Biblio

Cloud computing is a modern type of service that provides each consumer with a large-scale computing tool. Different cyber-attacks can potentially target cloud computing systems, as most cloud computing systems offer services to so many people who are not known to be trustworthy. Therefore, to protect that Virtual Machine from threats, a cloud computing system must incorporate some security monitoring framework. There is a tradeoff between the security level of the security system and the performance of the system in this scenario. If a strong security is required then a stronger security service using more rules or patterns should be incorporated and then in proportion to the strength of security, it needs much more computing resources. So the amount of resources allocated to customers is decreasing so this research work will introduce a new way of security system in cloud environments to the VM in this research. The main point of Fog computing is to part of the cloud server's work in the ongoing study tells the step-by-step cloud server to change gigantic information measurement because the endeavor apps are relocated to the cloud to keep the framework cost. So the cloud server is devouring and changing huge measures of information step by step so it is rented to keep up the problem and additionally get terrible reactions in a horrible device environment. Cloud computing and Fog computing approaches were combined in this paper to review data movement and safe information about MDHC.

Fog computing plays a critical role in the provisioning of computing tasks in the context of Internet of Things (IoT) services. However, the security of IoT services against breaches and attacks relies heavily on the security of fog resources, which must be properly implemented and managed. Increasing security investments and integrating the security aspect into the core processes and operations of fog computing including resource management will increase IoT service protection as well as the trustworthiness of fog service providers. However, this requires careful modeling of the security requirements of IoT services as well as theoretical and experimental evaluation of the tradeoff between security and performance in fog infrastructures. To this end, this paper explores a new model for fog resource allocation according to security and Quality of Service (QoS). The problem is modeled as a multi-objective linear optimization problem and solved using conventional, off-the-shelf optimizers by applying the preemptive method. Specifically, two objective functions were defined: one representing the satisfaction of the security design requirements of IoT services and another that models the communication delay among the different virtual machines belonging to the same service request, which might be deployed on different intermediary fog nodes. The simulation results show that the optimization is efficient and achieves the required level of scalability in fog computing. Moreover, a tradeoff needs to be pondered between the two criteria during the resource allocation process.

In this paper we propose a security and cost aware scheduling heuristic for real-time workflow jobs that process Internet of Things (IoT) data with various security requirements. The environment under study is a four-tier architecture, consisting of IoT, mist, fog and cloud layers. The resources in the mist, fog and cloud tiers are considered to be heterogeneous. The proposed scheduling approach is compared to a baseline strategy, which is security aware, but not cost aware. The performance evaluation of both heuristics is conducted via simulation, under different values of security level probabilities for the initial IoT input data of the entry tasks of the workflow jobs.

Fog computing is a new computing paradigm that utilizes numerous mutually cooperating terminal devices or network edge devices to provide computing, storage, and communication services. Fog computing extends cloud computing services to the edge of the network, making up for the deficiencies of cloud computing in terms of location awareness, mobility support and latency. However, fog nodes are not active enough to perform tasks, and fog nodes recruited by cloud service providers cannot provide stable and continuous resources, which limits the development of fog computing. In the process of cloud service providers using the resources in the fog nodes to provide services to users, the cloud service providers and fog nodes are selfish and committed to maximizing their own payoffs. This situation makes it easy for the fog node to work negatively during the execution of the task. Limited by the low quality of resource provided by fog nodes, the payoff of cloud service providers has been severely affected. In response to this problem, an appropriate incentive mechanism needs to be established in the fog computing environment to solve the core problems faced by both cloud service providers and fog nodes in maximizing their respective utility, in order to achieve the incentive effect. Therefore, this paper proposes an incentive model based on repeated game, and designs a trigger strategy with credible threats, and obtains the conditions for incentive consistency. Under this condition, the fog node will be forced by the deterrence of the trigger strategy to voluntarily choose the strategy of actively executing the task, so as to avoid the loss of subsequent rewards when it is found to perform the task passively. Then, using evolutionary game theory to analyze the stability of the trigger strategy, it proves the dynamic validity of the incentive consistency condition.

Cloud computing has helped in managing big data and providing resources remotely and ubiquitously, but it has some latency and security concerns. Fog has provided tremendous advantages over cloud computing which include low latency rate, improved real-time interactions, reduced network traffic overcrowding, and improved reliability, however, security concerns need to be addressed separately. Another major issue in the cloud is Cloud Lock-in/Vendor Lock-in. Through this research, an effort has been made to extend fog computing and Searchable Encryption technologies. The proposed system can reduce the issue of cloud lock-in faced in traditional cloud computing. The SE schemes used in this paper are Symmetric Searchable Encryption (SSE) and Multi-keyword Ranked Searchable Encryption (MRSE) to achieve confidentiality, privacy, fine-grained access control, and efficient keyword search. This can help to achieve better access control and keyword search simultaneously. An important use of this technique is it helps to prevent the issue of cloud/vendor lock-in. This can shift some computation and storage of index tables over fog nodes that will reduce the dependency on Cloud Service Providers (CSPs).

With the advancement in the growth of Internet-of-Things (IoT), its number of applications has also increased such as in healthcare, smart cities, vehicles, industries, household appliances, and Smart Grids (SG). One of the major applications of IoT is the SG and smart meter which consists of a large number of internet-connected sensors and can communicate bi-directionally in real-time. The SG network involves smart meters, data collectors, generators, and sensors connected with the internet. SG networks involve the generation, distribution, transmission, and consumption of electrical power supplies. It consists of Household Area Network (HAN), and Neighborhood Area Network (NAN) for communication. Smart meters can communicate bidirectionally with consumers and provide real-time information to utility offices. But this communication channel is a wide-open network for data transmission. Therefore, it makes the SG network and smart meter vulnerable to outside hacker and various Cyber-Physical System (CPS) attacks such as False Data Injection (FDI), inserting malicious data, erroneous data, manipulating the sensor reading values. Here cryptography techniques can play a major role along with the private blockchain model for secure data transmission in smart meters. Hence, to overcome these existing issues and challenges in smart meter communication we have proposed a blockchain-based system model for secure communication along with a novel Advanced Elliptic Curve Cryptography Digital Signature (AECCDS) algorithm in Fog Computing (FC) environment. Here FC nodes will work as miners at the edge of smart meters for secure and real-time communication. The algorithm is implemented using iFogSim, Geth version 1.9.25, Ganache, Truffle for compiling smart contracts, Anaconda (Python editor), and ATOM as language editor for the smart contracts.

The Internet of Vehicles (IoV) is a network that considers vehicles as intelligent machines. They interact and communicate with each other to improve the performance and safety of traffic. IoV solves certain problems, but it has some issues such as response time, which prompted researchers to propose the integration of Fog Computing into vehicular networks. In Vehicular Fog Computing (VFC), the services are provided at the edge of the network to increase data rate and reduce response time. However, in order to satisfy network users, the security and privacy of sensitive data should be guaranteed. Using pseudonyms instead of real identities is one of the techniques considered to preserve the privacy of users, however, this can push malicious vehicles to exploit such a process and launch the Sybil attack by creating several pseudonyms in order to perform various malicious activities. In this paper, we describe the Sybil attack effects on VFC networks and compare them to those in conventional networks, as well as identify the various existing methods for detecting this attack and determine if they are applicable to VFC networks.

Fog Computing was envisioned to solve problems like high latency, mobility, bandwidth, etc. that were introduced by Cloud Computing. Fog Computing has enabled remotely connected IoT devices and sensors to be managed efficiently. Nonetheless, the Fog-Cloud paradigm suffers from various security and privacy related problems. Blockchain ensures security in a trustless way and therefore its applications in various fields are increasing rapidly. In this work, we propose a Fog-Cloud architecture that enables Blockchain to ensure security, scalability, and privacy of remotely connected IoT devices. Furthermore, our proposed architecture also efficiently manages common problems like ever-increasing latency and energy consumption that comes with the integration of Blockchain in Fog-Cloud architecture.

Internet of Things (IoT) is penetrating into every aspect of our personal lives including our body, our home and our living environment which poses numerous security challenges. The number of heterogeneous connected devices is increasing exponentially in IoT, which in turn increases the attack surface of IoT. This forces the need for uniform, distributed security mechanism which can efficiently detect the attack at faster rate in highly scalable IoT environment. The proposed work satisfies this requirement by providing a security framework which combines Fog computing and Software Defined Networking (SDN). The experimental results depicts the effectiveness in protecting the IoT applications at faster rate

Cloud Computing is a technology which provides flexibility through scalability. Like, Cloud computing, nowadays, Fog computing is considered more revolutionary and dynamic technology. But the main problem with the Fog computing is to take care of its security as in this also person identification is done by single Sign-In system. To come out from the security problem raised in Fog computing, an innovative approach has been suggested here. In the present paper, an approach has been proposed that combines different biometric techniques to verify the authenticity of a person and provides a complete model that will be able to provide a necessary level of verification and security in fog computing. In this model, several biometric techniques have been used and each one of them individually helps extract out more authentic and detailed information after every step. Further, in the presented paper, different techniques and methodologies have been examined to assess the usefulness of proposed technology in reducing the security threats. The paper delivers a capacious technique for biometric authentication for bolstering the fog security.

In addition to the feature of real-time analytics, fog computing allows detection nodes to be located at the edges of the network. On the other hand, intrusion detection systems require prompt and accurate attack analysis and detection. These systems must promptly respond appropriately to an event. Increasing the speed of data transfer and response requires less bandwidth in the network, reducing the data sent to the cloud and increasing information security as some of the advantages of using detection nodes at the edges of the network in fog computing. The use of neural networks in the analyzer engine is important for the low consumption of system resources, avoidance of explicit production of detection rules, detection of known deformed attacks, and the ability to manage noise and outlier data. The current paper proposes and implements the architecture of network intrusion detection nodes in fog computing, in addition to presenting the proposed fog network architecture. In the proposed architecture, each node can, in addition to performing intrusion detection operations, observe the nodes around it, find the compromised node or intrusion node, and inform the nodes close to it to disconnect from that node.

Smart cities and societies are driving unprecedented technological and socioeconomic growth in everyday life albeit making us increasingly vulnerable to infinitely and incomprehensibly diverse threats. Short Message Service (SMS) spam is one such threat that can affect mobile security by propagating malware on mobile devices. A security breach could also cause a mobile device to send spam messages. Many works have focused on classifying incoming SMS messages. This paper proposes a tool to detect spam from outgoing SMS messages, although the work can be applied to both incoming and outgoing SMS messages. Specifically, we develop a system that comprises multiple machine learning (ML) based classifiers built by us using three classification methods – Naïve Bayes (NB), Support Vector Machine (SVM), and Naïve Bayes Multinomial (NBM)- and five preprocessing and feature extraction methods. The system is built to allow its execution in cloud, fog or edge layers, and is evaluated using 15 datasets built by 4 widely-used public SMS datasets. The system detects spam SMSs and gives recommendations on the spam filters and classifiers to be used based on user preferences including classification accuracy, True Negatives (TN), and computational resource requirements.

Converging Information Technology (IT) and Operations Technology (OT) in modern factories remains a challenging task. Several approaches such as Cloud, Fog or Edge computing aim to provide possible solutions for bridging OT that requires strict real-time processing with IT that targets computing functionality. In this context, this paper contributes to ongoing Fog computing research by presenting three industrial use cases with a specific focus on consolidation of functionality. Each use case exemplifies scenarios on how to use the computational resources closer to the edge of the network provided by a Fog Computing Platform (FCP). All use-cases utilize the same proposed FCP, which allows drawing a set of requirements on future FCPs, e.g. hardware, virtualization, security, communication and resource management. The central element of the FCP is the Fog Node (FN), built upon commercial off-the-shelf (COTS) multicore processors (MCPs) and virtualization support. Resource management tools, advanced security features and state of the art communication protocols complete the FCP. The paper concludes by outlining future research challenges by comparing the proposed FCP with the identified requirements.

For optimal use of cloud resources and to reduce the latency of cloud users, the cloud computing model extends the services such as networking facilities, computational capabilities and storage facilities based on demand. Due to the dynamic behavior, distributed paradigm and heterogeneity present among the processing elements, devices and service oriented pay per use policies; the cloud computing environment is having its availability, security and privacy issues. Among these various issues one of the important issues in cloud computing paradigm is DDoS attack. This paper put in plain words the DDoS attack, its detection as well as prevention mechanisms in cloud computing environment. The inclusive study also explains about the effects of DDoS attack on cloud platform and the related defense mechanisms required to be considered.

Internet of Things (IoT) has been growing exponentially in the commercial market in recent years. It is also a fact that people hold one or more computing devices at home. Many of them have been developed to operate through internet connectivity with cloud computing technologies that result in the demand for fast, robust, and secure services. In most cases, the lack of these services makes difficult the transfer of data to fulfill the devices' purposes. Under these conditions, an intermediate layer or middleware is needed to process, filter, and send data through a more efficient alternative. This paper presents the adaptive solution of a middleware architecture as an intermediate layer between smart devices and cloud computing to enhance the management of the heterogeneity of data provining from IoT devices. The proposed middleware provides easy configuration, adaptability, and bearability for different environments. Finally, this solution has been implemented in the healthcare domain, in which IoT solutions are deployed into Ambient Assisted Living (AAL) environments.

Internet of things (IoT) mainly depends on clouds to process and store their data. Clouds cannot handle the volume and velocity of data generated by IoT. IoT is delay-sensitive and resources limited. Fog computing proposed endorsing the internet of things (IoT) demands. Fog computing extends the cloud computing service to the edge of the network. Fog utilization reduces response time and network overhead while maintaining security aspects. isolation and operating system (OS) dependency achieved by using virtualization. Blockchain proposed to solve the security and privacy of fog computing. Blockchain is a decentralized, immutable ledger. fog computing with blockchain proposed as an IoT infrastructure. Fog computing adopted with lightweight blockchain in this proposed work. This adaptation endorses the IoT demands for low response time with limited resources. This paper explores system applicability. Varies from other papers that focus on one factor such as privacy or security-applicability of the proposed model achieved by concentration different IoT needs and limits. Response time and ram usage with 1000 transactions did not encroach 100s and 300MiB in the proposed model.

In this ever updating digitalized world, everything is connected with just few touches away. Our phone is connected with things around us, even we can see live video of our home, shop, institute or company on the phone. But we can't track suspicious activity 24*7 hence needed a smart system to track down any suspicious activity taking place, so it automatically notifies us before any robbery or dangerous activity takes place. We have proposed a framework to tackle down this security matter with the help of sensors enabled cameras(IoT) connected through a FOG layer hence called FOGIoT which consists of small servers configured with Human Activity Analysis Algorithm. Any suspicious activity analyzed will be reported to responsible personnel and the due action will be taken place.

Fog Computing is one of the edge computing paradigms that envisages being the proximate processing and storage infrastructure for a multitude of IoT appliances. With its dynamic deployability as a medium level cloud service, fog nodes are enabling heterogeneous service provisioning infrastructure that features scalability, interoperability, and adaptability. Out of the various 5G based services possible with the fog computing platforms, security services are imperative but minimally investigated direct live. Thus, in this research, we are focused on launching security services in a fog node with an architecture capable of provisioning on-demand service requests. As the fog nodes are constrained on resources, our intention is to integrate light-weight virtualization technology such as Docker for forming the service provisioning infrastructure. We managed to launch multiple security instances configured to be Intrusion Detection and Prevention Systems (IDPSs) on the fog infrastructure emulated via a Raspberry Pi-4 device. This environment was tested with multiple network flows to validate its feasibility. In our proposed architecture, orchestration strategies performed by the security orchestrator were stated as guidelines for achieving pragmatic, dynamic orchestration with fog in IoT deployments. The results of this research guarantee the possibility of developing an ambient security service model that facilitates IoT devices with enhanced security.

Fog computing is a new distributed computing paradigm that extends the cloud to the network edge. Fog computing aims at improving quality of service, data access, networking, computation and storage. However, the security and privacy issues persist, even if many cloud solutions were proposed. Indeed, Fog computing introduces new challenges in terms of security and privacy, due to its specific features such as mobility, geo-distribution and heterogeneity etc. Blockchain is an emergent concept bringing efficiency in many fields. In this paper, we propose a new access control scheme based on blockchain technology for the fog computing with fault tolerance in the context of the Internet of Things. Blockchain is used to provide secure management authentication and access process to IoT devices. Each network entity authenticates in the blockchain via the wallet, which allows a secure communication in decentralized environment, hence it achieves the security objectives. In addition, we propose to establish a secure connection between the users and the IoT devices, if their attributes satisfy the policy stored in the blockchain by smart contract. We also address the blockchain transparency problem by the encryption of the users attributes both in the policy and in the request. An authorization token is generated if the encrypted attributes are identical. Moreover, our proposition offers higher scalability, availability and fault tolerance in Fog nodes due to the implementation of load balancing through the Min-Min algorithm.

Fog Computing provides users with the cloud facilities at the network edge. It may be assumed to be a virtual platform with adequate storage., computation and processing facilities for latency-sensitive applications. The basic difference lies with the fact that this platform is decentralized in nature. In addition., the fog systems or devices process data locally., are conveyable and are capable of being installed on heterogenous hardware. This versatility in its behavior and it being at the network edge turns the attention towards the security of the users sensitive data (in transition or at rest). In this paper., the authors have emphasized on the security of the fog level in typical Fog- IoT architecture. Various security factors (along with their subfactors) persisting at fog level are identified and discussed in detail. The authors have presented a hierarchy of fog computing security factors that is expected to help in considering security in a systematic and efficient manner. Further., the authors have also ranked the same through Analytical Hierarchy Process (AHP) and compared the results with Fuzzy-AHP (F-AHP). The results are found to be highly correlated.

The Fog is an emergent computing architecture that will support the mobility and geographic distribution of Internet of Things (IoT) nodes and deliver context-aware applications with low latency to end-users. It forms an intermediate layer between IoT devices and the Cloud. However, Fog computing brings many requirements that increase the cost of security management. It inherits the security and trust issues of Cloud and acquires some of the vulnerable features of IoT that threaten data and application confidentiality, integrity, and availability. Several existing solutions address some of the security challenges following adequate adaptation, but others require new and innovative mechanisms. These reflect the need for a Fog architecture that provides secure access, efficient authentication, reliable and secure communication, and trust establishment among IoT devices and Fog nodes. The Fog might be more convenient to deploy decentralized authentication solutions for IoT than the Cloud if appropriately designed. In this short survey, we highlight the Fog security challenges related to IoT security requirements and architectural design. We conduct a comparative study of existing Fog architectures then perform a critical analysis of different authentication schemes in Fog computing, which confirms some of the fundamental requirements for effective authentication of IoT devices based on the Fog, such as decentralization, less resource consumption, and low latency.

Fog computing was emerged as mini-clouds deployed close to the ground to reduce communication overhead and time latency between the cloud and end-users' devices. Because fog computing is an extension of cloud computing, it inherits the security and privacy issues cloud computing has faced. If a Fog Node (FN) serving end-devices goes rogue or becomes maliciously compromised, this would hinder individuals' and organizations' data security (e.g., Confidentiality, Integrity, and Availability). This paper presents a novel scheme based on the Ciphertext-Policy-Attribute-Based-Encryption (CP-ABE) and hashing cryptographic primitives to minimize the amount of data in danger of breach by rogue fog nodes with maintaining the fog computing services provided to end-users' devices. This scheme manages to oust rogue Fog Nodes (FNs) and to prevent them from violating end-users' data security while guarantying the features provided by the fog computing paradigm. We demonstrate our scheme's applicability and efficiency by carrying out performance analysis and analyzing its security, and communication overhead.

The most recent and important developments in the field of computer networks are cloud and fog computing. In this study, modern cloud computer networks comprising computers, internet of things (IoT), fog servers, and cloud servers for data transmission, is investigated. A cloud computer networks can be modeled as a network with nodes and arcs, in which each arc represents a transmission line, and each node represents an IoT device, a fog server, or a cloud server. Each transmission line has several possible capacities and is regarded as a multistate. The network is termed a multi-state cloud computer network (MCCN). this study firstly constructs the mathematic model to elucidate the flow relationship among the IoT devices, edge servers, and cloud servers and subsequently develop an algorithm to evaluate the performance of the MCCN by calculating network reliability which is defined as the probability of the data being successfully processed by the MCCN.

The advent of Internet and recent technological developments have paved the way for IoT devices in different sectors. The demand for real-time response led to the development of fog computing which is now a popular computing technique. It provides processing, computing and storage at the network edge for latency-sensitive applications such as banking transactions, healthcare etc. This has further led to the pool of user's sensitive data across the web that needs to be secured. In order to find an efficient security solution, it is mandatory to prioritize amongst different fog-level security factors. The authors have therefore, adopted a fuzzy-based Analytical Hierarchy Approach (AHP) for ranking the security attributes in fog-driven IoT environment. The results have also been compared to the ones obtained from classical-AHP and are found to be correlated.

Budding technologies like IoT requires minimum latency for performing real-time applications. The IoT devices collect a huge amount of big data and stores in the cloud environment, because of its on-demand services and scalability. But processing the needed information of the IoT devices from the cloud computing environment is found to be time-sensitive one. To eradicate this issue fog computing environment was created which acts an intermediate between the IoT devices and cloud computing environment. The fog computing performs intermediate computation and storage which is needed by IoT devices and it eliminates the drawbacks of latency and bandwidth limitation faced by directly using cloud computing for storage and accessing. The fog computing even though more advantageous it is more exposed to security issues by its architecture. This paper concentrates more on the security issues met by fog computing and the present methods used by the researchers to secure fog with their pros and cons.