Academic literature on the topic 'ALG – Application-Level Gateway'

IETF has specified Mobile IPv4 and Mobile IPv6 in RFC3344 and RFC3775 respectively, but not yet discussed Mobile IPv4/v6 in any published RFC. This paper proposes a scheme to solve one of Mobile IPv4/v6 problems which Home Agent (HA) locates in IPv6 network, and Correspondent Node (CN) locates in IPv4 network, while Mobile Node (MN) moves within IPv4 network. In the solution, a gateway called Mobile IPv4/v6 translation gateway (MIPv4/v6-TG) is introduced to bridge between IPv4 network and IPv6 network, which is made up of a traditional NAT-PT gateway and a Mobile IP application level gateway (MIP-ALG) built upon the NAT-PT gateway. MIP-ALG maintains a MIP table, a data structure, which is formed by entries. We use the MIP table to realize the communication between the IPv4 entities and the IPv6 entities. The creation, usage and update processes of MIP table are described in this paper. And it can work compatibly with RFC3344 and RFC3775.

Tunnel establishment, like HTTPS tunnel or related ones, between a computer protected by a security gateway and a remote server located outside the protected network is the most effective way to bypass the network security policy. Indeed, a permitted protocol can be used to embed a forbidden one until the remote server. Therefore, if the resulting information flow is ciphered, security standard tools such as application level gateways (ALG), firewalls, intrusion detection system (IDS), do not detect this violation. In this paper, we describe a statistical analysis of ciphered flows that allows detection of the carried inner protocol. Regarding the deployed security policy, this technology could be added in security tools to detect forbidden protocols usages. In the defence domain, this technology could help preventing information leaks through side channels. At the end of this article, we present a tunnel detection tool architecture and the results obtained with our approach on a public database containing real data flows.

IPv4 and IPv6 will coexist for a long time, due to ISPes’ inertia in the transition from IPv4 to IPv6. Domain Name System (DNS) is a very important functional unit in the Internet. This paper describres the hierarchy and operating process of IPv6 DNS, IPv6 DNS resolver, and presents the DNS transition from IPv4 to IPv6 in particular. We suggest two methods to implement DNS service during the transition period: DNS-Application Level Gateway (DNS-ALG) with Network Address Translation-Protocol Translation (NAT-PT), and dual stacks. And we also propose their respective operational principles. This paper is of valuable reference for network engineers to construct DNS in the transition phase.

The purpose of this article is to show a specific approach in the design, construction and protection of a computer network for a medium-sized company. When designing the network, the specifics of the building and the location of the individual nodes of the network (user computers and servers) are taken into account. To meet the requirements of users and the maximum protection of their devices, an adequate architecture and topology of network components have been selected and implemented. Particular attention is paid to the expected threats and appropriate means and methods for their prevention are provided

The sheer volume of data accumulated in many scientific disciplines as well as in industry is a critical point that requires immediate attention. The handling of large data sets will become a limiting factor - even for data intensive applications running on future Exascale systems. Nowadays, Big Data can be more a collection of challenges for data processing at large scale and less a tool box of solutions used to improve applications, scale well, and handle the constantly growing data sets. There is an urgent need for intelligent mechanisms to acquire, process, and analyze data, which have to run and scale efficiently on current and future computing architectures. The complexity of Big Data applications will highly profit from flexible workflow systems that consider the full data life cycle, from data acquisition to long-term storage and towards the curation of knowledge. To maximize the applicability of HPC systems for Big Data workflows, several changes in the system architecture and its software need to be considered. First, in order to exploit all available I/O capacities an adaptable monitoring system needs to collect information about I/O patterns of application and workflows as well as provide information to model the I/O subsystem. The goal is to collect long term performance data, to evaluate this data, and finally to show how and why resources cannot be used to their full potential. Second, as the complexity of systems is continuously increasing, the level of abstraction that is presented to the user needs to increase with at least the same rate in order to ensure that the current usability is at least maintained. This is accomplished by employing science gateways as well as workflow and metadata technologies.

<title>ABSTRACT</title> <p>A cybersecurity exploit can be crafted to affect the vehicle diagnostic adapter system, which consists of the technician, vehicle diagnostic adapter, device drivers, and maintenance software all working together in a trusting relationship.</p> <p>In this paper, application layer encryption of the SAE J1939 diagnostic traffic between the vehicle diagnostic application and the in-vehicle secure gateway is developed to mitigate the vulnerabilities in potential attack paths. The proposed encryption strategy uses AES-128, which uses 16-byte cipher blocks. The secure connection is established by adjusting the bit rate to over twice the normal speed and packing a single J1939 message into two encrypted sequential CAN frames,</p> <p>The in-vehicle diagnostic gateway employs a hardware security module. A provisioning process is employed wherein the diagnostic application and the hardware security module both generate public-private key pairs. An elliptic curve Diffie-Hellman (ECDH) key exchange then takes place. Thus, each diagnostic session uses ephemeral symmetric session keys that are securely exchanged between the hardware security module and the diagnostics application.</p> <p>This approach is effective in mitigating attacks originating at the driver (DLL) level, such as an attacker that would exfiltrate and modify data using the system and vehicle diagnostic subsystems in a Windows environment. Also, as the secure key system can be centrally administered, the ability for user attribution through key management is possible.</p> <p>While the approach requires the addition of a hardware security module on the vehicle, the hardware strategy presented could be implemented in an arbitrary electronic control module on the vehicle. Vulnerabilities and mitigations are explained in detail to provide a solution to secure diagnostic sessions for heavy vehicles.</p> <p><bold>Citation:</bold> J. Daily, P. Kulkarni, “Secure Heavy Vehicle Diagnostics”, In <italic>Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium</italic> (GVSETS), NDIA, Novi, MI, Aug. 13-15, 2020.</p>

Abstract Traditional simulation-based approach for Gas-Lift Optimization depends heavily on the quality of reservoir and fluid data. Excessive OPEX and man-hours are needed to maintain data integrity and to ensure the models are suitably calibrated. Even then, pseudo-steady-state models do not consider losses due to multi-pointing condition and slugging behavior; and for dynamic multiphase flow simulation, the added complexity and man-hours required to assert accurate results cannot be sustained on a full field scale deployment. Gas-Lift Optimization essentially relies on the relationship between the Well Production Rate with the Gas-Lift Injection Rate. The objective of the proposed solution is to remove the need for well models, correlations and personnel from the optimization process and to implement a data-driven (model-free) approach that, by focusing just on the relationship of these variables over time is able to find the next best optimized Gas-Lift Injection Rate setpoint and to implement it directly at the wells via an automated local control loop. This data-driven approach has been compartmentalized and developed as an Edge Application, ran directly on site in an IIOT gateway device. This method has the advantage of providing a predictive response that can be used directly in conjunction with a solver for single-well and multi-well optimization (handling well level and group level constraints by need). The application operates under iterative optimization cycles that progress towards system optimality. Even though well conditions are constantly changing over time, and consequently system optimality, these changes are reflected in the high-frequency data gathered by the application running on the gateway on site. Due to the iterative nature of the process, the solver can recognize these changes and react accordingly, adjusting based on the new system conditions in a closed-loop manner. This paper presents the methodology and the results of a case study of eight wells, including both, single and multi-well optimization. All these wells are unconventional horizontal wells from the Permian basin in Texas, US. Regardless of the complexities associated with unconventional wells, noted by severe slugging and fast changing well conditions, in all the cases the results were outstanding. For the single well optimization, the candidate well was able to outperform the remaining wells in the pad by 5% in production improvement. For the multi-well optimization results vary from 5% to 25% production improvements. The full execution and optimization process was done in a fully autonomous manner, removing completely office and field personnel, as well as the need for well modeling from the optimization process. This solution demonstrates a fully autonomous and Data-Driven Gas-Lift Optimization workflow, from data gathering and processing, edge computation, multi-well optimization based on field constraints, to the direct well implementation via closed-loop control.

Following a review of Vital Signs – indicators of ecosystem health – in the coastal parks of the Northeast Coastal and Barrier Network (NCBN), knowledge of shoreline change was ranked as the top variable for monitoring. Shoreline change is a basic element in the management of any coastal system because it contributes to the understanding of the functioning of the natural resources and to the administration of the cultural resources within the parks. Collection of information on the vectors of change relies on the establishment of a rigorous system of protocols to monitor elements of the coastal geomorphology that are guided by three basic principles: 1) all of the elements in the protocols are to be based on scientific principles; 2) the products of the monitoring must relate to issues of importance to park management; and 3) the application of the protocols must be capable of implementation at the local level within the NCBN. Changes in ocean shoreline position are recognized as interacting with many other elements of the Ocean Beach-Dune Ecosystem and are thus both driving and responding to the variety of natural and cultural factors active at the coast at a variety of temporal and spatial scales. The direction and magnitude of shoreline change can be monitored through the application of a protocol that tracks the spatial position of the neap-tide, high tide swash line under well-defined conditions of temporal sampling. Spring and fall surveys conducted in accordance with standard operating procedures will generate consistent and comparable shoreline position data sets that can be incorporated within a data matrix and subsequently analyzed for temporal and spatial variations. The Ocean Shoreline Position Monitoring Protocol will be applied to six parks in the NCBN: Assateague Island National Seashore, Cape Cod National Seashore, Fire Island National Seashore, Gateway National Recreation Area, George Washington Birthplace National Monument, and Sagamore Hill National Historic Site. Monitoring will be accomplished with a Global Positioning System (GPS )/ Global Navigation Satellite System (GNSS) unit capable of sub-meter horizontal accuracy that is usually mounted on an off-road vehicle and driven along the swash line. Under the guidance of a set of Standard Operating Procedures (SOPs) (Psuty et al., 2022), the monitoring will generate comparable data sets. The protocol will produce shoreline change metrics following the methodology of the Digital Shoreline Analysis System developed by the United States Geological Survey. Annual Data Summaries and Trend Reports will present and analyze the collected data sets. All collected data will undergo rigorous quality-assurance and quality-control procedures and will be archived at the offices of the NCBN. All monitoring products will be made available via the National Park Service’s Integrated Resource Management Applications Portal.