Recently, Pan et al. proposed the “Public-Key Authenticated Encryption with Keyword Search Achieving both Multi-Ciphertext and Multi-Trapdoor Indistinguishability” in Pan and Li (2021). However, after carefully revisiting the scheme, we found an attack on Pan et al.’s scheme. As a result, the multi-ciphertext indistinguishability of their scheme is totally broken. In addition, we also pointed out a

Sensor cloud provides a new way for the owners of different WSNs (Wireless Sensor Networks) to share their data to other parties (users/organizations). The edge-computing-assisted sensor-cloud systems (EC-assisted SCSs) can even supply real-time services for different parties. However, both the edge servers and the cloud servers in the systems are prone to be attacked in insecure network environments

In this paper, we consider simultaneously energy consumption and resource synchronization in mixed-criticality (MC) single processor systems. First, we give a feasibility analysis of single processor systems that execute real-time MC tasks. Second, an energy efficient speed based on sufficient feasibility condition is computed. In addition, we propose a single speed energy efficient algorithm for MC

Open-Channel SSD (OCSSD) shows great potential in high-performance storage systems. Existing applications or file systems rely on host-based Flash Translation Layer (FTL) to use OCSSDs. However, the existing solution cannot fully exploit the OCSSD performance under multi-thread workloads. On the read/write critical paths, we find three components (ring buffer, translation map, and DMA memory pool)

Vehicular networking allows vehicles with sensing capabilities to carry out communication from vehicle to vehicle or with accessible roadside units. To attain effective communication in vehicular networking, we have proposed a hybrid technological solution in terms of vehicular edge computing (VEC) utilizing resources, cloud and edge server environment. The proposed architecture supports a frequent

Arm TrustZone is a hardware technology that adds significant value to the ongoing security picture. TrustZone-based systems typically consolidate multiple environments into the same platform, requiring resources to be shared among them. Currently, hardware devices on TrustZone-enabled system-on-chip (SoC) solutions can only be configured as secure or non-secure, which means the dual-world concept of

Since 1973, Earliest Deadline First (EDF) uniprocessor scheduling has been known to be superior to its Rate Monotonic (Fixed-Priority, FPS) counterpart for its capacity to feasibly sustain full utilization, which FPS can only achieve in certain favorable circumstances. In 2005, further research results illustrated EDF’s superiority in a number of finer-grained performance indicators, such as preemption

With the extensive application of IoT techniques, IoT devices have become ubiquitous in daily lives. Meanwhile, attacks against IoT devices have emerged to compromise IoT devices by tampering with system pre-installed programs or injecting new malware. To mitigate these attacks, integrity enforcement of IoT systems has been proposed. The integrity of an IoT device system includes load-time integrity

Memristor-based memory computing has attracted much attention recently. By combining the storability and computability of memristor devices together, the memristor-based in-memory computing could break the so-called von Neumann bottleneck. Logic-in-memory (LIM) aims at implementing any computing task in memory. IMPLY family and MAGIC family are two of the most popular stateful logic families of LIM

This paper tackles the problem of admitting real-time tasks on non-symmetric multiprocessor platforms, where partitioned EDF-FF is used. We extend the already obtained results for symmetric multiprocessor platforms and provide an improved equation based on the number of tasks in the taskset that considers the first few heaviest tasks in the taskset. This equation has been enveloped in three effective

Sensor-cloud combines the merits of WSN with cloud computing and has been deployed in many practical applications. Data security is the prerequisite for the implementation of a sensor-cloud system, but conventional security mechanisms cannot fully satisfy the several new security demands arisen in this scenario. To address the challenge of flexible and secure data sharing, in this paper, we design

A Lightweight Verifiable Trust based Data Collection (LVT-DC) approach is proposed to obtain credible data for mobile vehicles network, in which, a large number of IoT devices are deployed in smart city, and Mobile Vehicles (MVs) collect data from IoT devices and report data to cloud to construct various applications. First, some IoT devices are selected as core-IoT device whose data more than others

With the advent of new technologies in both hardware and software, we are in the need of a new type of application that requires huge computation power and minimal delay. Applications such as face recognition, augmented reality, virtual reality, automated vehicles, industrial IoT, etc. belong to this category. Cloud computing technology is one of the candidates to satisfy the computation requirement

Recent years have witnessed a significant interest in the “generative adversarial networks” (GANs) due to their ability to generate high-fidelity data. Many models of GANs have been proposed for a diverse range of domains ranging from natural language processing to image processing. GANs have a high compute and memory requirements. Also, since they involve both convolution and deconvolution operation

Application of Ethernet-based networks in the autonomous and automated vehicles requires safe and efficient resource management policy. The network components must not only handle high volume of sensor data but also safely accommodate dynamics in system behavior, e.g. detect permanent failures, switch between different driving modes (city/highway), incorporate car-2-x communication etc. This is currently

A co-simulation may comprise several heterogeneous federates with diverse spatial and temporal execution characteristics. In an iterative time-stepped simulation, a federation exhibits the Bulk Synchronous Parallel (BSP) computation paradigm in which all federates perform local operations and synchronize with their peers before proceeding to the next round of computation. In this context, the lowest

Designed for real-time systems, the Patmos instruction-set architecture’s features ensure a high degree of predictability. One such feature is its dual-issue pipeline, which can issue and execute bundles of up to two instructions at a time. Executing instructions in the second issue slot is a predictable way to increase the throughput of a processor, but without dedicated support from the compiler

Global static scheduling for Mixed Criticality (MC) systems demonstrates excellent results in terms of acceptance ratio and number of preemptions. But, no practical implementation and empirical evaluation have been presented yet for multi-processors systems. Moreover, the new kernel mechanisms it would require have not been studied. In this paper, we present two contributions on the implementation

Cyber-physical systems need self-adaptation as a mean to autonomously deal with changes. For runtime adaptation, a cyber-physical system repeatedly monitors the environment for detecting possible changes. Faults in the monitoring devices due to the dynamic and uncertain environment is very likely, necessitating resilient monitoring. In this paper, we discuss imperfect monitoring in self-adaptive systems

Intrusion detection has been extremely important for the security of the cloud computing environment for these years. However, it is also extremely hard to prevent network systems from attacking, due to that the attacking data and normal data usually have large different density distributions, i.e, they are imbalanced. Clustering is one of the effective methods for intrusion detection. Density Peak

In hard real-time embedded systems, switching to multicores is a step that most application domains delay as much as possible. This is mainly due to the number of sources of indeterminism, which mainly involve shared hardware resources, such as buses, caches, and memories. In this paper, a new task model that considers the interference that task execution causes in other tasks running on other cores

The current dependency of Artificial Intelligence (AI) systems on Cloud computing implies higher transmission latency and bandwidth consumption. Moreover, it challenges the real-time monitoring of physical objects, e.g., the Internet of Things (IoT). Edge systems bring computing closer to end devices and support time-sensitive applications. However, Edge systems struggle with state-of-the-art Deep

This paper presents OTune, a novel overlay-based approach for rapid in-circuit debugging and tuning of Deep Neural Network (DNN) designs targeting Field-Programmable Gate Array (FPGA). We first propose overlay-based instruments that provide hardware profiling information to FPGA-based DNN developers for tuning and debugging their designs. Our instrumentation is optimized to take advantage of characteristics

Smart healthcare plays an important role in contemporary society while its security and privacy issues remain inevitable challenges. Authenticated key agreement (AKA) mechanism, as the foundation of secure communication, has been recognized as an important measure for solving this problem. Most existing AKA protocols utilize cloud-based centralized architecture, data privacy and security can be exposed

Currently, password-based remote authentication mechanism has become an essential procedure to ensure users access the resources of the cloud server securely. Dozens of password-based multi-factor authentication schemes have been successively proposed recently. Unfortunately, most of them are vulnerable to various known attacks. The key to designing a secure and privacy-preserving authentication scheme

Fault tolerance techniques are of vital importance to promise data reliability for mobile distributed system. In mobile environments, nodes suffer from high failure probability and fluctuating bandwidth. Thus, traditional fault tolerance techniques are no longer suitable. In this paper, we present a replica prioritized hybrid fault tolerance strategy combining erasure codes and replicas for a mobile

Recently, the trending 5G technology encourages extensive applications of on-device machine learning, which collects user data for model training. This requires cost-effective techniques to preserve the privacy and the security of model training within the resource-constrained environment. Traditional learning methods rely on the trust among the system for privacy and security. However, with the increase

App vendors now have a new way to deploy applications on edge servers thanks to the rise of edge cloud computing. App vendors will be able to deliver better services to users throughout this form. Compared to the traditional centralized system, the new distributed computing paradigm constructs a novel cyber–physical–social system. However, how to design a data deployment method to meet the requirement

This paper proposes a novel framework providing a declarative interface to access real-time process scheduling services available in an operating system kernel. The main idea is to let applications declare their temporal requirements or characteristics without knowing exactly which underlying scheduling algorithms are offered by the system. The proposed framework can adequately handle such a set of

Non-uniform memory access (NUMA) systems are characterized by varying memory latencies so that execution times may become unpredictable in a multicore real-time system. This results in overly conservative scheduling with low utilization due to loose bounds on a task’s worst-case execution time (WCET). This work contributes a controller/node-aware memory coloring (CAMC) allocator inside the Linux kernel

Microservices are hailed for their capabilities to tackle the challenge of breaking monolithic business systems down into small, cohesive, and loosely-coupled services. Indeed, these systems are neither easy to maintain nor to replace undermining organizations’ efforts to cope with user’s changing needs and governments’ complex regulations. Microservices constitute an architectural style for developing

The safety-critical system communities have been struggling to manage and maintain their legacy softwaresystems because upgrading such systems has been a complex challenge. To overcome or reduce this problem, reverse engineering has been increasingly used in safety-critical systems. This paper proposes C2AADL_Reverse, a model-driven reverse engineering approach for safety-critical software development

Multicore processors provide great average-case performance. However, the use of multicore processors for safety-critical applications can lead to catastrophic consequences because of contention on shared resources. The problem has been well-studied in literature, and solutions such as partitioning of shared resources have been proposed. Strict partitioning of memory resources among cores, however

Side-channel attacks are one of the security threats to the chip-level devices of the communication systems. To strengthen chip-level cryptographic devices against side-channel attacks, a current equalizer that weakens the current difference is proposed, which barely changes the original design flow and is resistant to physical teardown. This method overlays (metal-insulator-metal) MIM capacitors on

Mobile network operators are at the verge of distribution and allotment of existing mobile communications with 5G. It is a high time that we should be focused on the forthcoming sixth generation (6G) networking. Though, it is mandated that 6G would leverage best of the existing network functions and cover an extended geographical range, we need to first understand the importance of 6G. In this article

Pattern recognition applications such as face recognition and agricultural product detection have drawn a rapid interest on Cyber–Physical–Social-Systems (CPSS). These CPSS applications rely on the deep neural networks (DNN) to conduct the image classification. However, traditional DNN inference models in the cloud could suffer from network delay fluctuations and privacy leakage problems. In this regard

Mobile edge computing (MEC) is a promising paradigm, which brings computation resources in proximity to mobile devices and allows the tasks of mobile devices to be offloaded to MEC servers with low latency. The joint problem of cooperative computation task offloading and resource allocation is a challenging issue. The joint problem of cooperative computation task offloading scheme and resource assignment

The lattice cryptosystem is considered to be able to resist the attacks of quantum computers. Lattice-based Public Key Encryption (PKE) schemes have attracted the interest of many researchers. In lattice-based cryptography, Learning With Errors (LWE) problem is a hard problem usually used to construct PKE scheme. To ensure the correctness of decryption, LWE-based schemes have a large ciphertext size

Dynamic Binary Instrumentation (DBI) is one way to monitor a distributed system in real-time without modifying application source code. Previous work has shown it is possible to instrument distributed systems using standards-based distributed middleware. Existing work, however, only applies to a single middleware, such as CORBA. This article therefore presents a tool named the Standards-based Distributed

Over the last years, deep neural networks (DNNs) are becoming more powerful and have risen in popularity, especially in mobile computing. Applications running on edge AI devices such as smartphones would potentially benefit from the new opportunities enabled by deep learning techniques. However, DNNs are by nature computationally and memory intensive, making them challenging to deploy on mobile devices

As “deep neural networks” (DNNs) achieve increasing accuracy, they are getting employed in increasingly diverse applications, including security-critical applications such as medical and defense. This immense use of DNNs has motivated the researchers to scrutinizingly study their security vulnerability and propose countermeasures, especially in the context of hardware security. In this paper, we present

As an indispensable part of intelligent transportation systems, Internet of Vehicles (IoV) has been widely used in improving the driving experience and road conditions. In the communication of IoV, the security of transmitted messages is critical. Specifically, the messages should be signed and verified before they are accepted by vehicles or road side units. To ensure the privacy of vehicle users

Improper timing has severe safety repercussions in modern vehicles due to the use of mixed-criticality systems. Human lives and increased material costs might be at stake due to faulty configuration or incorrect startup of the timing subsystem. TTEthernet is a communication infrastructure that enables combined use of distributed applications with mixed-criticality requirements over a single physical

“Unmanned aerial vehicles” (UAVs) are now being used for a wide range of surveillance applications. Specifically, the detection of on-ground vehicles from UAV images has attracted significant attention due to its potential in applications such as traffic management, parking lot management, and facilitating rescue operations in disaster zones and rugged terrains. This paper presents a survey of deep

Weakly-hard real-time scheduling enables to tolerate certain execution timeouts of tasks, and has been widely exploited in those intelligent embedded systems over the past two decades. In general, the current weakly-hard real-time scheduling algorithms try to rapidly raise the priorities of jobs (instances) of those tasks that have missed deadlines to guarantee their individual weakly-hard constraints

Applications run in embedded systems should usually be completed within the constrained time to reduce energy consumption. Therefore, the memory of embedded system should satisfy time-efficient and energy-efficient. Domain Wall Memory (DWM) achieves high energy efficiency, high density, non-volatile and low cost advantages. However, the data access on DWM always requires shift operations to align the

The existing privacy-preserving authentication models for Vehicular Ad-hoc Networks (VANETs) primarily preserve multiple pseudonyms for one vehicle, while overlooking the consideration of confidential identity requirements. These authentication models cause pseudonyms management complex and revocation inconvenient. Blockchain seems to be suitable for storing the pseudonym certificates as transactions

Liquid state machine(LSM) is an attractive spiking neural network (SNN) for Network-on-Chip(NoC)-based neuromorphic platforms due to their biological characteristics and hardware efficiency. But the randomly connected topology of the liquid in LSM and lots of communication spike bring different dataflow and communication congestion on the NoC-based platform. Aiming to design an accurate and communication

With the wide use of multiprocessor architecture, parallel tasks have been receiving growing attention in both industry and academia. In real-time systems, the scheduling and synchronization that ensure predictable task execution and resource access are of utmost importance. Although the scheduling of (independent) parallel tasks is widely studied in recent years, few works have been done for the synchronization

The past decade has seen a rapidly growing interest in IoT-connected devices. But as is usually the case with computer systems and networks, malicious individuals soon realized that these objects could be exploited for criminal purposes. The problem is particularly salient since the firmware used in many Internet connected devices was developed without taking into consideration the expertise and best

Virtualized data centers usually consist of heterogeneous servers which have different specifications (performance). Though there usually exist unused heterogeneous servers in such data centers, conventional DVFS (Dynamic Voltage and Frequency Scaling)-based DTM (Dynamic Thermal Management) techniques do not exploit the unused servers to cool down hot servers. In this paper, we propose a novel DTM

The functionality advancements and novel customer features that are currently found in modern automotive systems require high-bandwidth and low-latency in-vehicle communications, which become even more compelling for autonomous vehicles. In a recent effort to meet these requirements, the IEEE Time-Sensitive Networking (TSN) task group has developed a set of standards that introduce novel features in

Time sensitive networks (TSNs) enable deterministic real-time communication over Ethernet networks. According to IEEE 802.1Qbv standards, TSN switches use gates between queues and their corresponding egress ports to facilitate timing-deterministic communications. Management of switch resources, such as queues, has a significant impact on the schedulability of real-time flows. In this paper, we look

There is a need for reliable and efficient methods for monitoring the activity and social behaviour in cows, in order to optimise management in modern dairy farms. This research presents an embedded system that could track individual cows using Ultra-wideband technology. At the same time, social interactions between individuals around the feeding area are analysed with a computer vision module. Detections

To allow more accurate and efficient browsing performance, existing works showed that visual landmarks (e.g.3D pins) can facilitate spatial learning and recalling of browsing performance in Virtual Reality (VR). Compared with visual cues, the additional auditory cue is well known to provide benefits of navigational performance in virtual environments. However, less is known about the effects of such

The emergence of mobile edge computing provides an efficient and stable computing platform for intelligent applications of autonomous vehicles, and deep neural network (DNN) based tasks collaborative inference through joint device-edge is considered an effective way to reduce latency. However, the computing resources allocated to the vehicle are dynamic as the number of requesters changes due to the

Mixed-criticality embedded systems, as the next-generation of safety-critical systems, are increasingly employed in the industry due to consolidating functionalities with varying criticality levels onto the same computing platform. Technology scaling, battery-supplied design, and heavy computation in mixed-criticality systems necessitate employing energy management techniques. Due to the degrading

Motion estimation (ME) is a high efficiency video coding (HEVC) process for determining motion vectors that describe the blocks transformation direction from one adjacent frame to a future frame in a video sequence. ME is a memory and computation consuming process which accounts for more than 50% of the total running time of HEVC. To conquer the memory and computation challenges, this paper presents

Mixed-criticality system is an emerging design paradigm to improve the resource-efficiency for real-time embedded system. However, the traditional mixed-criticality system is commonly designed under pessimistic constraints on overrun handling and slack utilization. These solutions cannot provide efficient resource utilization when considering the dynamic behaviors of MC system. In this paper, we present