Security in Mission Critical Communication Systems

Commercial off-the-shelf (COTS) software products are being included in ever more complex and critical systems. There are clearly advantages to considering the use of COTS in such systems, but given the rigorous needs of such critical systems or subsystems, there are concerns about the suitability of COTS software for such applications. The AIAA’s Software Systems Technical Committee and the AIAA’s Computer Systems Technical Committee have undertaken an effort to produce a guidebook that captures issues related to the consideration and use of COTS products in these large, complex systems, with a special emphasis on those risks and risk mitigation approaches that relate to mission critical systems. This guidebook identifies a set of characteristics of mission critical systems that makes the consideration, selection and validation processes of COTS products (hardware, software, subsystems, etc.) an emerging factor in systems definition, development and acceptance. The guidebook discusses a large number of risk areas related to using COTS software products in mission critical systems and identifies various mitigation approaches to the risks. It includes detailed processes for selecting and evaluating the products and considerations for using COTS software products within the overall context of the software development life cycle standardized in IEEE/EIA 12207. Mission critical system characteristics such as reliability, safety, availability, maintainability and certification tend to influence whether or not COTS software should be considered for a given application. Once the suitability of COTS software has been determined, then it is possible that additional requirements may be placed on the product and/or the product’s vendor for such mission critical applications. Further, it is possible that certain system requirements and expectations may need to be modified because of the inclusion of COTS software products in that system. As COTS products continue to be considered as candidates for inclusion within mission critical systems, there are likely to be additional concerns and factors to emerge that will influence how both acquirers and suppliers decide if and/or when to use COTS products. Ongoing monitoring of this technology area seems to be warranted.

: The Computer Resource Management Technology Program (PE 64740F) is the sole Air Force engineering development program to focus on the problems associated with the acquisition, development, and support of computer resources within mission critical Air Force weapon systems. Engineering development is the final development and test of an operationally, technically, and economically desirable product. Mission critical systems are the airborne; spaceborne; command, control, communications and intelligence; and armament systems directly involved in the planning and execution of military missions. As the primary Air Force vehicle for transitioning the computer technology of advanced development work accomplished in industry, universities, and laboratories, the program's five continuing projects target the development and initial application of products which reduce software life cycle cost, enhance acquisition management control, and improve the quality and security of weapon system software.

The accelerating adoption of 5G and the emergence of 6G paradigms have introduced complex cybersecurity challenges, particularly due to the proliferation of heterogeneous devices, dynamic network slicing, and latency-sensitive applications. This article presents a hybrid intelligence-based architecture, SecureNet-6G, which offers real-time detection of cyber threats with Quality of Service (QoS) by combining Transformer-based temporal modeling alongside Graph Neural Network (GNN) based spatial learning. The system proposes a new two-head Transformer to detect encrypted traffic deviations and protocol-layer violations, which is combined with a CNN-Bi-LSTM-Autoencoder network to identify packet-level and behavioral signatures. A tuned GraphSAGE network using genetic algorithm can predict dynamical flow patterns between devices, creating an explainable representation of the network security. The model has been trained and tested on a mixture dataset obtained using 5G NSA/SA traffic, edge slice, and sensors. The proposed framework scored a detection accuracy of 91.72, a precision of 91.30, a recall of 91.05 and an F1-score of 91.17, exceeding the current baseline models by 2.1-4.6. Further, QoS preservation measures revealed that latency and packet loss were greatly reduced even in the case of attack. A comparative testing showed that SecureNet-6G inferred 60 times faster than cloud-based models and maintained more than 95 % network throughput. These results show that hybrid deep learning with graph reasoning is effective in managing the emerging 6G cyber-physical threats. The work is part of the development of smart, adaptive cybersecurity systems that can be implemented in real-time, mission-critical communication systems.

Specifying fault tolerance in mission critical intelligent systems

Ponte Academic JournalAug 2017, Volume 73, Issue 8 An Effective Model for Testing Distributed Embedded Systems using Scaffolding MethodAuthor(s): SASTRY JKR ,K. Chaitanya, K Raja Sekhara Rao, DBK KameshJ. Ponte - Aug 2017 - Volume 73 - Issue 8 doi: 10.21506/j.ponte.2017.8.1 Abstract:Many methods are in use for undertaking comprehensive testing of standalone embedded systems. Many intricate aspects which include throughput, response time, signal patterns, are be tested to ensure that the embedded have been functioning properly. Distributed embedded systems are being used quite frequently these days for many purposes commencing from Automation of automobiles to Home appliances to home security systems. Some of the Distributed systems are being used for monitoring and controlling safety critical and mission critical systems. The mission and safety critical systems require thorough testing. Many additional aspects are to be considered for testing a distributed embedded system which include testing message flow, arbitration, synchronization Heterogeneity of distributed system, portability etc. This paper presents a Modified Scaffolding method for undertaking testing of a distributed embedded system which is built using many heterogeneous microcontroller based systems. The method has been used for testing a pilot distributed embedded system and the results obtained by undertaking the testing have shown that the bugs existing in the development of embedded system have been thoroughly exposed.. Download full text:Check if you have access through your login credentials or your institution Username Password

When a fault occurs in the field, developers usually collect failure reports that contain function-call traces to uncover the root causes. Fault diagnosis in failure traces is an arduous task due to the volume and size of typical traces. Previously, we have conducted several research studies to diagnose faulty functions in function-call level traces of field failures. During our studies, we have found that different faults in closely related functions occur with similar function-call traces. We also infer from existing studies (including our previous work) that a classification or clustering algorithm can be trained on the function-call traces of a fault in a function and then be used to diagnose different faults in the traces where the same function appears. In this paper, we propose an emerging descriptive theory based on the propositions grounded in these empirical findings. There is scarcity of theorizing empirical findings in software engineering research and our work is a step towards filling this gap. The emerging theory is stated as: a fault in a function can be diagnosed from a function-call trace if the traces of the same or a different fault in that function are already known to a clustering or classification algorithm. We evaluate this theory using the criteria described in the literature. We believe that this emerging theory can help reduce the time spent in diagnosing the origin of faults in field traces.

The use of good random numbers is crucial to the security of many mission-critical systems. However, when such systems are replicated for Byzantine fault tolerance, a serious issue arises (i.e., how do we preserve the integrity of the systems while ensuring strong replica consistency?). Despite the fact that there exists a large body of work on how to render replicas deterministic under the benign fault model, the solutions regarding the random number control are often overly simplistic without regard to the security requirement, and hence, they are not suitable for practical Byzantine fault tolerance. In this chapter, the authors present a novel integrity-preserving replica coordination algorithm for Byzantine fault tolerant systems. The central idea behind our CD-BFT algorithm is that all random numbers to be used by the replicas are collectively determined, based on the contributions made by a quorum of replicas, at least f+1 of which are not faulty.

Physical layer security (PLS) in wireless communication systems has attracted extensive research attentions in recent years. Unlike cryptography-based methods applied in upper-layer in network, PLS methods are applied in physical layers and can provide information-theoretic security by utilizing the randomness of signals and wireless channels. In this survey, we provide a comprehensive review in the domain of physical layer authentication (PLA) in wireless communication systems, including the concepts, several key techniques of typical PLA architectures as well as future challenges and research trends in more sophisticated communication systems. The survey begins with an overview of the background and basic concepts of PLA, such as the general model of wireless security communication system, typical frameworks of key-based/less PLA systems, and the common attack models. We then discuss the major concerns and key techniques that are applied in PLA systems, where three types of authentication schemes are considered, i.e., the authentication based on channel information, radio-frequency and identity watermarks. Basic models and representative research results about key approaches and techniques applied to the authentication systems above are subsequently covered. Finally, the associated challenges and potential research trends of PLA in future communication systems are presented at the end of the survey paper.

An Optimized Intelligent Computational Security Model for Interconnected Blockchain-IoT System & Cities

Abstract: The service dramatically affects the number of guests staying at the hotel. Bali is the most visited tourist area by foreign tourists. Therefore, improved service is crucial for determining the rating level of a hotel. This research aims to combine two data mining algorithms: clustering and classification. This research is expected to contribute to hospitality in improving the best services for tourists, especially in the City of Bali. Clustering algorithms are used to group the best number of hotels based on the four clusters selected from the k-means clustering algorithm. The classification algorithm using C4.5 determines the factors most dominant in determining the hotel rating level based on the gain ratio. The data used in this study results from observations on the website agoda.com in Bali of 51 data. The results of this study explained that cluster_0 is the highest-rated cluster, with a total number of 19 hotels found in claster_0. Data cluster0 is used for classification analysis using a decision tree, and the most dominant factor is the service factor, with an accuracy of 80%. Keywords: data mining; kmeans; decision tree; hotel; bali; Abstrak: Pelayanan sangat mempengaruhi jumlah pengunjung yang menginap dihotel. Bali merupakan daerah wisata paling banyak dikunjungi oleh wisatawan mancanegara. Oleh karena itu, peningkatan pelayanan sangat penting untuk penentuan level rating dari hotel. Tujuan dari penelitian ini untuk menggabungkan dua algoritma data mining yaitu clustering dan klasifikasi. Dengan penelitian ini diharapkan dapat memberikan kontribusi bagi perhotelan dalam meningkatkan pelayanan yang terbaik bagi wisatawan khususnya di Kota Bali. Algoritma Clustering digunakan untuk mengelompokkan dari jumlah hotel yang terbaik berdasarkan empat cluster yang dipilih dari algoritma clustering berupa k-means. Algoritma klasifikasi menggunakan C4.5 digunakan untuk mengetahui faktor apa yang paling dominan dalam menentukan level rating hotel berdasarkan gain ratio. Data yang digunakan dalam penelitian ini hasil observasi di website agoda.com di bali sebanyak 51 data. Hasil dari penelitian ini menjelaskan dataset cluster_0 merupakan cluster rating tertinggi dengan jumlah 19 hotel yang terdapat di cluster_0. Data cluster_0 digunakan untuk analisis klasifikasi menggunakan decesion tree, didapat faktor yang paling dominan adalah faktor layanan dengan nilai akurasi sebesar 80%. Kata kunci: data mining; kmeans; decision tree; hotel; bali;

With the growing dependency of many technical, commercial, administrative and even social processes from computer software, the number of mission critical software projects rapidly increases. The rapid integration of formerly stand-alone systems into global networks subjects these systems to yet unknown threats. Even mission critical systems may be deliberately manipulated to let malicious attackers access vital system functions or to take over the entire system. Though such systems feature protection mechanism during operation, they are rather vulnerable during their software design and development process. This paper defines a secure software development process to reduce the risk of manipulation and enhance the trustworthiness of critical software produced by renowned manufaturers according to high quality standards. It also explained how this process may be implemented cost efficiently.KeywordsHash FunctionTrust CenterMission Critical SystemMission Critical ApplicationCertificate VerificationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Tradespace Exploration (TSE) is a process of analyzing various suitable alternatives in an intuitive manner. In recent years, TSE has emerged as a systematic strategy to assess the effectiveness and suitability of alternative conceptual designs. An advantage of TSE is that it promotes a detailed consideration of tradeoffs, which should be agreed upon by stakeholders prior to committing to a particular design. However, explicit consideration of the “-ilities,” such as reliability, availability, maintainability, as well as their associated cost are often omitted from such studies. A related trend in reliability engineering is the application of machine learning methods to various mission critical systems. Specifically, effective monitoring of a system’s health can identify preventive maintenance actions based on a usage profile. In this regard, prognostics and health management (PHM) has emerged as a promising approach to predict the deterioration of components prior to failure so that they can be maintained on an as-needed basis instead of performing costly part replacement at regular intervals to preserve reliability and safety. Previous PHM studies emphasize degradation modeling and predictive algorithms to improve state of health predictions. However, most of these techniques focus on improving performance within a single maintenance cycle, while fewer studies consider the effectiveness of alternative degradation models and predictive algorithms over multiple successive maintenance intervals. This dissertation presents two contributions (i) a method to incorporate reliability engineering into tradespace exploration, and (ii) a measure based on concepts from maintenance theory to provide a framework for the objective assessment of existing and future degradation models.

In this paper, we propose a fault tolerant network architecture called Hierarchical Scalable Fault-tolerant Ethernet (H-SAFE) for mission critical systems. The proposed architecture is a tree based structure which provides multiple paths to route a packet. If any failure occurs in current path, then the alternative path recovers the failure and reroute the packet to destination without any information loss. In the failure state of any route, the fault detection and rerouting can be done within 750ms, which is a reasonable time for fault tolerance.

Self-adaptation ability is particularly desirable for mission critical software (MCS). This paper proposes a fuzzy control-based approach to provide a systematic, engineering, and intuitive way for programmers to achieve software self adaptation. This approach uses fuzzy logic to handle uncertainty in software, uses natural-language style to describe self-adaptation logic, and makes control visible in software. These greatly shorten the knowledge and semantics gap between control engineering and software engineering, and reduce the realization difficulty of software self-adaptation. We illustrate our approach through the development of an adaptive MCS application in process control systems.

Fault-tolerant Ethernet (FTE) aims to keep data flowing in the network continuously even if there are faults in the network. This is an important requirement in mission critical systems that cannot afford for the network to go down even for a few seconds. In this paper we propose a novel approach for fault-tolerant Ethernet implementation. The proposed approach is a hybrid of conventional hardware and layer 2 software based approaches. Our approach mostly shows the strengths of conventional approaches. We then demonstrate our approach using a single network with redundant cable model that can be easily expanded into multi-cable model.