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Gafurov, Davrondzhon, Hurum, Arne Erik.  2020.  Efficiency Metrics and Test Case Design for Test Automation. 2020 IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C). :15—23.
In this paper, we present our test automation work applied on national e-health portal for residents in Norway which has over million monthly visits. The focus of the work is threefold: delegating automation tasks and increasing reusability of test artifacts; metrics for estimating efficiency when creating test artifacts and designing robust automated test cases. Delegating (part of) test automation tasks from technical specialist (e.g. programmer - expensive resource) to non-technical specialist (e.g. domain expert, functional tester) is carried out by transforming low level test artifacts into high level test artifacts. Such transformations not only reduce dependency on specialists with coding skills but also enables involving more stakeholders with domain knowledge into test automation. Furthermore, we propose simple metrics which are useful for estimating efficiency during such transformations. Examples of the new metrics are implementation creation efficiency and test creation efficiency. We describe how we design automated test cases in order to reduce the number of false positives and minimize code duplication in the presence of test data challenge (i.e. using same test data both for manual and automated testing). We have been using our test automation solution for over three years. We successfully applied test automation on 2 out of 6 Scrum teams in Helsenorge. In total there are over 120 automated test cases with over 600 iterations (as of today).
Wang, Wenhui, Chen, Liandong, Han, Longxi, Zhou, Zhihong, Xia, Zhengmin, Chen, Xiuzhen.  2020.  Vulnerability Assessment for ICS system Based on Zero-day Attack Graph. 2020 International Conference on Intelligent Computing, Automation and Systems (ICICAS). :1—5.
The numerous attacks on ICS systems have made severe threats to critical infrastructure. Extensive studies have focussed on the risk assessment of discovering vulnerabilities. However, to identify Zero-day vulnerabilities is challenging because they are unknown to defenders. Here we sought to measure ICS system zero-day risk by building an enhanced attack graph for expected attack path exploiting zero-day vulnerability. In this study, we define the security metrics of Zero-day vulnerability for an ICS. Then we created a Zero-day attack graph to guide how to harden the system by measuring attack paths that exploiting zero-day vulnerabilities. Our studies identify the vulnerability assessment method on ICS systems considering Zero-day Vulnerability by zero-day attack graph. Together, our work is essential to ICS systems security. By assessing unknown vulnerability risk to close the imbalance between attackers and defenders.
Angermeir, Florian, Voggenreiter, Markus, Moyón, Fabiola, Mendez, Daniel.  2021.  Enterprise-Driven Open Source Software: A Case Study on Security Automation. 2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP). :278—287.
Agile and DevOps are widely adopted by the industry. Hence, integrating security activities with industrial practices, such as continuous integration (CI) pipelines, is necessary to detect security flaws and adhere to regulators’ demands early. In this paper, we analyze automated security activities in CI pipelines of enterprise-driven open source software (OSS). This shall allow us, in the long-run, to better understand the extent to which security activities are (or should be) part of automated pipelines. In particular, we mine publicly available OSS repositories and survey a sample of project maintainers to better understand the role that security activities and their related tools play in their CI pipelines. To increase transparency and allow other researchers to replicate our study (and to take different perspectives), we further disclose our research artefacts.Our results indicate that security activities in enterprise-driven OSS projects are scarce and protection coverage is rather low. Only 6.83% of the analyzed 8,243 projects apply security automation in their CI pipelines, even though maintainers consider security to be rather important. This alerts industry to keep the focus on vulnerabilities of 3rd Party software and it opens space for other improvements of practice which we outline in this manuscript.
Silitonga, Arthur, Becker, Juergen.  2020.  Security-driven Cross-Layer Model Description of a HW/SW Framework for AP MPSoC-based Computing Device. 2020 IEEE International Systems Conference (SysCon). :1—8.

Implementation of Internet-of-Things (IoT) can take place in many applications, for instance, automobiles, and industrial automation. We generally view the role of an Electronic Control Unit (ECU) or industrial network node that is occupied and interconnected in many different configurations in a vehicle or a factory. This condition may raise the occurrence of problems related to security issues, such as unauthorized access to data or components in ECUs or industrial network nodes. In this paper, we propose a hardware (HW)/software (SW) framework having integrated security extensions complemented with various security-related features that later can be implemented directly from the framework to All Programmable Multiprocessor System-on-Chip (AP MPSoC)-based ECUs. The framework is a software-defined one that can be configured or reconfigured in a higher level of abstraction language, including High-Level Synthesis (HLS), and the output of the framework is hardware configuration in multiprocessor or reconfigurable components in the FPGA. The system comprises high-level requirements, covert and side-channel estimation, cryptography, optimization, artificial intelligence, and partial reconfiguration. With this framework, we may reduce the design & development time, and provide significant flexibility to configure/reconfigure our framework and its target platform equipped with security extensions.

Baybulatov, A. A., Promyslov, V. G..  2020.  On a Deterministic Approach to Solving Industrial Control System Problems. 2020 International Russian Automation Conference (RusAutoCon). :115—120.

Since remote ages, queues and delays have been a rather exasperating reality of human daily life. Today, they pursue us everywhere: in technical, social, socio-technical, and even control systems, dramatically deteriorating their performance. In this variety, it is the computer systems that are sure to cause the growing anxiety in our digital era. Although for our everyday Internet surfing, experiencing long-lasting and annoying delays is an unpleasant but not dangerous situation, for industrial control systems, especially those dealing with critical infrastructures, such behavior is unacceptable. The article presents a deterministic approach to solving some digital control system problems associated with delays and backlogs. Being based on Network calculus, in contrast to statistical methods of Queuing theory, it provides worst-case results, which are eminently desirable for critical infrastructures. The article covers the basics of a theory of deterministic queuing systems Network calculus, its evolution regarding the relationship between backlog bound and delay, and a technique for handling empirical data. The problems being solved by the deterministic approach: standard calculation of network performance measures, estimation of database maximum updating time, and cybersecurity assessment including such issues as the CIA triad representation, operational technology influence, and availability understanding focusing on its correlation with a delay are thoroughly discussed as well.

Dai, Q., Shi, L..  2020.  A Game-Theoretic Analysis of Cyber Attack-Mitigation in Centralized Feeder Automation System. 2020 IEEE Power Energy Society General Meeting (PESGM). :1–5.
The intelligent electronic devices widely deployed across the distribution network are inevitably making the feeder automation (FA) system more vulnerable to cyber-attacks, which would lead to disastrous socio-economic impacts. This paper proposes a three-stage game-theoretic framework that the defender allocates limited security resources to minimize the economic impacts on FA system while the attacker deploys limited attack resources to maximize the corresponding impacts. Meanwhile, the probability of successful attack is calculated based on the Bayesian attack graph, and a fault-tolerant location technique for centralized FA system is elaborately considered during analysis. The proposed game-theoretic framework is converted into a two-level zero-sum game model and solved by the particle swarm optimization (PSO) combined with a generalized reduced gradient algorithm. Finally, the proposed model is validated on distribution network for RBTS bus 2.
Bresch, C., Lysecky, R., Hély, D..  2020.  BackFlow: Backward Edge Control Flow Enforcement for Low End ARM Microcontrollers. 2020 Design, Automation Test in Europe Conference Exhibition (DATE). :1606–1609.
This paper presents BackFlow, a compiler-based toolchain that enforces indirect backward edge control flow integrity for low-end ARM Cortex-M microprocessors. BackFlow is implemented within the Clang/LLVM compiler and supports the ARM instruction set and its subset Thumb. The control flow integrity generated by the compiler relies on a bitmap, where each set bit indicates a valid pointer destination. The efficiency of the framework is benchmarked using an STM32 NUCLEO F446RE microcontroller. The obtained results show that the control flow integrity solution incurs an execution time overhead ranging from 1.5 to 4.5%.
Carrozzo, G., Siddiqui, M. S., Betzler, A., Bonnet, J., Perez, G. M., Ramos, A., Subramanya, T..  2020.  AI-driven Zero-touch Operations, Security and Trust in Multi-operator 5G Networks: a Conceptual Architecture. 2020 European Conference on Networks and Communications (EuCNC). :254—258.
The 5G network solutions currently standardised and deployed do not yet enable the full potential of pervasive networking and computing envisioned in 5G initial visions: network services and slices with different QoS profiles do not span multiple operators; security, trust and automation is limited. The evolution of 5G towards a truly production-level stage needs to heavily rely on automated end-to-end network operations, use of distributed Artificial Intelligence (AI) for cognitive network orchestration and management and minimal manual interventions (zero-touch automation). All these elements are key to implement highly pervasive network infrastructures. Moreover, Distributed Ledger Technologies (DLT) can be adopted to implement distributed security and trust through Smart Contracts among multiple non-trusted parties. In this paper, we propose an initial concept of a zero-touch security and trust architecture for ubiquitous computing and connectivity in 5G networks. Our architecture aims at cross-domain security & trust orchestration mechanisms by coupling DLTs with AI-driven operations and service lifecycle automation in multi-tenant and multi-stakeholder environments. Three representative use cases are identified through which we will validate the work which will be validated in the test facilities at 5GBarcelona and 5TONIC/Madrid.
Wang Xiao, Mi Hong, Wang Wei.  2010.  Inner edge detection of PET bottle opening based on the Balloon Snake. 2010 2nd International Conference on Advanced Computer Control. 4:56—59.

Edge detection of bottle opening is a primary section to the machine vision based bottle opening detection system. This paper, taking advantage of the Balloon Snake, on the PET (Polyethylene Terephthalate) images sampled at rotating bottle-blowing machine producing pipelines, extracts the opening. It first uses the grayscale weighting average method to calculate the centroid as the initial position of Snake and then based on the energy minimal theory, it extracts the opening. Experiments show that compared with the conventional edge detection and center location methods, Balloon Snake is robust and can easily step over the weak noise points. Edge extracted thorough Balloon Snake is more integral and continuous which provides a guarantee to correctly judge the opening.

Wang, Y., Wen, M., Liu, Y., Wang, Y., Li, Z., Wang, C., Yu, H., Cheung, S.-C., Xu, C., Zhu, Z..  2020.  Watchman: Monitoring Dependency Conflicts for Python Library Ecosystem. 2020 IEEE/ACM 42nd International Conference on Software Engineering (ICSE). :125–135.
The PyPI ecosystem has indexed millions of Python libraries to allow developers to automatically download and install dependencies of their projects based on the specified version constraints. Despite the convenience brought by automation, version constraints in Python projects can easily conflict, resulting in build failures. We refer to such conflicts as Dependency Conflict (DC) issues. Although DC issues are common in Python projects, developers lack tool support to gain a comprehensive knowledge for diagnosing the root causes of these issues. In this paper, we conducted an empirical study on 235 real-world DC issues. We studied the manifestation patterns and fixing strategies of these issues and found several key factors that can lead to DC issues and their regressions. Based on our findings, we designed and implemented Watchman, a technique to continuously monitor dependency conflicts for the PyPI ecosystem. In our evaluation, Watchman analyzed PyPI snapshots between 11 Jul 2019 and 16 Aug 2019, and found 117 potential DC issues. We reported these issues to the developers of the corresponding projects. So far, 63 issues have been confirmed, 38 of which have been quickly fixed by applying our suggested patches.
Lyons, J. B., Nam, C. S., Jessup, S. A., Vo, T. Q., Wynne, K. T..  2020.  The Role of Individual Differences as Predictors of Trust in Autonomous Security Robots. 2020 IEEE International Conference on Human-Machine Systems (ICHMS). :1—5.

This research used an Autonomous Security Robot (ASR) scenario to examine public reactions to a robot that possesses the authority and capability to inflict harm on a human. Individual differences in terms of personality and Perfect Automation Schema (PAS) were examined as predictors of trust in the ASR. Participants (N=316) from Amazon Mechanical Turk (MTurk) rated their trust of the ASR and desire to use ASRs in public and military contexts following a 2-minute video depicting the robot interacting with three research confederates. The video showed the robot using force against one of the three confederates with a non-lethal device. Results demonstrated that individual differences factors were related to trust and desired use of the ASR. Agreeableness and both facets of the PAS (high expectations and all-or-none beliefs) demonstrated unique associations with trust using multiple regression techniques. Agreeableness, intellect, and high expectations were uniquely related to desired use for both public and military domains. This study showed that individual differences influence trust and one's desired use of ASRs, demonstrating that societal reactions to ASRs may be subject to variation among individuals.

Alarcon, G. M., Gibson, A. M., Jessup, S. A..  2020.  Trust Repair in Performance, Process, and Purpose Factors of Human-Robot Trust. 2020 IEEE International Conference on Human-Machine Systems (ICHMS). :1—6.

The current study explored the influence of trust and distrust behaviors on performance, process, and purpose (trustworthiness) perceptions over time when participants were paired with a robot partner. We examined the changes in trustworthiness perceptions after trust violations and trust repair after those violations. Results indicated performance, process, and purpose perceptions were all affected by trust violations, but perceptions of process and purpose decreased more than performance following a distrust behavior. Similarly, trust repair was achieved in performance perceptions, but trust repair in perceived process and purpose was absent. When a trust violation occurred, process and purpose perceptions deteriorated and failed to recover from the violation. In addition, the trust violation resulted in untrustworthy perceptions of the robot. In contrast, trust violations decreased partner performance perceptions, and subsequent trust behaviors resulted in a trust repair. These findings suggest that people are more sensitive to distrust behaviors in their perceptions of process and purpose than they are in performance perceptions.

Razin, Y. S., Feigh, K. M..  2020.  Hitting the Road: Exploring Human-Robot Trust for Self-Driving Vehicles. 2020 IEEE International Conference on Human-Machine Systems (ICHMS). :1—6.

With self-driving cars making their way on to our roads, we ask not what it would take for them to gain acceptance among consumers, but what impact they may have on other drivers. How they will be perceived and whether they will be trusted will likely have a major effect on traffic flow and vehicular safety. This work first undertakes an exploratory factor analysis to validate a trust scale for human-robot interaction and shows how previously validated metrics and general trust theory support a more complete model of trust that has increased applicability in the driving domain. We experimentally test this expanded model in the context of human-automation interaction during simulated driving, revealing how using these dimensions uncovers significant biases within human-robot trust that may have particularly deleterious effects when it comes to sharing our future roads with automated vehicles.

Chernov, D., Sychugov, A..  2020.  Determining the Hazard Quotient of Destructive Actions of Automated Process Control Systems Information Security Violator. 2020 International Russian Automation Conference (RusAutoCon). :566—570.
The purpose of the work is a formalized description of the method determining numerical expression of the danger from actions potentially implemented by an information security violator. The implementation of such actions may lead to a disruption of the ordered functioning of multilevel distributed automated process control systems, which indicates the importance of developing new adequate solutions for predicting attacks consequences. The analysis of the largest destructive effects on information security systems of critical objects is carried out. The most common methods of obtaining the value of the hazard quotient of information security violators' destructive actions are considered. Based on the known methods for determining the possible damage from attacks implemented by a potential information security violator, a new, previously undetected in open sources method for determining the hazard quotient of destructive actions of an information security violator has been proposed. In order to carry out experimental calculations by the proposed method, the authors developed the required software. The calculations results are presented and indicate the possibility of using the proposed method for modeling threats and information security violators when designing an information security system for automated process control systems.
Jin, H., Wang, T., Zhang, M., Li, M., Wang, Y., Snoussi, H..  2020.  Neural Style Transfer for Picture with Gradient Gram Matrix Description. 2020 39th Chinese Control Conference (CCC). :7026–7030.
Despite the high performance of neural style transfer on stylized pictures, we found that Gatys et al [1] algorithm cannot perfectly reconstruct texture style. Output stylized picture could emerge unsatisfied unexpected textures such like muddiness in local area and insufficient grain expression. Our method bases on original algorithm, adding the Gradient Gram description on style loss, aiming to strengthen texture expression and eliminate muddiness. To some extent our method lengthens the runtime, however, its output stylized pictures get higher performance on texture details, especially in the elimination of muddiness.
Lee, J., Abe, G., Sato, K., Itoh, M..  2020.  Impacts of System Transparency and System Failure on Driver Trust During Partially Automated Driving. 2020 IEEE International Conference on Human-Machine Systems (ICHMS). :1–3.
The objective of this study is to explore changes of trust by a situation where drivers need to intervene. Trust in automation is a key determinant for appropriate interaction between drivers and the system. System transparency and types of system failure influence shaping trust in a supervisory control. Subjective ratings of trust were collected to examine the impact of two factors: system transparency (Detailed vs. Less) and system failure (by Limits vs. Malfunction) in a driving simulator study in which drivers experienced a partially automated vehicle. We examined trust ratings at three points: before and after driver intervention in the automated vehicle, and after subsequent experience of flawless automated driving. Our result found that system transparency did not have significant impacts on trust change from before to after the intervention. System-malfunction led trust reduction compared to those of before the intervention, whilst system-limits did not influence trust. The subsequent experience recovered decreased trust, in addition, when the system-limit occurred to drivers who have detailed information about the system, trust prompted in spite of the intervention. The present finding has implications for automation design to achieve the appropriate level of trust.
Shuncheng, L., Jiajia, X., Jin, C., Jian, C., Lin, D., Lu, W..  2020.  Research on the Calibration Influence Factors of UHF Partial Discharge Detector. 2020 5th International Conference on Smart Grid and Electrical Automation (ICSGEA). :34—41.

Ultra high frequency (UHF) partial discharge detection technology has been widely used in on-line monitoring of electrical equipment, for the influence factors of UHF signal's transfer function is complicated, the calibration of UHF method is still not realized until now. In order to study the calibration influence factors of UHF partial discharge (PD) detector, the discharge mechanism of typical PD defects is analyzed, and use a PD UHF signal simulator with multiple adjustable parameters to simulate types of PD UHF signals of electrical equipment, then performed the relative experimental research in propagation characteristics and Sensor characteristics of UHF signals. It is concluded that the calibration reliability has big differences between UHF signal energy and discharge capacity of different discharge source. The calibration curve of corona discharge and suspended discharge which can representation the severity of equipment insulation defect more accurate, and the calibration curve of internal air gap discharge and dielectric surface discharge is poorer. The distance of UHF signal energy decays to stable period become smaller with increase of frequency, and the decay of UHF signal energy is irrelevant to its frequencies when the measuring angle is changing. The frequency range of measuring UHF signal depends on effective frequency range of measurement sensor, moreover, the gain and standing-wave ratio of sensor and the energy of the received signal manifested same change trend. Therefore, in order to calibration the UHF signal, it is necessary to comprehensive consideration the specific discharge type and measuring condition. The results provide the favorable reference for a further study to build the calibration system of UHF measuring method, and to promote the effective application of UHF method in sensor characteristic fault diagnosis and insulation evaluation of electrical equipment.

Nam, C., Li, H., Li, S., Lewis, M., Sycara, K..  2018.  Trust of Humans in Supervisory Control of Swarm Robots with Varied Levels of Autonomy. 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC). :825—830.

In this paper, we study trust-related human factors in supervisory control of swarm robots with varied levels of autonomy (LOA) in a target foraging task. We compare three LOAs: manual, mixed-initiative (MI), and fully autonomous LOA. In the manual LOA, the human operator chooses headings for a flocking swarm, issuing new headings as needed. In the fully autonomous LOA, the swarm is redirected automatically by changing headings using a search algorithm. In the mixed-initiative LOA, if performance declines, control is switched from human to swarm or swarm to human. The result of this work extends the current knowledge on human factors in swarm supervisory control. Specifically, the finding that the relationship between trust and performance improved for passively monitoring operators (i.e., improved situation awareness in higher LOAs) is particularly novel in its contradiction of earlier work. We also discover that operators switch the degree of autonomy when their trust in the swarm system is low. Last, our analysis shows that operator's preference for a lower LOA is confirmed for a new domain of swarm control.

Xie, Y., Bodala, I. P., Ong, D. C., Hsu, D., Soh, H..  2019.  Robot Capability and Intention in Trust-Based Decisions Across Tasks. 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI). :39—47.

In this paper, we present results from a human-subject study designed to explore two facets of human mental models of robots - inferred capability and intention - and their relationship to overall trust and eventual decisions. In particular, we examine delegation situations characterized by uncertainty, and explore how inferred capability and intention are applied across different tasks. We develop an online survey where human participants decide whether to delegate control to a simulated UAV agent. Our study shows that human estimations of robot capability and intent correlate strongly with overall self-reported trust. However, overall trust is not independently sufficient to determine whether a human will decide to trust (delegate) a given task to a robot. Instead, our study reveals that estimations of robot intention, capability, and overall trust are integrated when deciding to delegate. From a broader perspective, these results suggest that calibrating overall trust alone is insufficient; to make correct decisions, humans need (and use) multi-faceted mental models when collaborating with robots across multiple contexts.

Muller, T., Walz, A., Kiefer, M., Doran, H. Dermot, Sikora, A..  2018.  Challenges and prospects of communication security in real-time ethernet automation systems. 2018 14th IEEE International Workshop on Factory Communication Systems (WFCS). :1–9.
Real-Time Ethernet has become the major communication technology for modern automation and industrial control systems. On the one hand, this trend increases the need for an automation-friendly security solution, as such networks can no longer be considered sufficiently isolated. On the other hand, it shows that, despite diverging requirements, the domain of Operational Technology (OT) can derive advantage from high-volume technology of the Information Technology (IT) domain. Based on these two sides of the same coin, we study the challenges and prospects of approaches to communication security in real-time Ethernet automation systems. In order to capitalize the expertise aggregated in decades of research and development, we put a special focus on the reuse of well-established security technology from the IT domain. We argue that enhancing such technology to become automation-friendly is likely to result in more robust and secure designs than greenfield designs. Because of its widespread deployment and the (to this date) nonexistence of a consistent security architecture, we use PROFINET as a showcase of our considerations. Security requirements for this technology are defined and different well-known solutions are examined according their suitability for PROFINET. Based on these findings, we elaborate the necessary adaptions for the deployment on PROFINET.
Khalid, F., Hanif, M. A., Rehman, S., Ahmed, R., Shafique, M..  2019.  TrISec: Training Data-Unaware Imperceptible Security Attacks on Deep Neural Networks. 2019 IEEE 25th International Symposium on On-Line Testing and Robust System Design (IOLTS). :188—193.

Most of the data manipulation attacks on deep neural networks (DNNs) during the training stage introduce a perceptible noise that can be catered by preprocessing during inference, or can be identified during the validation phase. There-fore, data poisoning attacks during inference (e.g., adversarial attacks) are becoming more popular. However, many of them do not consider the imperceptibility factor in their optimization algorithms, and can be detected by correlation and structural similarity analysis, or noticeable (e.g., by humans) in multi-level security system. Moreover, majority of the inference attack rely on some knowledge about the training dataset. In this paper, we propose a novel methodology which automatically generates imperceptible attack images by using the back-propagation algorithm on pre-trained DNNs, without requiring any information about the training dataset (i.e., completely training data-unaware). We present a case study on traffic sign detection using the VGGNet trained on the German Traffic Sign Recognition Benchmarks dataset in an autonomous driving use case. Our results demonstrate that the generated attack images successfully perform misclassification while remaining imperceptible in both “subjective” and “objective” quality tests.

Aman, W., Khan, F..  2019.  Ontology-based Dynamic and Context-aware Security Assessment Automation for Critical Applications. 2019 IEEE 8th Global Conference on Consumer Electronics (GCCE). :644–647.

Several assessment techniques and methodologies exist to analyze the security of an application dynamically. However, they either are focused on a particular product or are mainly concerned about the assessment process rather than the product's security confidence. Most crucially, they tend to assess the security of a target application as a standalone artifact without assessing its host infrastructure. Such attempts can undervalue the overall security posture since the infrastructure becomes crucial when it hosts a critical application. We present an ontology-based security model that aims to provide the necessary knowledge, including network settings, application configurations, testing techniques and tools, and security metrics to evaluate the security aptitude of a critical application in the context of its hosting infrastructure. The objective is to integrate the current good practices and standards in security testing and virtualization to furnish an on-demand and test-ready virtual target infrastructure to execute the critical application and to initiate a context-aware and quantifiable security assessment process in an automated manner. Furthermore, we present a security assessment architecture to reflect on how the ontology can be integrated into a standard process.

Hamad, R. M. H., Fayoumi, M. Al.  2019.  Scalable Quality and Testing Lab (SQTL): Mission-Critical Applications Testing. 2019 International Conference on Computer and Information Sciences (ICCIS). :1–7.

Currently, the complexity of software quality and testing is increasing exponentially with a huge number of challenges knocking doors, especially when testing a mission-critical application in banking and other critical domains, or the new technology trends with decentralized and nonintegrated testing tools. From practical experience, software testing has become costly and more effort-intensive with unlimited scope. This thesis promotes the Scalable Quality and Testing Lab (SQTL), it's a centralized quality and testing platform, which integrates a powerful manual, automation and business intelligence tools. SQTL helps quality engineers (QE) effectively organize, manage and control all testing activities in one centralized lab, starting from creating test cases, then executing different testing types such as web, security and others. And finally, ending with analyzing and displaying all testing activities result in an interactive dashboard, which allows QE to forecast new bugs especially those related to security. The centralized SQTL is to empower QE during the testing cycle, help them to achieve a greater level of software quality in minimum time, effort and cost, and decrease defect density metric.

Kumar, Sushil, Mann, Kulwinder Singh.  2019.  Prevention of DoS Attacks by Detection of Multiple Malicious Nodes in VANETs. 2019 International Conference on Automation, Computational and Technology Management (ICACTM). :89—94.

Vehicular Adhoc Network (VANET), a specialized form of MANET in which safety is the major concern as critical information related to driver's safety and assistance need to be disseminated between the vehicle nodes. The security of the nodes can be increased, if the network availability is increased. The availability of the network is decreased, if there is Denial of Service Attacks (DoS) in the network. In this paper, a packet detection algorithm for the prevention of DoS attacks is proposed. This algorithm will be able to detect the multiple malicious nodes in the network which are sending irrelevant packets to jam the network and that will eventually stop the network to send the safety messages. The proposed algorithm was simulated in NS-2 and the quantitative values of packet delivery ratio, packet loss ratio, network throughput proves that the proposed algorithm enhance the security of the network by detecting the DoS attack well in time.

Mintu, Singh, Gursharan, Malhi, Simarjit Singh, Mahajan, Makul, Batra, Salil, Bath, Ranbir Singh.  2019.  Anatomization of Detection and Performance Measures Techniques for Flooding Attacks using Routing Protocols in MANETs. 2019 International Conference on Automation, Computational and Technology Management (ICACTM). :160—167.
Mobile ad-hoc network (MANETS) is generally appropriate in different territories like military tactical network, educational, home and entertainment and emergency operations etc. The MANETSs are simply the disintegration and designing kind of system in this portable hubs coming up and out the system whenever. Because of decentralized creation of the network, security, routing and Standard of service are the three noteworthy issues. MANETSs are helpless against security attack in light of the decentralized validation. The mobile hubs can enter or out the system and at some point malicious hubs enter the system, which are capable to trigger different dynamic and inactive attack. The flooding attack is the dynamic sort of attack in which malicious hubs transfers flooding packets on the medium. Because of this, medium gets over-burden and packets drop may happen inside the system. This decreases the throughput and increased packet loss. In this paper we illustrated different techniques and proposed various methods responsible for flooding attack. Our commitment in this paper is that we have investigated various flooding attacks in MANETs, their detection techniques with performance measure parameters.