovsepyan, Aram, Scandariato, Riccardo, Joosen, Wouter.  2016.  Is Newer Always Better?: The Case of Vulnerability Prediction Models Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement. :26:1–26:6.

Finding security vulnerabilities in the source code as early as possible is becoming more and more essential. In this respect, vulnerability prediction models have the potential to help the security assurance activities by identifying code locations that deserve the most attention. In this paper, we investigate whether prediction models behave like milk (i.e., they turn with time) or wine (i.e., the improve with time) when used to predict future vulnerabilities. Our findings indicate that the recall values are largely in favor of predictors based on older versions. However, the better recall comes at the price of much higher file inspection ratio values.

Khan, R. A., Khan, S. U..  2018.  A Preliminary Structure of Software Security Assurance Model. 2018 IEEE/ACM 13th International Conference on Global Software Engineering (ICGSE). :132-135.
Software security is an important aspect that needs to be considered during the entire software development life cycle (SDLC). Integrating software security at each phase of SDLC has become an urgent need. To address software security, various approaches, techniques, methods, practices, and models have been proposed and developed. However, recent research shows that many software development methodologies do not explicitly include methods for incorporating software security during the development of software as it evolves from requirements engineering to its final disposal. The primary objective of this research is to study the state-of-the-art of security in the context of SDLC by following systematic mapping study (SMS). In the second phase, we will identify, through systematic literature review (SLR) and empirical study in the industry, the software security contributions, security challenges and their practices for global software development (GSD) vendors. The ultimate aim is to develop a Software Security Assurance Model (SSAM) to assist GSD vendor organisations in measuring their readiness towards the development of secure software.
Prechelt, Lutz, Schmeisky, Holger, Zieris, Franz.  2016.  Quality Experience: A Grounded Theory of Successful Agile Projects Without Dedicated Testers. Proceedings of the 38th International Conference on Software Engineering. :1017–1027.

Context: While successful conventional software development regularly employs separate testing staff, there are successful agile teams with as well as without separate testers. Question: How does successful agile development work without separate testers? What are advantages and disadvantages? Method: A case study, based on Grounded Theory evaluation of interviews and direct observation of three agile teams; one having separate testers, two without. All teams perform long-term development of parts of e-business web portals. Results: Teams without testers use a quality experience work mode centered around a tight field-use feedback loop, driven by a feeling of responsibility, supported by test automation, resulting in frequent deployments. Conclusion: In the given domain, hand-overs to separate testers appear to hamper the feedback loop more than they contribute to quality, so working without testers is preferred. However, Quality Experience is achievable only with modular architectures and in suitable domains.

Baruah, Sanjoy.  2016.  Schedulability Analysis of Mixed-criticality Systems with Multiple Frequency Specifications. Proceedings of the 13th International Conference on Embedded Software. :24:1–24:10.

In mixed-criticality systems functionalities of different criticalities, that need to have their correctness validated to different levels of assurance, co-exist upon a shared platform. Multiple specifications at differing levels of assurance may be provided for such systems; the specifications that are trusted at very high levels of assurance tend to be more conservative than those at lower levels of assurance. Prior research on the scheduling of such mixed-criticality systems has primarily focused upon the case where multiple estimates of the worst-case execution time (WCET) of pieces of code are provided; in this paper, a model is considered in which multiple estimates are instead provided for the rate at which event-triggered processes are executed. An algorithm is derived for scheduling such systems upon a preemptive uniprocessor; the effectiveness of this algorithm is demonstrated quantitatively via the speedup factor metric.

Ghosh, U., Chatterjee, P., Tosh, D., Shetty, S., Xiong, K., Kamhoua, C..  2017.  An SDN Based Framework for Guaranteeing Security and Performance in Information-Centric Cloud Networks. 2017 IEEE 10th International Conference on Cloud Computing (CLOUD). :749–752.

Cloud data centers are critical infrastructures to deliver cloud services. Although security and performance of cloud data centers have been well studied in the past, their networking aspects are overlooked. Current network infrastructures in cloud data centers limit the ability of cloud provider to offer guaranteed cloud network resources to users. In order to ensure security and performance requirements as defined in the service level agreement (SLA) between cloud user and provider, cloud providers need the ability to provision network resources dynamically and on the fly. The main challenge for cloud provider in utilizing network resource can be addressed by provisioning virtual networks that support information centric services by separating the control plane from the cloud infrastructure. In this paper, we propose an sdn based information centric cloud framework to provision network resources in order to support elastic demands of cloud applications depending on SLA requirements. The framework decouples the control plane and data plane wherein the conceptually centralized control plane controls and manages the fully distributed data plane. It computes the path to ensure security and performance of the network. We report initial experiment on average round-trip delay between consumers and producers.

Koutroumpouchos, Nikos, Ntantogian, Christoforos, Menesidou, Sofia-Anna, Liang, Kaitai, Gouvas, Panagiotis, Xenakis, Christos, Giannetsos, Thanassis.  2019.  Secure Edge Computing with Lightweight Control-Flow Property-based Attestation. 2019 IEEE Conference on Network Softwarization (NetSoft). :84–92.
The Internet of Things (IoT) is rapidly evolving, while introducing several new challenges regarding security, resilience and operational assurance. In the face of an increasing attack landscape, it is necessary to cater for the provision of efficient mechanisms to collectively verify software- and device-integrity in order to detect run-time modifications. Towards this direction, remote attestation has been proposed as a promising defense mechanism. It allows a third party, the verifier, to ensure the integrity of a remote device, the prover. However, this family of solutions do not capture the real-time requirements of industrial IoT applications and suffer from scalability and efficiency issues. In this paper, we present a lightweight dynamic control-flow property-based attestation architecture (CFPA) that can be applied on both resource-constrained edge and cloud devices and services. It is a first step towards a new line of security mechanisms that enables the provision of control-flow attestation of only those specific, critical software components that are comparatively small, simple and limited in function, thus, allowing for a much more efficient verification. Our goal is to enhance run-time software integrity and trustworthiness with a scalable and decentralized solution eliminating the need for federated infrastructure trust. Based on our findings, we posit open issues and challenges, and discuss possible ways to address them, so that security do not hinder the deployment of intelligent edge computing systems.