Addressing Operator Privacy in Automatic Dependent Surveillance - Broadcast (ADS-B)

We investigate security of ADS-B system and propose a framework composed of two solutions that would require minimal change to the existing system. The investigation focuses on providing an encrypted ADS-B system that provides confidentiality, availability, and integrity while requiring minimal changes to the existing ADS-B specification. The proposed framework consisting of two solutions is envisioned to be implemented through software updates while providing backwards compatibility. The most challenging requirement during this study was to work within the constraints of the existing ADS-B system

Trustworthiness Requirements for Manufacturing Cyber-Physical Systems

Distributed manufacturing operations include cyber-physical systems vulnerable to cyber-attacks. Long time not considered a priority, cybersecurity jumped to the forefront of manufacturing concerns due to the need to network together legacy, newer equipment, and entire operation centers. This paper proposes trustworthiness solutions for integrated manufacturing physical-cyber worlds, where trustworthiness is defined to complement system dependability requirements with cybersecurity requirements, such that the resulting manufacturing cyber-physical system delivers services that can justifiably be trusted. Acknowledging the inevitability of cyber-attacks, the paper models the cybersecurity component using the resilient systems framework, where system resilience is viewed as preservation of a required state of cybersecurity

Linear Model Estimation of Nonlinear Systems Using Least-Squares Algorithm5

This paper presents utilizes Least-Squares Algorithm to obtain more accurate linear models of nonlinear systems using parameter estimation. This approach generates an optimal linear model which is valid over a wide range of trajectories and converges to the desired steady-state value with no errors unlike the existing techniques. The proposed technique is very efficient and does not require storing the data. Therefore, it can easily be used and implemented with limited resources for undergraduate curriculum especially in underdeveloped countries. Most available techniques for linearization of nonlinear system are only valid about the operating point; furthermore, the knowledge of the operating point is required. The advantage of proposed technique is that the linearized model is not sensitive to the operating point; the estimation only requires the order of the system not the operating point. A physical example will be giving to illustrate the linear model of jet engines nonlinear system

Software Safety and Security Risk Mitigation in Cyber-Physical Systems

Cyber-physical systems (CPSs) offer many opportunities but pose many challenges--especially regarding functional safety, cybersecurity, and their interplay, as well as the systems\u27 impact on society. Consequently, new methods and techniques are needed for CPS development and assurance. This article [and issue] aims to address some of these challenges

Evaluation and Analysis of Distributed Graph-Parallel Processing Frameworks

A number of graph-parallel processing frameworks have been proposed to address the needs of processing complex and large-scale graph structured datasets in recent years. Although significant performance improvement made by those frameworks were reported, comparative advantages of each of these frameworks over the others have not been fully studied, which impedes the best utilization of those frameworks for a specific graph computing task and setting. In this work, we conducted a comparison study on parallel processing systems for large-scale graph computations in a systematic manner, aiming to reveal the characteristics of those systems in performing common graph algorithms with real-world datasets on the same ground. We selected three popular graph-parallel processing frameworks (Giraph, GPS and GraphLab) for the study and also include a representative general data-parallel computing system— Spark—in the comparison in order to understand how well a general data-parallel system can run graph problems. We applied basic performance metrics measuring speed, resource utilization, and scalability to answer a basic question of which graph-parallel processing platform is better suited for what applications and datasets. Three widely-used graph algorithms— clustering coefficient, shortest path length, and PageRank score—were used for benchmarking on the targeted computing systems.We ran those algorithms against three real world network datasets with diverse characteristics and scales on a research cluster and have obtained a number of interesting observations. For instance, all evaluated systems showed poor scalability (i.e., the runtime increases with more computing nodes) with small datasets likely due to communication overhead. Further, out of the evaluated graphparallel computing platforms, PowerGraph consistently exhibits better performance than others

Aircraft Access to System-Wide Information Management Infrastructure

Within the Federal Aviation Administration’s (FAA) NextGen project, System Wide Information Management (SWIM) program is the essential core in facilitating the collaborative access to the aviation information by various stakeholders. The Aircraft Access to SWIM (AAtS) initiative is an effort to connect the SWIM network to the aircraft to exchange the situational information between the aircraft and the National Airspace System (NAS). This paper summarizes the highlevel design and implementation of the AAtS infrastructure; namely the communication medium design, data management system, pilot peripheral, as well as the security of the data being exchanged and the performance of the entire system. The research work led to the design and implementation of a reliable data storing and exchange system between the Electronic Flight Bag (EFB) (pilot peripheral to the AAtS network) and the SWIM network architecture. Issues such as cyber-security, performance, availability, and quality of service in the AAtS are investigated and mitigation approaches toward more secure and efficient service provided to the aircraft and to NAS are discussed

Why a future commercial spacecraft must be able to SWIM

Regarding current as well as future commercial space transportation (CST) projects, new re-entry trajectory profiles, differing from capsule and shuttle-like approaches, have to be taken into account. These characteristics are mainly ruled by the principle of “landing like an aircraft at an airport”. This directly generates the need to be taken in a system wide information management (SWIM) consideration because of the fact, that all the future air traffic participants are requested to act as SWIM communicating sub-systems by the future Single European Sky Air Traffic Management Research (SESAR) SWIM “Intranet for ATM” concept. Against the background of the global character of future CST operations and the associated SWIM harmonization need referring the U.S. Next Generation Air Transportation System (NextGen) and SESAR, the presented solution addresses near real-time information sharing for normal air traffic protection purposes in the event of a future space vehicle breakup and bases on the already harmonized data format standards Aeronautical Information Exchange Model (AIXM) and Flight Information Exchange Model (FIXM)

A DATA MINING ALGORITH FOR MULTI LEVEL PREFETCHING IN STORAGE SYSTEMS

Parallel storage systems have been highly scalable and widely used in support of dataintensive applications. In future systems with the nature of massive data processing and storing, hybrid storage systems opt for a solution to fulfill a variety of demands such as large storage capacity, high I/O performance and low cost. Hybrid storage systems (HSS) contain both high-end storage components (e.g. solid-state disks and hard disk drives) to guarantee performance, and low-end storage components (e.g. tapes) to reduce cost. In HSS, transferring data back and forth among solid-state disks (SSDs), hard disk drives (HDDs), and tapes plays a critical role in achieving high I/O performance. Prefetching is a promising solution to reduce the latency of data transferring in HSS. However, prefetching in the context of HSS is technically challenging due to an interesting dilemma: aggressive prefetching is required to efficiently reduce I/O latency, whereas overaggressive prefetching may waste I/O bandwidth by transferring useless data from HDDs to SSDs or from tapes to HDDs. To address this problem, we propose a data-minin multi-layer prefetching algorithm that can judiciously prefetch data from tapes to HDDs and from HDDs to SSDs. To evaluate our algorithm, we develop an analytical model and the experimental results reveal that our prefetching algorithm improves the performance in hybrid storage systems