Biblio

This paper aims to present a performance comparison of new authenticated encryption (AE) algorithm with the objective of high network security and better efficiency as compared to the defacto standard. This algorithm is based on a critical property of nonce-misuse-resistance incorporating DNA computation for securing the key, here the processing unit of DNA block converts the input key into its equivalent DNA base formats based on the ASCII code table. The need for secure exchange of keys through a public channel has become inevitable and thus, the proposed architecture will enhance the secrecy by using DNA cryptography. These implementations consider Advanced Encryption Standard in Galois Counter mode (AES-GCM) as a standard for comparison.

The emergence of the 5G network has boosted the advancements in the field of the internet of things (IoT) and edge/cloud computing. We present a novel architecture to detect fire in indoor and outdoor environments, dubbed as EAC-FD, an abbreviation of edge and cloud-based fire detection. Compared with existing frameworks, ours is lightweight, secure, cost-effective, and reliable. It utilizes a hybrid edge and cloud computing framework with Intel neural compute stick 2 (NCS2) accelerator is for inference in real-time with Raspberry Pi 3B as an edge device. Our fire detection model runs on the edge device while also capable of cloud computing for more robust analysis making it a secure system. We compare different versions of SSD-MobileNet architectures with ours suitable for low-end devices. The fire detection model shows a good balance between computational cost frames per second (FPS) and accuracy.

Cloud security includes the strategies which works together to guard data and infrastructure with a set of policies, procedures, controls and technologies. These security events are arranged to protect cloud data, support supervisory obedience and protect customers' privacy as well as setting endorsement rules for individual users and devices. The partition-based handling and encryption mechanism which provide fine-grained admittance control and protected data sharing to the data users in cloud computing. Graph partition problems fall under the category of NP-hard problems. Resolutions to these problems are generally imitative using heuristics and approximation algorithms. Partition problems strategy is used in bi-criteria approximation or resource augmentation approaches with a common extension of hyper graphs, which can address the storage hierarchy.

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.

With the recognition of cyberspace as an operating domain, concerted effort is now being placed on addressing it in the whole-of-domain manner found in land, sea, undersea, air, and space domains. Among the first steps in this effort is applying the standard supporting concepts of security, defense, and deterrence to the cyber domain. This paper presents an architecture that helps realize forward defense in cyberspace, wherein adversarial actions are repulsed as close to the origin as possible. However, substantial work remains in making the architecture an operational reality including furthering fundamental research cyber science, conducting design trade-off analysis, and developing appropriate public policy frameworks.

This paper aims to address the problem of Deepfake Detection using a Two-Stream Capsule Network. First we review methods used to create Deepfake content, as well as methods proposed in the literature to detect such Deepfake content. We then propose a novel architecture to detect Deepfakes, which consists of a two-stream Capsule network running in parallel that takes in both RGB images/frames as well as Error Level Analysis images. Results show that the proposed approach exhibits the detection accuracy of 73.39 % and 57.45 % for the Deepfake Detection Challenge (DFDC) and the Celeb-DF datasets respectively. These results are, however, from a preliminary implementation of the proposed approach. As part of future work, population-based optimization techniques such as Particle Swarm Optimization (PSO) will be used to tune the hyper parameters for better performance.

This paper designs a data anomaly detection method for power grid data centers. The method uses cloud computing architecture to realize the storage and calculation of large amounts of data from power grid data centers. After that, the STL decomposition method is used to decompose the grid data, and then the decomposed residual data is used for anomaly analysis to complete the detection of abnormal data in the grid data. Finally, the feasibility of the method is verified through experiments.

This paper describes a Cyber Threat, Vulnerability and Defense Modeling and Simulation tool kit used for evaluation of systems and networks to improve cyber resiliency. This capability is used to help increase the resiliency of networks at various stages of their lifecycle, from initial design and architecture through the operation of deployed systems and networks. Resiliency of computer systems and networks to cyber threats is facilitated by the modeling of agile and resilient defenses versus threats and running multiple simulations evaluated against resiliency metrics. This helps network designers, cyber analysts and Security Operations Center personnel to perform trades using what-if scenarios to select resiliency capabilities and optimally design and configure cyber resiliency capabilities for their systems and networks.

Modern vehicles equipped with a large number of electronic components, sensors, actuators, and extensive connectivity, are the classical example of cyber-physical systems (CPS). Communication as an integral part of the CPS has enabled and offered many value-added services for vehicular networks. The communication mechanism helps to share contents with all vehicular network nodes and the surrounding environment, e.g., vehicles, traffic lights, and smart road signs, to efficiently take informed and smart decisions. Thus, it opens the doors to many security threats and vulnerabilities. Traditional TCP/IP-based communication paradigm focuses on securing the communication channel instead of the contents that travel through the network. Nevertheless, for content-centered application, content security is more important than communication channel security. To this end, named data networking (NDN) is one of the future Internet architectures that puts the contents at the center of communication and offers embedded content security. In this paper, we first identify the cyberattacks and security challenges faced by the vehicular CPS (VCPS). Next, we propose the NDN-based cyber-resilient, the layered and modular architecture for VCPS. The architecture includes the NDN's forwarding daemon, threat aversion, detection, and resilience components. A detailed discussion about the functionality of each component is also presented. Furthermore, we discuss the future challenges faced by the integration of NDN with VCPS to realize NDN-based VCPS.

Cyber-Physical System(CPS) is now a new evolutional morphology of embedded systems. With features of merging computation and physical processes together, the traditional verification and simulation methods have being challenged recently. After analyzed the state-of-art of related research, a new simulation environment is studied according to the characters of a special autonomous cyber-physical system-Unmanned Aerial Vehicle, and designed to be scene-driven, modeling and reconfigurable. In this environment, a novel CPS-in-loop architecture, which can support simulations under different customized scenes, is studied firstly to ensure its opening and flexibility. And as another foundation, some dynamics models of CPS and atmospheric ones of relative sensors are introduced to simulate the motion of CPS and the change of its posture. On the basis above, the reconfigurable scene-driven mechanisms that are Based on hybrid events are mainly excogitated. Then, different scenes can be configured in terms of special verification requirements, and then each scene will be decomposed into a spatio-temporal event sequence and scheduled by a scene executor. With this environment, not only the posture of CPS, but also the autonomy of its behavior can be verified and observed. It will be meaningful for the design of such autonomous CPS.

This paper presents ongoing work on the formalism of Cyber-Physical Systems (CPS) simulations. These systems are distributed real-time systems, and their simulations might be distributed or not. In this paper, we propose a model to describe the modular components forming a simulation of a CPS. The main goal is to introduce a model of generic simulation distributed architecture, on which we are able to execute a logical architecture of simulation. This architecture of simulation allows the expression of structural and behavioural constraints on the simulation, abstracting its execution. We will propose two implementations of the execution architecture based on generic architectures of distributed simulation: $\cdot$ The High Level Architecture (HLA), an IEEE standard for distributed simulation, and one of its open-source implementation of RunTime Infrastructure (RTI): CERTI. $\cdot$ The Distributed Simulation Scheduler (DSS), an Airbus framework scheduling predefined models. Finally, we present the initial results obtained applying our formalism to the open-source case study from the ROSACE case study.

Networked embedded systems (which include IoT, CPS, etc.) are vulnerable. Even though we know how to secure these systems, their heterogeneity and the heterogeneity of security policies remains a major problem. Designers face ever more sophisticated attacks while they are not always security experts and have to get a trade-off on design criteria. We propose in this paper the CLASA architecture (Cross-Layer Agent Security Architecture), a generic, integrated, inter-operable, decentralized and modular architecture which relies on cross-layering.

The main purpose to ensure the security for confidential medical data is to develop and implement the architecture of a medical cloud system, for storage, systematization, and processing of survey results (for example EEG) jointly with an algorithm for ensuring the protection of confidential data based on a fully homomorphic cryptosystem. The most optimal algorithm based on the test results (analysis of the time of encryption, decryption, addition, multiplication, the ratio of the signal-to-noise of the ciphertext to the open text), has been selected between two potential applicants for using (BFV and CKKS schemes). As a result, the CKKS scheme demonstrates maximal effectiveness in the context of the criticality of the requirements for an important level of security.

In view of the current status of Internet of Things applications and related security problems, the architecture system of Internet of Things applications based on block chain is introduced. First, it introduces the concepts related to blockchain technology, introduces the architecture system of iot application based on blockchain, and discusses its overall architecture design, key technologies and functional structure design. The product embodies the whole process of the Internet of Things platform on the basis of blockchain, which builds an infrastructure based on the Internet of Things and solves the increasingly serious security problems in the Internet of Things through the technical characteristics of decentralization.

Renewed focus on spacecraft networking by government and private industry promises to establish interoperable communications infrastructures and enable distributed computing in multi-nodal systems. Planned near-Earth and cislunar missions by NASA and others evidence the start of building this networking vision. Working with space agencies, academia, and industry, NASA has developed a suite of communications protocols and algorithms collectively referred to as Delay-Tolerant Networking (DTN) to support an interoperable space network. Included in the DTN protocol suite is a security protocol - the Bundle Protocol Security Protocol - which provides the kind of delay-tolerant, transport-layer security needed for cislunar and deep-space trusted networking. We present an analysis of the lifecycle of security operations inherent in a space network with a focus on the DTN-enabled space networking paradigm. This analysis defines three security-related roles for spacecraft (Security Sources, verifiers, and acceptors) and associates a series of critical processing events with each of these roles. We then define the set of required and optional actions associated with these security events. Finally, we present a series of best practices associated with policy configurations that are unique to the space-network security problem. Framing space network security policy as a mapping of security actions to security events provides the details necessary for making trusted networks semantically interoperable. Finally, this method is flexible enough to allow for customization even while providing a unifying core set of mandatory security actions.

Artificial intelligence (AI) technologies have given the cyber security industry a huge leverage with the possibility of having significantly autonomous models that can detect and prevent cyberattacks – even though there still exist some degree of human interventions. AI technologies have been utilized in gathering data which can then be processed into information that are valuable in the prevention of cyberattacks. These AI-based cybersecurity frameworks have commendable scalability about them and are able to detect malicious activities within the cyberspace in a prompter and more efficient manner than conventional security architectures. However, our one or two completed studies did not provide a complete and clear analyses to apply different machine learning algorithms on different media systems. Because of the existing methods of attack and the dynamic nature of malware or other unwanted software (adware etc.) it is important to automatically and systematically create, update and approve malicious packages that can be available to the public. Some of Complex tests have shown that DNN performs maybe can better than conventional machine learning classification. Finally, we present a multiple, large and hybrid DNN torrent structure called Scale-Hybrid-IDS-AlertNet, which can be used to effectively monitor to detect and review the impact of network traffic and host-level events to warn directly or indirectly about cyber-attacks. Besides this, they are also highly adaptable and flexible, with commensurate efficiency and accuracy when it comes to the detection and prevention of cyberattacks.There has been a multiplicity of AI-based cyber security architectures in recent years, and each of these has been found to show varying degree of effectiveness. Deep Neural Networks, which tend to be more complex and even more efficient, have been the major focus of research studies in recent times. In light of the foregoing, the objective of this paper is to discuss the use of AI methods in fighting cyberattacks like malware and DDoS attacks, with attention on DNN-based models.

Software-defined networking (SDN) is a new networking architecture having the concept of separation of control plane and data plane that leads the existing networks to be programmable, dynamically configurable and extremely flexible. This paradigm has huge benefits to organizations and large networks, however, its security is major issue and Distributed Denial of Service (DDoS) Attack has become a serious concern for the working of SDN. In this article, we have proposed a taxonomy of DDoS Defense Mechanisms in SDN Environment. We have categorized the various DDoS detection and mitigation techniques with respect to switch intelligence, Defense Deployment, Defense Activity and Network Flow Activities.

Over the last few years, the deployment of Internet of Things (IoT) is attaining much more concern on smart computing devices. With the exponential growth of small devices and at the same time cheap prices of these sensing devices, there raises an important question for the security of the stored information as these devices generate a large amount of private data for observing and controlling purposes. Distributed Denial of Service (DDoS) attacks are current examples of major security threats to IoT devices. As yet, no standard protocol can fully ensure the security of IoT devices. But adaptive decision making along with elasticity and incessant monitoring is required. These difficulties can be resolved with the assistance of Software Defined Networking (SDN) which can viably deal with the security dangers to the IoT devices in a powerful and versatile way without hampering the lightweightness of the IoT devices. Although SDN performs quite well for managing and controlling IoT devices, security is still an open concern. Nonetheless, there are a few challenges relating to the mitigation of DDoS attacks in IoT systems implemented with SDN architecture. In this paper, a brief overview of some of the popular DDoS attack mitigation techniques and their limitations are described. Also, the challenges of implementing these techniques in SDN-based architecture to IoT devices have been presented.

Scientific applications built on wide-area distributed systems such as emerging cloud based architectures and the legacy grid computing infrastructure often struggle with user adoption even though they succeed from a systems research perspective. This paper examines the coupling of user-centered design processes with modern distributed systems. Further in this paper, we describe approaches for conceptualizing a product that solves a recognized need: to develop a data gateway to serve the data management and research needs of experimentalists of electron microscopes and similar shared scientific instruments in the context of a research service laboratory. The purpose of the data gateway is to provide secure, controlled access to data generated from a wide range of scientific instruments. From the functional perspective, we focus on the basic processing of raw data that underlies the lab's "business" processes, the movement of data from the laboratory to central access and archival storage points, and the distribution of data to respective authorized users. Through the gateway interface, users will be able to share the instrument data with collaborators or copy it to remote storage servers. Basic pipelines for extracting additional metadata (through a pluggable parser framework) will be enabled. The core contribution described in this paper, building on the aforementioned distributed data management capabilities, is the adoption of user-centered design processes for developing the scientific user interface. We describe the user-centered design methodology for exploring user needs, iteratively testing the design, learning from user experiences, and adapting what we learn to improve design and capabilities. We further conclude that user-centered design is, in turn, best enabled by an adaptable distributed systems framework. A key challenge to implementing a user-centered design is to have design tools closely linked with a software system architecture that can evolve over time while providing a highly available data gateway. A key contribution of this paper is to share the insights from crafting such an evolvable design-build-evaluate-deploy architecture and plans for iterative development and deployment.

This paper proposes an artificial immune information security protection technology architecture for embedded system of Electric power equipment. By simulating the three functions of human immunity, namely "immune homeostasis", "immune surveillance" and "immune defense", the power equipment is endowed with the ability of human like active immune security protection. Among them, "immune homeostasis" is constructed by trusted computing technology components to establish a trusted embedded system running environment. Through fault-tolerant component construction, "immune surveillance" and "immune defense" realize illegal data defense, business logic legitimacy check and equipment status evaluation, realize real-time perception and evaluation of power equipment's own security status, as well as fault emergency handling and event backtracking record, so that power equipment can realize self recovery from abnormal status. The proposed technology architecture is systematic, scientific and rich in scalability, which can significantly improve the information security protection ability of electric power equipment.

The main objective of the proposed work is to build a reliable and secure architecture for cloud servers where users may safely store and transfer their data. This platform ensures secure communication between the client and the server during data transfer. Furthermore, it provides a safe method for sharing and transferring files from one person to another. As a result, for ensuring safe data on cloud servers, this research work presents a secure architecture combining three DNA cryptography, HMAC, and a third party Auditor. In order to provide security by utilizing various strategies, a number of traditional and novel cryptographic methods are investigated. In the first step, data will be encrypted with the help of DNA cryptography, where the encoded document will be stored in the cloud server. In next step, create a HMAC value of encrypted file, which was stored on cloud by using secret key and sends to TPA. In addition, Third Party Auditor is used for authenticate the purity of stored documents in cloud at the time of verification TPA also create HMAC value from Cloud stored data and verify it. DNA-based cryptographic technique, hash based message authentic code and third party auditor will provide more secured framework for data security and integrity in cloud server.

Modern embedded IoT devices are an attractive target for cyber attacks. For example, they can be used to disable entire factories and ask for ransom. Recovery of compromised devices is not an easy task, because malware can subvert the original software and make itself persistent. In addition, many embedded devices do not implement remote recovery procedures and, therefore, require manual intervention.Recent proposals from NIST and TCG define concepts and building blocks for cyber resilience: protection, detection and recovery. In this paper, we describe a system which allows implementing cyber resilient IoT devices that can be recovered remotely and timely. The proposed architecture consists of trusted data monitoring, local and remote attack detection, and enforced connections to remote services as building blocks for attack detection and recovery. Further, hardware- and software-based implementations of such a system are presented.

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.

The problem of buffer overflow in the information system is not threatening, and the system's own defense mechanism can detect and terminate code injection attacks. However, as countermeasures compete with each other, advanced stack overflow attacks have emerged: Return Oriented-Programming (ROP) technology, which has become a hot spot in the field of system security research in recent years. First, this article explains the reason for the existence of this technology and the attack principle. Secondly, it systematically expounds the realization of the return-oriented programming technology at home and abroad in recent years from the common architecture platform, the research of attack load construction, and the research of variants based on ROP attacks. Finally, we summarize the paper.

Nowadays, exploits often rely on a code-reuse approach. Short pieces of code called gadgets are chained together to execute some payload. Code-reuse attacks can exploit vul-nerabilities in the presence of operating system protection that prohibits data memory execution. The ROP chain construction task is the code generation for the virtual machine defined by an exploited executable. It is crucial to understand how powerful ROP attacks can be. Such knowledge can be used to improve software security. We implement MAJORCA that generates ROP and JOP payloads in an architecture agnostic manner and thoroughly consider restricted symbols such as null bytes that terminate data copying via strcpy. The paper covers the whole code-reuse payloads construction pipeline: cataloging gadgets, chaining them in DAG, scheduling, linearizing to the ready-to-run payload. MAJORCA automatically generates both ROP and JOP payloads for x86 and MIPS. MAJORCA constructs payloads respecting restricted symbols both in gadget addresses and data. We evaluate MAJORCA performance and accuracy with rop-benchmark and compare it with open-source compilers. We show that MAJORCA outperforms open-source tools. We propose a ROP chaining metric and use it to estimate the probabilities of successful ROP chaining for different operating systems with MAJORCA as well as other ROP compilers to show that ROP chaining is still feasible. This metric can estimate the efficiency of OS defences.