Biblio

Smart building security systems typically consist of sensors and controllers that monitor power operating systems, alarms, camera monitoring, access controls, and many other important information and security systems. These systems are managed and controlled through online platforms. A successful attack on one of these platforms may result in the failure of one or more critical intelligent systems in the building. In this paper, the security requirements in the application layer of any IoT system were discussed, in particular the role of IoT platforms in dealing with the security problems that smart buildings are exposed to and the extent of their strength to reduce the attacks they are exposed to, where an experimental platform was designed to test the presence of security vulnerabilities and This was done by using the Zed Attack Proxy (ZAP) tool, according to the OWASP standards and security level assessment, and the importance of this paper comes as a contribution to providing information about the most famous IoT platforms and stimulating work to explore security concerns in IoT-based platforms.

The military operations in low communications infrastructure scenarios employ flexible solutions to optimize the data processing cycle using situational awareness systems, guaranteeing interoperability and assisting in all processes of decision-making. This paper presents an architecture for the integration of Command, Control, Computing, Communication, Intelligence, Surveillance and Reconnaissance Systems (C4ISR), developed within the scope of the Brazilian Ministry of Defense, in the context of operations with Unmanned Aerial Vehicles (UAV) - swarm drones - and the Internet-to-the-battlefield (IoBT) concept. This solution comprises the following intelligent subsystems embedded in UAV: STFANET, an SDN-Based Topology Management for Flying Ad Hoc Network focusing drone swarms operations, developed by University of Rio Grande do Sul; Interoperability of Command and Control (INTERC2), an intelligent communication middleware developed by Brazilian Navy; A Mission-Oriented Sensors Array (MOSA), which provides the automatization of data acquisition, data fusion, and data sharing, developed by Brazilian Army; The In-Flight Awareness Augmentation System (IFA2S), which was developed to increase the safety navigation of Unmanned Aerial Vehicles (UAV), developed by Brazilian Air Force; Data Mining Techniques to optimize the MOSA with data patterns; and an adaptive-collaborative system, composed of a Software Defined Radio (SDR), to solve the identification of electromagnetic signals and a Geographical Information System (GIS) to organize the information processed. This research proposes, as a main contribution in this conceptual phase, an application that describes the premises for increasing the capacity of sensing threats in the low structured zones, such as the Amazon rainforest, using existing communications solutions of Brazilian defense monitoring systems.

The FAA proposes Safety Continuum that recognizes the public expectation for safety outcomes vary with aviation sectors that have different missions, aircraft, and environments. The purpose is to align the rigor of oversight to the public expectations. An aircraft, its variants or derivatives may be used in operations with different expectations. The differences in mission might bring immutable risks for some applications that reuse or revise the original aircraft type design. The continuum enables a more agile design approval process for innovations in the context of a dynamic ecosystems, addressing the creation of variants for different sectors and needs. Since an aircraft type design can be reused in various operations under part 91 or 135 with different mission risks the assurance case will have many branches reflecting the variants and derivatives.This paper proposes a model for the holistic, performance-based, through-life safety assurance case that focuses applicant and oversight alike on achieving the safety outcomes. This paper describes the application of goal-based, technology-neutral features of performance-based assurance cases extending the philosophy of UL 4600, to the Safety Continuum. This paper specifically addresses component reuse including third-party vehicle modifications and changes to operational concept or eco-system. The performance-based assurance argument offers a way to combine the design approval more seamlessly with the oversight functions by focusing all aspects of the argument and practice together to manage the safety outcomes. The model provides the context to assure mitigated risk are consistent with an operation’s place on the safety continuum, while allowing the applicant to reuse parts of the assurance argument to innovate variants or derivatives. The focus on monitoring performance to constantly verify the safety argument complements compliance checking as a way to assure products are "fit-for-use". The paper explains how continued operational safety becomes a natural part of monitoring the assurance case for growing variety in a product line by accounting for the ecosystem changes. Such a model could be used with the Safety Continuum to promote applicant and operator accountability delivering the expected safety outcomes.

Aviation is a highly sophisticated and complex System-of-Systems (SoSs) with equally complex safety oversight. As novel products with autonomous functions and interactions between component systems are adopted, the number of interdependencies within and among the SoS grows. These interactions may not always be obvious. Understanding how proposed products (component systems) fit into the context of a larger SoS is essential to promote the safe use of new as well as conventional technology.UL 4600, is a Standard for Safety for the Evaluation of Autonomous Products specifically written for completely autonomous Load vehicles. The goal-based, technology-neutral features of this standard make it adaptable to other industries and applications.This paper, using the philosophy of UL 4600, gives guidance for creating an assurance case for products in an SoS context. An assurance argument is a cogent structured argument concluding that an autonomous aircraft system possesses all applicable through-life performance and safety properties. The assurance case process can be repeated at each level in the SoS: aircraft, aircraft system, unmodified components, and modified components. The original Equipment Manufacturer (OEM) develops the assurance case for the whole aircraft envisioned in the type certification process. Assurance cases are continuously validated by collecting and analyzing Safety Performance Indicators (SPIs). SPIs provide predictive safety information, thus offering an opportunity to improve safety by preventing incidents and accidents. Continuous validation is essential for risk-based approval of autonomously evolving (dynamic) systems, learning systems, and new technology. System variants, derivatives, and components are captured in a subordinate assurance case by their developer. These variants of the assurance case inherently reflect the evolution of the vehicle-level derivatives and options in the context of their specific target ecosystem. These subordinate assurance cases are nested under the argument put forward by the OEM of components and aircraft, for certification credit.It has become a common practice in aviation to address design hazards through operational mitigations. It is also common for hazards noted in an aircraft component system to be mitigated within another component system. Where a component system depends on risk mitigation in another component of the SoS, organizational responsibilities must be stated explicitly in the assurance case. However, current practices do not formalize accounting for these dependencies by the parties responsible for design; consequently, subsequent modifications are made without the benefit of critical safety-related information from the OEMs. The resulting assurance cases, including 3rd party vehicle modifications, must be scrutinized as part of the holistic validation process.When changes are made to a product represented within the assurance case, their impact must be analyzed and reflected in an updated assurance case. An OEM can facilitate this by integrating affected assurance cases across their customer’s supply chains to ensure their validity. The OEM is expected to exercise the sphere-of-control over their product even if it includes outsourced components. Any organization that modifies a product (with or without assurance argumentation information from other suppliers) is accountable for validating the conditions for any dependent mitigations. For example, the OEM may manage the assurance argumentation by identifying requirements and supporting SPI that must be applied in all component assurance cases. For their part, component assurance cases must accommodate all spheres-of-control that mitigate the risks they present in their respective contexts. The assurance case must express how interdependent mitigations will collectively assure the outcome. These considerations are much more than interface requirements and include explicit hazard mitigation dependencies between SoS components. A properly integrated SoS assurance case reflects a set of interdependent systems that could be independently developed..Even in this extremely interconnected environment, stakeholders must make accommodations for the independent evolution of products in a manner that protects proprietary information, domain knowledge, and safety data. The collective safety outcome for the SoS is based on the interdependence of mitigations by each constituent component and could not be accomplished by any single component. This dependency must be explicit in the assurance case and should include operational mitigations predicated on people and processes.Assurance cases could be used to gain regulatory approval of conventional and new technology. They can also serve to demonstrate consistency with a desired level of safety, especially in SoSs whose existing standards may not be adequate. This paper also provides guidelines for preserving alignment between component assurance cases along a product supply chain, and the respective SoSs that they support. It shows how assurance is a continuous process that spans product evolution through the monitoring of interdependent requirements and SPI. The interdependency necessary for a successful assurance case encourages stakeholders to identify and formally accept critical interconnections between related organizations. The resulting coordination promotes accountability for safety through increased awareness and the cultivation of a positive safety culture.

The ongoing COVID-19 virus pandemic has resulted in a global tragedy due to its lethal spread. The population's vulnerability grows as a result of a lack of effective helping agents and vaccines against the virus. The spread of viruses can be mitigated by minimizing close connections between people. Social distancing is a critical containment tool for COVID-19 prevention. In this paper, the social distancing violations that are being made by the people when they are in public places are detected. As per CDC (Centers for Disease Control and Prevention) minimum distance that should be maintained by people is 2-3 meters to prevent the spread of COVID- 19, the proposed tool will be used to detect the people who are maintaining less than 2-3 meters of distance between themselves and record them as a violation. As a result, the goal of this work is to develop a deep learning-based system for object detection and tracking models in social distancing detection. For object detection models, You Only Look Once, Version 3 (YOLO v3) is used in conjunction with deep sort algorithms to balance speed and accuracy. To recognize persons in video segments, the approach applies the YOLOv3 object recognition paradigm. An efficient computer vision-based approach centered on legitimate continuous tracking of individuals is presented to determine supportive social distancing in public locations by creating a model to generate a supportive climate that contributes to public safety and detect violations through camera.

SDN represents a significant advance for the telecom world, since the decoupling of the control and data planes offers numerous advantages in terms of management dynamism and programmability, mainly due to its software-based centralized control. Unfortunately, these features can be exploited by malicious entities, who take advantage of the centralized control to extend the scope and consequences of their attacks. When this happens, both the legal and network technical fields are concerned with gathering information that will lead them to the root cause of the problem. Although forensics and incident response processes share their interest in the event information, both operate in isolation due to the conceptual and pragmatic challenges of integrating them into SDN environments, which impacts on the resources and time required for information analysis. Given these limitations, the current work focuses on proposing a framework for SDNs that combines the above approaches to optimize the resources to deliver evidence, incorporate incident response activation mechanisms, and generate assumptions about the possible origin of the security problem.

Cooperative secure computing based on the relationship between numerical value and numerical interval is not only the basic problems of secure multiparty computing but also the core problems of cooperative secure computing. It is of substantial theoretical and practical significance for information security in relation to scientific computing to continuously investigate and construct solutions to such problems. Based on the Goldwasser-Micali homomorphic encryption scheme, this paper propose the Morton rule, according to the characteristics of the interval, a double-length vector is constructed to participate in the exclusive-or operation, and an efficient cooperative decision-making solution for integer and integer interval security is designed. This solution can solve more basic problems in cooperative security computation after suitable transformations. A theoretical analysis shows that this solution is safe and efficient. Finally, applications that are based on these protocols are presented.

Supervisory Control and Data Acquisition (SCADA) systems are used to control and monitor components within the energy grid, playing a significant role in the stability of the system. As a part of critical infrastructures, components in these systems have to fulfill a variety of different requirements regarding their dependability and must also undergo strict audit procedures in order to comply with all relevant standards. This results in a slow adoption of new functionalities. Due to the emerged threat of cyberattacks against critical infrastructures, extensive security measures are needed within these systems to protect them from adversaries and ensure a stable operation. In this work, a solution is proposed to integrate extensive security measures into current systems. By deploying additional security-gateways into the communication path between two nodes, security features can be integrated transparently for the existing components. The developed security-gateway is compliant to all regulatory requirements and features an internal architecture based on the separation-of-concerns principle to increase its security and longevity. The viability of the proposed solution has been verified in different scenarios, consisting of realistic field tests, security penetration tests and various performance evaluations.

We present the new class of non-uniform Rowhammer access patterns that bypass undocumented, proprietary in-DRAM Target Row Refresh (TRR) while operating in a production setting. We show that these patterns trigger bit flips on all 40 DDR4 DRAM devices in our test pool. We make a key observation that all published Rowhammer access patterns always hammer “aggressor” rows uniformly. While uniform accesses maximize the number of aggressor activations, we find that in-DRAM TRR exploits this behavior to catch aggressor rows and refresh neighboring “victims” before they fail. There is no reason, however, to limit Rowhammer attacks to uniform access patterns: smaller technology nodes make underlying DRAM technologies more vulnerable, and significantly fewer accesses are nowadays required to trigger bit flips, making it interesting to investigate less predictable access patterns. The search space for non-uniform access patterns, however, is tremendous. We design experiments to explore this space with respect to the deployed mitigations, highlighting the importance of the order, regularity, and intensity of accessing aggressor rows in non-uniform access patterns. We show how randomizing parameters in the frequency domain captures these aspects and use this insight in the design of Blacksmith, a scalable Rowhammer fuzzer that generates access patterns that hammer aggressor rows with different phases, frequencies, and amplitudes. Blacksmith finds complex patterns that trigger Rowhammer bit flips on all 40 of our recently purchased DDR4 DIMMs, \$2.6 \textbackslashtimes\$ more than state of the art, and generating on average \$87 \textbackslashtimes\$ more bit flips. We also demonstrate the effectiveness of these patterns on Low Power DDR4X devices. Our extensive analysis using Blacksmith further provides new insights on the properties of currently deployed TRR mitigations. We conclude that after almost a decade of research and deployed in-DRAM mitigations, we are perhaps in a worse situation than when Rowhammer was first discovered.

Global cybersecurity threats have grown as a result of the evolving digital transformation. Cybercriminals have more opportunities as a result of digitization. Initially, cyberthreats take the form of phishing in order to gain confidential user credentials.As cyber-attacks get more sophisticated and sophisticated, the cybersecurity industry is faced with the problem of utilising cutting-edge technology and techniques to combat the ever-present hostile threats. Hackers use phishing to persuade customers to grant them access to a company’s digital assets and networks. As technology progressed, phishing attempts became more sophisticated, necessitating the development of tools to detect phishing.Machine learning is unsupervised one of the most powerful weapons in the fight against terrorist threats. The features used for phishing detection, as well as the approaches employed with machine learning, are discussed in this study.In this light, the study’s major goal is to propose a unique, robust ensemble machine learning model architecture that gives the highest prediction accuracy with the lowest error rate, while also recommending a few alternative robust machine learning models.Finally, the Random forest algorithm attained a maximum accuracy of 96.454 percent. But by implementing a hybrid model including the 3 classifiers- Decision Trees,Random forest, Gradient boosting classifiers, the accuracy increases to 98.4 percent.

The growing amount of data and advances in data science have created a need for a new kind of cloud platform that provides users with flexibility, strong security, and the ability to couple with supercomputers and edge devices through high-performance networks. We have built such a nation-wide cloud platform, called "mdx" to meet this need. The mdx platform's virtualization service, jointly operated by 9 national universities and 2 national research institutes in Japan, launched in 2021, and more features are in development. Currently mdx is used by researchers in a wide variety of domains, including materials informatics, geo-spatial information science, life science, astronomical science, economics, social science, and computer science. This paper provides an overview of the mdx platform, details the motivation for its development, reports its current status, and outlines its future plans.

State-of-the-art approaches in gait analysis usually rely on one isolated tracking system, generating insufficient data for complex use cases such as sports, rehabilitation, and MedTech. We address the opportunity to comprehensively understand human motion by a novel data model combining several motion-tracking methods. The model aggregates pose estimation by captured videos and EMG and EIT sensor data synchronously to gain insights into muscle activities. Our demonstration with biceps curl and sitting/standing pose generates time-synchronous data and delivers insights into our experiment’s usability, advantages, and challenges.

With their variety of application verticals, smart cities represent a killer scenario for Cloud-IoT computing, e.g. fog computing. Such applications require a management capable of satisfying all their requirements through suitable service placements, and of balancing among QoS-assurance, operational costs, deployment security and, last but not least, energy consumption and carbon emissions. This keynote discusses these aspects over a motivating use case and points to some open challenges.

With billions of devices already connected to the network's edge, the Internet of Things (IoT) is shaping the future of pervasive computing. Nonetheless, IoT applications still cannot escape the need for the computing resources available at the fog layer. This becomes challenging since the fog nodes are not necessarily secure nor reliable, which widens even further the IoT threat surface. Moreover, the security risk appetite of heterogeneous IoT applications in different domains or deploy-ment contexts should not be assessed similarly. To respond to this challenge, this paper proposes a new approach to optimize the allocation of secure and reliable fog computing resources among IoT applications with varying security risk level. First, the security and reliability levels of fog nodes are quantitatively evaluated, and a security risk assessment methodology is defined for IoT services. Then, an online, incentive-compatible mechanism is designed to allocate secure fog resources to high-risk IoT offloading requests. Compared to the offline Vickrey auction, the proposed mechanism is computationally efficient and yields an acceptable approximation of the social welfare of IoT devices, allowing to attenuate security risk within the edge network.

The distributed energy resources (DERs) have significantly stimulated the development of decentralized energy system and changed the way how the energy system works. In recent years, peer-to-peer (P2P) trading has drawn attention as a promising alternative for prosumers to engage with the energy market more actively, particular by using the emerging blockchain technology. Blockchain can securely hold critical information and store data in blocks linking with chain, providing a desired platform for the P2P energy trading. This paper provides a detailed description of blockchain-enabled P2P energy trading, its essential components, and how it can be implemented within the local energy market An analysis of potential threats during blockchain-enabled P2P energy trading is also performed, which subsequently results in a list of operation and privacy requirements suggested to be implemented in the local energy market.

Financial technology (Fintech) is an amalgamation of financial management using a technology system. Fintech has become a public concern because this service provides many service features to make it easier from the financial side, such as being used in cooperative financial institutions, banking and insurance. This paper will analyze the opportunities and challenges of Fintech sharia in Indonesia. By exploring the existing literature, this article will try to answer that question. This research is carried out using a literature review approach and comparative qualitative method which will determined the results of the SWOT analysis of sharia financial technology in indonesia. It is needed to mitigate risk of funding in a peer to peer method in overcoming the security of funds and data from investors, firstly companies can perform transparency on the clarity of investor funds. This is done as one of the facilities provided to investors in the Fintech application. In the future, it is hoped that in facing competition, sharia-based fintech companies must be able to provide targeted services through the socialization of sharia fintech to the public, both online and offline. Investors are expected to be more careful before investing in choosing Fintech Peer to Peer (P2P) Lending services by checking the list of Fintech lending and lending companies registered and found by the Financial Services Authority (OJK).

With the development of social networks, traditional covert communication requires more consideration of lossy processes of Social Network Platforms (SNPs), which is called robust steganography. Since JPEG compression is a universal processing of SNPs, a method using repeated JPEG compression to fit transport channel matching is recently proposed and shows strong compression-resist performance. However, the repeated JPEG compression will inevitably introduce other artifacts into the stego image. Using only traditional steganalysis methods does not work well towards such robust steganography under low payload. In this paper, we propose a simple and effective method to detect the mentioned steganography by chasing both steganographic perturbations as well as continuous compression artifacts. We introduce compression-forensic features as a complement to steganalysis features, and then use the ensemble classifier for detection. Experiments demonstrate that this method owns a similar and better performance with respect to both traditional and neural-network-based steganalysis.

Minimizing embedding impact model of steganography has good performance for steganalysis detection. By using effective distortion cost function and coding method, steganography under this model becomes the mainstream embedding framework recently. In this paper, to improve the anti-detection performance, a new steganography optimization model by constructing a reference cover is proposed. First, a reference cover is construed by performing a filtering operation on the cover image. Then, by minimizing the residual between the reference cover and the original cover, the optimization function is formulated considering the effect of different modification directions. With correcting the distortion cost of +1 and \_1 modification operations, the stego image obtained by the proposed method is more consistent with the natural image. Finally, by applying the proposed framework to the cost function of the well-known HILL embedding, experimental results show that the anti-detection performance of the proposed method is better than the traditional method.

Due to the simplicity of implementation and high threat level, SQL injection attacks are one of the oldest, most prevalent, and most destructive types of security attacks on Web-based information systems. With the continuous development and maturity of artificial intelligence technology, it has been a general trend to use AI technology to detect SQL injection. The selection of the sample set is the deciding factor of whether AI algorithms can achieve good results, but dataset with tagged specific category labels are difficult to obtain. This paper focuses on data augmentation to learn similar feature representations from the original data to improve the accuracy of classification models. In this paper, deep convolutional generative adversarial networks combined with genetic algorithms are applied to the field of Web vulnerability attacks, aiming to solve the problem of insufficient number of SQL injection samples. This method is also expected to be applied to sample generation for other types of vulnerability attacks.

Aiming at the specificity and complexity of the power IoT terminal, a method of power IoT terminal firmware vulnerability detection based on memory fuzzing is proposed. Use the method of bypassing the execution to simulate and run the firmware program, dynamically monitor and control the execution of the firmware program, realize the memory fuzzing test of the firmware program, design an automatic vulnerability exploitability judgment plug-in for rules and procedures, and provide power on this basis The method and specific process of the firmware vulnerability detection of the IoT terminal. The effectiveness of the method is verified by an example.

The power industrial control system is an important part of the national critical Information infrastructure. Its security is related to the national strategic security and has become an important target of cyber attacks. In order to solve the problem that the vulnerability detection technology of power industrial control system cannot meet the requirement of non-destructive, this paper proposes an industrial control vulnerability analysis technology combined with dynamic and static analysis technology. On this basis, an industrial control non-destructive vulnerability detection system is designed, and a simulation verification platform is built to verify the effectiveness of the industrial control non-destructive vulnerability detection system. These provide technical support for the safety protection research of the power industrial control system.

Static analyzers have become increasingly popular both as developer tools and as subjects of empirical studies. Whereas static analysis tools exist for disparate programming languages, the bulk of the empirical research has focused on the popular Java programming language. In this paper, we investigate to what extent some known results about using static analyzers for Java change when considering C\#-another popular object-oriented language. To this end, we combine two replications of previous Java studies. First, we study which static analysis tools are most widely used among C\# developers, and which warnings are more commonly reported by these tools on open-source C\# projects. Second, we develop and empirically evaluate EagleRepair: a technique to automatically fix code in response to static analysis warnings; this is a replication of our previous work for Java [20]. Our replication indicates, among other things, that 1) static code analysis is fairly popular among C\# developers too; 2) Re-Sharper is the most widely used static analyzer for C\#; 3) several static analysis rules are commonly violated in both Java and C\# projects; 4) automatically generating fixes to static code analysis warnings with good precision is feasible in C\#. The EagleRepair tool developed for this research is available as open source.

In this paper we consider cyber security requirements of the smart buildings. We identify cyber risks, threats, attack scenarios, security objectives and related security controls. The work was done as a part of a smart building design and construction work. From the controls identified w e concluded security practices for engineering-in smart buildings security. The paper provides an idea toward which system security engineers can strive in the basic design and implementation of the most critical components of the smart buildings. The intent of the concept is to help practitioners to avoid ad hoc approaches in the development of security mechanisms for smart buildings with shared space.

With the gradual construction and implementation of cloud computing, the information security problem of the smart grid has surfaced. Therefore, in the construction of the smart grid cloud computing platform, information security needs to be considered in planning, infrastructure, and management at the same time, and it is imminent to build an information network that is secure from terminal to the platform to data. This paper introduces the concept of cloud security technology and the latest development of cloud security technology and discusses the main strategies of cloud security construction in electric power enterprises.

In order to solve the problem of untargeted data security grading methods in the process of power grid data governance, this paper analyzes the mainstream data security grading standards at home and abroad, investigates and sorts out the characteristics of power grid data security grading requirements, and proposes a method that considers national, social, and A grid data security classification scheme for the security impact of four dimensions of individuals and enterprises. The plan determines the principle of power grid data security classification. Based on the basic idea of “who will be affected to what extent and to what extent when the power grid data security is damaged”, it defines three classification factors that need to be considered: the degree of impact, the scope of influence, and the objects of influence, and the power grid data is divided into five security levels. In the operation stage of power grid data security grading, this paper sorts out the experience and gives the recommended grading process. This scheme basically conforms to the status quo of power grid data classification, and lays the foundation for power grid data governance.