Biblio

Along with the ever increasing growth in data collection and its mining, there is an increasing fear of compromising individual and population privacy. Several techniques have been proposed in literature to preserve privacy of collected data while storing and processing. In this paper, we propose a privacy-aware architecture for storing and processing data in a Big Data warehouse. In particular, we propose a flexible, extendable, and adaptable architecture that enforces user specified privacy requirements in the form of Embedded Privacy Agreements. The paper discusses the details of the architecture with some implementation details.

We demonstrate an in-house built Endpoint Detection and Response (EDR) for linux systems using open-sourced tools like Osquery and Elastic. The advantage of building an in-house EDR tools against using commercial EDR tools provides both the knowledge and the technical capability to detect and investigate security incidents. We discuss the architecture of the tools and advantages it offers. Specifically, in our method all the endpoint logs are collected at a common server which we leverage to perform correlation between events happening on different endpoints and automatically detect threats like pivoting and lateral movements. We discuss various attacks that can be detected by our tool.

Worldwide, societies are rapidly becoming more connected, owing primarily to the growing number of intelligent things and smart applications (e.g, smart automobiles, smart wearable devices, etc.) These have occurred in tandem with the Internet Of Things, a new method of connecting the physical and virtual worlds. It is a new promising paradigm whereby every ‘thing’ can connect to anything via the Internet. However, with IoT systems being deployed even on large-scale, security concerns arise amongst other challenges. Hence the need to allocate appropriate protection of resources. The realization of secure IoT systems could only be accomplished with a comprehensive understanding of the particular needs of a specific system. How-ever, this paradigm lacks a proper and exhaustive classification of security requirements. This paper presents an approach towards understanding and classifying the security requirements of IoT devices. This effort is expected to play a role in designing cost-efficient and purposefully secured future IoT systems. During the coming up with and the classification of the requirements, We present a variety of set-ups and define possible attacks and threats within the scope of IoT. Considering the nature of IoT and security weaknesses as manifestations of unrealized security requirements, We put together possible attacks and threats in categories, assessed the existent IoT security requirements as seen in literature, added more in accordance with the applied domain of the IoT and then classified the security requirements. An IoT system can be secure, scalable, and flexible by following the proposed security requirement classification.

In this paper we consider cyber security requirements of the smart buildings. We identify cyber risks, threats, attack scenarios, security objectives and related security controls. The work was done as a part of a smart building design and construction work. From the controls identified w e concluded security practices for engineering-in smart buildings security. The paper provides an idea toward which system security engineers can strive in the basic design and implementation of the most critical components of the smart buildings. The intent of the concept is to help practitioners to avoid ad hoc approaches in the development of security mechanisms for smart buildings with shared space.

The Time-Triggered Architecture (TTA) presents a blueprint for building safe and real-time constrained distributed systems, based on a set of orthogonal concepts that make extensive use of the availability of a globally consistent notion of time and a priori knowledge of events. Although the TTA tolerates arbitrary failures of any of its nodes by architectural means (active node replication, a membership service, and bus guardians), the design of these means considers only accidental faults. However, distributed safety- and real-time critical systems have been emerging into more open and interconnected systems, operating autonomously for prolonged times and interfacing with other possibly non-real-time systems. Therefore, the existence of vulnerabilities that adversaries may exploit to compromise system safety cannot be ruled out. In this paper, we discuss potential targeted attacks capable of bypassing TTA's fault-tolerance mechanisms and demonstrate how two well-known recovery techniques - proactive and reactive rejuvenation - can be incorporated into TTA to reduce the window of vulnerability for attacks without introducing extensive and costly changes.

Distributed computation and AI processing at the edge has been identified as an efficient solution to deliver real-time IoT services and applications compared to cloud-based paradigms. These solutions are expected to support the delay-sensitive IoT applications, autonomic decision making, and smart service creation at the edge in comparison to traditional IoT solutions. However, existing solutions have limitations concerning distributed and simultaneous resource management for AI computation and data processing at the edge; concurrent and real-time application execution; and platform-independent deployment. Hence, first, we propose a novel three-layer architecture that facilitates the above service requirements. Then we have developed a novel platform and relevant modules with integrated AI processing and edge computer paradigms considering issues related to scalability, heterogeneity, security, and interoperability of IoT services. Further, each component is designed to handle the control signals, data flows, microservice orchestration, and resource composition to match with the IoT application requirements. Finally, the effectiveness of the proposed platform is tested and have been verified.

The Enterprise Architecture and Systems Engineering communities are often faced with complexity barriers that develop due to the fact that modern systems must be agile and resilient. This requires dynamic changes to the system so as to adapt to changing missions as well as changes in the internal and external environments. The requirement is not entirely new, but practitioners need guidance on how to manage the life cycle of such systems. This is a problem because we must be able to architect systems by alleviating the difficulties in systems life cycle management (e.g., by helping the enterprise- or systems engineer organise and maintain models and architecture descriptions of the system of interest). Building on Pask’s conversation theoretic model of aware (human or machine) individuals, the paper proposes a reference model for systems that maintain their own models real time, act efficiently, and create system-level awareness on all levers of aggregation.

With the construction of power information network, the power grid has built a security protection system based on boundary protection. However, with the continuous advancement of the construction of the power Internet of Things, a large number of power Internet of Things terminals need to connect to the power information network through the public network, which have an impact on the existing security protection system of the power grid. This article analyzes the characteristics of the border protection model commonly used in network security protection. Aiming at the lack of security protection capabilities of this model, a zero-trust security architecture-based power Internet of Things network security protection model is proposed. Finally, this article analyzes and studies the application of zero trust in the power Internet of Things.

This paper discusses DDoS attacks, their current threat level and IDS systems, which are one of the main tools to protect against them. It focuses on the problems encountered by IDS systems in detecting DDoS attacks and the difficulties and challenges of integrating them with artificial intelligence systems today.

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.

Over the years, operating systems (OSs) have grown significantly in complexity and size providing attackers with more avenues to compromise their security. By eliminating the OS, it becomes possible to develop general-purpose non-embedded applications that are free of typical OS-related vulnerabilities. Such applications are simpler and smaller in size, making it easier secure the application code. Bare machine computing (BMC) applications run on ordinary desktops and laptops without the support of any operating system or centralized kernel. Many BMC applications have been developed previously for single-core systems. We show how to build BMC applications for multicore systems by presenting the design and implementation of a novel UDP-based bare machine prototype Web server for a multicore architecture. We also include preliminary experimental results from running the server on the Internet. This work provides a foundation for building secure computer applications that run on multicore systems without the need for intermediary software.

Recent advances in adversarial attacks uncover the intrinsic vulnerability of modern deep neural networks. Since then, extensive efforts have been devoted to enhancing the robustness of deep networks via specialized learning algorithms and loss functions. In this work, we take an architectural perspective and investigate the patterns of network architectures that are resilient to adversarial attacks. To obtain the large number of networks needed for this study, we adopt one-shot neural architecture search, training a large network for once and then finetuning the sub-networks sampled therefrom. The sampled architectures together with the accuracies they achieve provide a rich basis for our study. Our ''robust architecture Odyssey'' reveals several valuable observations: 1) densely connected patterns result in improved robustness; 2) under computational budget, adding convolution operations to direct connection edge is effective; 3) flow of solution procedure (FSP) matrix is a good indicator of network robustness. Based on these observations, we discover a family of robust architectures (RobNets). On various datasets, including CIFAR, SVHN, Tiny-ImageNet, and ImageNet, RobNets exhibit superior robustness performance to other widely used architectures. Notably, RobNets substantially improve the robust accuracy ( 5% absolute gains) under both white-box and black-box attacks, even with fewer parameter numbers. Code is available at https://github.com/gmh14/RobNets.

It is predicted that, the number of connected Internet of Things (IoT) devices will rise to 38.6 billion by 2025 and an estimated 50 billion by 2030. The increased deployment of IoT devices into diverse areas of our life has provided us with significant benefits such as improved quality of life and task automation. However, each time a new IoT device is deployed, new and unique security threats emerge or are introduced into the environment under which the device must operate. Instantaneous detection and mitigation of every security threat introduced by different IoT devices deployed can be very challenging. This is because many of the IoT devices are manufactured with no consideration of their security implications. In this paper therefore, we review existing literature and present IoT threat detection research advances with a focus on the various IoT security challenges as well as the current developments towards combating cyber security threats in IoT networks. However, this paper also highlights several future research directions in the IoT domain.

With a storage space limit on the sensors, WSN has some drawbacks related to bandwidth and computational skills. This limited resources would reduce the amount of data transmitted across the network. For this reason, data aggregation is considered as a new process. Iterative filtration (IF) algorithms, which provide trust assessment to the various sources from which the data aggregation has been performed, are efficient in the present data aggregation algorithms. Trust assessment is done with weights from the simple average method to aggregation, which treats attack susceptibility. Iteration filter algorithms are stronger than the ordinary average, but they do not handle the current advanced attack that takes advantage of false information with many compromise nodes. Iterative filters are strengthened by an initial confidence estimate to track new and complex attacks, improving the solidity and accuracy of the IF algorithm. The new method is mainly concerned with attacks against the clusters and not against the aggregator. In this process, if an aggregator is attacked, the current system fails, and the information is eventually transmitted to the aggregator by the cluster members. This problem can be detected when both cluster members and aggregators are being targeted. It is proposed to choose an aggregator which chooses a new aggregator according to the remaining maximum energy and distance to the base station when an aggregator attack is detected. It also save time and energy compared to the current program against the corrupted aggregator node.

Password-based authentication is the most common authentication method for either online or offline system. Password composition policies become too burdensome and put the user in a state of struggle to remember their password. Thus, most of the user save their password on the browser or even list it down in their personal gadgets. Therefore, a multi agent-based password management application have been developed to helps user in keeping their password safely. However, multi-agent system facing security issues such as man in the middle attack, data modification and eavesdropping. This paper proposed a security protocol for multi agent-based architecture in order to reduce potential threats. The security protocol focuess on the authentication of mobile agents, data transmission and the data local protection. The communication channels are secured using cryptography techniques.

ARtect is an Augmented Reality application developed with Unity 3D, which envisions an educational interactive and immersive tool for architects, designers, researchers, and artists. This digital instrument renders the competency to visualize custom-made 3D models and 2D graphics in interior and exterior environments. The user-friendly interface offers an accurate insight before the materialization of any architectural project, enabling evaluation of the design proposal. This practice could be integrated into learning architectural design process, saving resources of printed drawings, and 3D carton models during several stages of spatial conception.

A physical protection system (PPS) integrates people, procedures, and equipment for the protection of assets or facilities against theft, sabotage, or other malevolent intruder attacks. In this paper we focus on the architecture modeling of PPS to support the communication among stakeholders, analysis and guiding the systems development activities. A common practice for modeling architecture is by using an architecture framework that defines a coherent set of viewpoints. Existing systems engineering modeling approaches appear to be too general and fail to address the domain-specific aspects of PPSs. On the other hand, no dedicated architecture framework approach has been provided yet to address the specific concerns of PPS. In this paper, we present an architecture framework for PPS (PPSAF) that has been developed in a real industrial context focusing on the development of multiple PPSs. The architecture framework consists of six coherent set of viewpoints including facility viewpoint, threats and vulnerabilities viewpoint, deterrence viewpoint, detection viewpoint, delay viewpoint, and response viewpoint. We illustrate the application of the architecture framework for the design of a PPS architecture of a building.

Large enterprises and organizations from both private and public sectors typically outsource a platform solution, as part of the Managed Security Services (MSSs), from 3rd party providers (MSSPs) to monitor and analyze their data containing cyber security information. Sharing such data among these large entities is believed to improve their effectiveness and efficiency at tackling cybercrimes, via improved analytics and insights. However, MSS platform customers currently are not able or not willing to share data among themselves because of multiple reasons, including privacy and confidentiality concerns, even when they are using the same MSS platform. Therefore any proposed mechanism or technique to address such a challenge need to ensure that sharing is achieved in a secure and controlled way. In this paper, we propose a new architecture and use case driven designs to enable confidential, flexible and collaborative data sharing among such organizations using the same MSS platform. MSS platform is a complex environment where different stakeholders, including authorized MSSP personnel and customers' own users, have access to the same platform but with different types of rights and tasks. Hence we make every effort to improve the usability of the platform supporting sharing while keeping the existing rights and tasks intact. As an innovative and pioneering attempt to address the challenge of data sharing in the MSS platform, we hope to encourage further work to follow so that confidential and collaborative sharing eventually happens among MSS platform customers.

In this article, we introduce the MACH-2K trust overlay network and its architecture. MACH-2K's objectives are to (a) enhance the resiliency of emergency response and public service networks and (b) help build such networks in places, or at times, where network infrastructure is limited. Resiliency may be enhanced in an economic manner by building new ad hoc networks of private mobile devices and joining these to public service networks at specific trusted points. The major barrier to building resiliency by using private devices is ensuring security. MACH-2K uses device location and communication utility patterns to assign trust to devices, after owner approval. After trust is established, message confidentiality, privacy, and integrity may be implemented by well-known cryptographic means. MACH-2K devices may be then requested to forward or consume different types of messages depending on their current level of trust and utility.

With the advancement in technology, inclusion of Information and Communication Technology (ICT) in the conventional Electrical Power Grid has become evident. The combination of communication system with physical system makes it cyber-physical system (CPS). Though the advantages of this improvement in technology are numerous, there exist certain issues with the system. Security and privacy concerns of a CPS are a major field and research and the insight of which is content of this paper.

The rise in the number of devices joining the Internet of Things (IoT) has created a huge potential for distributed denial of service (DDoS) attacks, especially due to the lack of security in these computationally limited devices. Malicious actors have realized that and managed to turn large sets of IoT devices into botnets under their control. Given this scenario, this work studies botnet architectures identified so far and assesses how they are considered in the few recent defense proposals that consider botnet architectures.

The threats posed by botnets in the cyber-space continues to grow each day and it has become very hard to detect or infiltrate bots given that the botnet developers each day keep changing the propagation and attack techniques. Currently, most of these attacks have been centered on stealing computing energy, theft of personal information and Distributed Denial of Service (DDoS attacks). In this paper, the authors propose a novel technique that uses the Non-Deterministic Polynomial-Time Hardness (NP-Hard Problem) based on the Traveling Salesperson Person (TSP) that depicts that a given bot, bj, is able to visit each host on a network environment, NE, and then it returns to the botmaster in form of instruction(command) through optimal minimization of the hosts that are or may be attacked. Given that bj represents a piece of malicious code and based on TSP-NP Hard Problem which forms part of combinatorial optimization, the authors present an effective approach for the detection of the botnet. It is worth noting that the concentration of this study is basically on the centralized botnet architecture. This holistic approach shows that botnet detection accuracy can be increased with a degree of certainty and potentially decrease the chances of false positives. Nevertheless, a discussion on the possible applicability and implementation has also been given in this paper.

Conversational systems are computer programs that interact with users using natural language. Considering the complexity and interaction of the different components involved in building intelligent conversational systems that can perform diverse tasks, a promising approach to facilitate their development is by using multiagent systems (MAS). This paper reviews the main concepts and history of conversational systems, and introduces an architecture based on MAS. This architecture was designed to support the development of conversational systems in the domain chosen by the developer while also providing a reusable built-in dialogue control. We present a practical application in the healthcare domain. We observed that it can help developers to create conversational systems in different domains while providing a reusable and centralized dialogue control. We also present derived lessons learned that can be helpful to steer future research on engineering domain-specific conversational systems.

Cyber-Physical System (CPS) and Cloud Computing are emerging and important research fields in recent years. It is a current trend that CPS combines with Cloud Computing. Compared with traditional CPS, Cloud can improve its performance, but Cloud failures occur occasionally. The existing cloud-based CPS architectures rely too much on the Cloud, ignoring the risk and problems caused by Cloud failures, thus making the reliability of CPS not guaranteed. In order to solve the risk and problems above, spare parts are involved based on the research of cloud-based CPS. An architecture of cloud-based CPS with spare parts is proposed and two solutions for spare parts are designed. Agricultural intelligent temperature control system is used as an example to model and simulate the proposed architecture and solutions using Simulink. The simulation results prove the effectiveness of the proposed architecture and solutions, which enhance the reliability of cloud-based CPS.

Deep packet inspection via regular expression (RE) matching is a crucial task of network intrusion detection systems (IDSes), which secure Internet connection against attacks and suspicious network traffic. Monitoring high-speed computer networks (100 Gbps and faster) in a single-box solution demands that the RE matching, traditionally based on finite automata (FAs), is accelerated in hardware. In this paper, we describe a novel FPGA architecture for RE matching that is able to process network traffic beyond 100 Gbps. The key idea is to reduce the required FPGA resources by leveraging approximate nondeterministic FAs (NFAs). The NFAs are compiled into a multi-stage architecture starting with the least precise stage with a high throughput and ending with the most precise stage with a low throughput. To obtain the reduced NFAs, we propose new approximate reduction techniques that take into account the profile of the network traffic. Our experiments showed that using our approach, we were able to perform matching of large sets of REs from SNORT, a popular IDS, on unprecedented network speeds.