Message Arrivals Research Articles

DGIDS: Dynamic graph-based intrusion detection system for CAN

The Controller Area Network (CAN) is widely used in automobiles to interconnect safety-critical electronic control units (ECUs). Unfortunately, CAN does not have inherent security mechanisms as originally designed, which has drawn significant attention from the research community. Currently, the mainstream CAN protection strategy is the Intrusion Detection System (IDS). However, many statistics-based IDSs are unable to identify the identifier (ID) of the attacked message; they can only identify anomalies within a specific time window. Moreover, these systems are often tested solely on public datasets, lacking theoretical validation of their effectiveness. To address these shortcomings, we propose a real-time intrusion detection system based on a dynamic graph. The graph is dynamically constructed based on the arrival of messages, and features are extracted concurrently. By utilizing the distribution of features extracted during the offline phase, our system achieves real-time detection of incoming messages and identifies the ID of the attacked message. Additionally, we introduce a method to theoretically validate the detection system through permutation and probabilistic statistical analysis. Experiments and theoretical analysis demonstrate that our proposed IDS can effectively detect a wide range of attacks with reduced detection time and memory usage.

Analysis of False Negative Rates for Recycling Bloom Filters (Yes, They Happen!)

Bloom Filters are a desirable data structure for distinguishing new values in sequences of data (i.e., messages), due to their space efficiency, their low false positive rates (incorrectly classifying a new value as a repeat), and never producing false negatives (classifying a repeat value as new). However, as the Bloom Filter's bits are filled, false positive rates creep upward. To keep false positive rates below a reasonable threshold, applications periodically "recycle" the Bloom Filter, clearing the memory and then resuming the tracking of data. After a recycle point, subsequent arrivals of recycled messages are likely to be misclassified as new; recycling induces false negatives. Despite numerous applications of recycling, the corresponding false negative rates have never been analyzed. In this paper, we derive approximations, upper bounds, and lower bounds of false negative rates for several variants of recycling Bloom Filters. These approximations and bounds are functions of the size of memory used to store the Bloom Filter and the distributions on new arrivals and repeat messages, and can be efficiently computed on conventional hardware. We show, via comparison to simulation, that our upper bounds and approximations are extremely tight, and can be efficiently computed for megabyte-sized Bloom Filters on conventional hardware.

Analysis of False Negative Rates for Recycling Bloom Filters (Yes, They Happen!)

Bloom Filters are a desirable data structure for distinguishing new values in sequences of data (i.e., messages), due to their space efficiency, their low false positive rates (incorrectly classifying a new value as a repeat), and never producing false negatives (classifying a repeat value as new). However, as the Bloom Filter's bits are filled, false positive rates creep upward. To keep false positive rates below a reasonable threshold, applications periodically "recycle" the Bloom Filter, clearing the memory and then resuming the tracking of data. After a recycle point, subsequent arrivals of recycled messages are likely to be misclassified as new; recycling induces false negatives. Despite numerous applications of recycling, the corresponding false negative rates have never been analyzed. In this paper, we derive approximations, upper bounds, and lower bounds of false negative rates for several variants of recycling Bloom Filters. These approximations and bounds are functions of the size of memory used to store the Bloom Filter and the distributions on new arrivals and repeat messages, and can be efficiently computed on conventional hardware. We show, via comparison to simulation, that our upper bounds and approximations are extremely tight, and can be efficiently computed for megabyte-sized Bloom Filters on conventional hardware.

A Markovian Analysis of an IEEE-802.11 Station with Buffering

The purpose of this paper is to analyze the so-called backoff tech- nique of the IEEE 802.11 protocol with buffers. This protocol rules the trans- missions on a radio channel between nodes (or stations) of a network exchanging packets of information. In contrast to existing models, packets arriving at a sta- tion which in the backoff state are not discarded, but are stored in a buffer of in nite capacity. The backoff state corresponds to the number of time-intervals (mini-slot) that a node must wait before its packet is actually transmitted. As in previous studies, the key point of our analysis hinges on the assumption that the time on the radio channel is viewed as a random succession of trans- mission slots (whose duration corresponds to a packet transmission time) and mini-slots, which stand for the time intervals during which the backoff of the station is decremented. During these mini-slots the channel is idle, which im- plies that there is no packet transmission. These events occur independently with given probabilities, and the external arrivals of messages follow a Pois- son process. The state of a node is represented by a three-dimensional Markov chain in discrete-time, formed by the triple (backoff counter, number of packets at the station, number of transmission attempts). Stability (ergodicity) condi- tions are obtained for an arbitrary station and interpreted in terms of maximum throughput. Several approximations related to these models are also discussed.

Accelerating Tip Selection in Burst Message Arrivals for DAG-Based Blockchain Systems

Accelerating Tip Selection in Burst Message Arrivals for DAG-Based Blockchain Systems

Average delay analysis of soft deadline messages scheduled in the dynamic segment of FlexRay protocol

The FlexRay communication protocol provides high bandwidth for supporting both hard deadline and soft deadline traffic in in-vehicle communication networks. In this paper, we carry out delay analysis of soft deadline traffic which is handled by the dynamic segment of FlexRay. We model the arrival of these messages as Poisson processes, and use queuing theory to evaluate the average delay that they experience. Initially, we consider three nodes competing for service, assuming that two out of three can transmit messages in any FlexRay cycle and obtain expressions for the evolution of the corresponding queues. We also determine the range of message arrival rates for which the queues are stable. These results are then extended to the general case of N queues. The analytical results are compared with those obtained by simulation for a typical system.

A CFO-Assisted Algorithm for Wireless Time-Difference-of-Arrival Localization Networks: Analytical Study and Experimental Results

Localization of wireless transmitters is traditionally done using Radio Frequency (RF) sensors that measure the propagation delays between the transmitter and a set of anchor receivers. One of the major challenges of wireless localization systems is the need for anchor nodes to be time-synchronized to achieve accurate localization of a target node. Using a reference transmitter is an efficient way to synchronize the anchor nodes Over-The-Air (OTA), but such algorithms require multiple periodic messages to achieve tight synchronization. In this paper, we propose a new synchronization method that only requires a single message from a reference transmitter. The main idea is to use the Carrier Frequency Offset (CFO) from the reference node, alongside the Time of Arrival (ToA) of the reference node messages, to achieve tight synchronization. The ToA allows the anchor nodes to compensate for their absolute time offset, and the CFO allows the anchor nodes to compensate for their local oscillator drift. Additionally, using the CFO of the messages sent by the reference nodes and the target nodes also allow us to estimate the speed of the targets. The error of the proposed algorithm is derived analytically and is validated through controlled laboratory experiments. Finally, the algorithm is validated by realistic outdoor vehicular measurements with a software-defined radio testbed.

Characterizing optimal LPWAN access delay in massive multi-RAT smart grid deployments

Massive machine-type communications services penetrating the market, such as smart grids, differ from conventional services characterized by stochastic arrival patterns. Requiring permanent end device (ED) connectivity, control centers poll EDs over regular time intervals, leading to batch message arrivals that affect the mean access delay at the air interface. In addition, the smart grid requires high reliability and network availability that can be achieved by utilizing multiple radio access technologies in EDs. Radio access technologies (RATs), i.e., narrowband internet of things (NB-IoT) and long-term evolution machine type communication (LTE-M), have been identified as promising solutions for these use-cases. This work first reports results of an extensive performance evaluation measurement campaign showing that LTE-M can be considered a preferred option and NB-IoT as a possible backup solution for smart grids. We also show that none of the selected technologies can fully meet the requirements of smart grid use cases. We then develop a theoretical model and corresponding association algorithm for balancing traffic load between two low-power wide area network (LPWAN) technologies to minimize the mean access delay. Our results demonstrate that the optimized usage of multi-RAT EDs considerably increases the number of supported EDs operating in polling-based mode. For 500EDs utilizing a single LTE-M technology, the mean access delay is over two seconds — contradicting the minimum requirements of smart grid applications. On the other hand, multi-RAT EDs running the developed algorithm increase the service capacity by up to six times (up to 3000EDs) while still satisfying the two-second latency budget.

IoTMapper: A Metrics Aggregation System Architecture in Support of Smart City Solutions.

Smart cities are, nowadays, an unavoidable and growing reality, supported on software platforms that support city management, through the processing and presentation of a large number of data, obtained from sensors used throughout the cities. Low-power wide area networks (LPWAN) leverage the sensorization process; however, urban landscape, in turn, induces a high probability of change in the propagation conditions of the LPWAN network, thus requiring active monitoring solutions for assessing the city LPWAN network condition. Currently existing solutions usually consider the existence of only one type of LPWAN network to be monitored. In this paper, an architecture for aggregation of metrics from heterogeneous LPWAN networks is presented. The architecture, named IoTMapper, combines purpose build components with existing components from the FIWARE and Apache Kafka ecosystems. Implementation details for the LPWAN networks are abstracted by adapters so that new networks may be easily added. The validation was carried out using real data collected for long-range wide-area network (LoRaWAN) in Lisbon, and a simulated data set extrapolated from the collected data. The results indicate that the presented architecture is a viable solution for metrics aggregation that may be expanded to support multiple networks. However, some of the considered FIWARE components present performance bottlenecks that may hinder the scaling of the architecture while processing new message arrivals.

PERANCANGAN APLIKASI PENGADUAN MASYARAKAT DESA BEBER BERBASIS ANDROID

Until now, the Beber Village Government, community complaints still have to go to the village office, Kadus houses or BPD. Complaints like that, of course, will take a little time and take a little longer. Data on public complaints is not stored as evaluation Material for evaluation and preparation of the RKPDes. Information submitted from the village government took a long time to reach the community. Although basically now there is a name WhatsApp, the public can also send WhatsApp messages by sending evidence of events and others. However, the complaint message will not be stored in its entirety, even a few days after the message arrives, it's easy to be crushed by other messages, making it difficult to find it again. In connection with the problems above, the researchers tried to design an application entitled Beber Village Community Complaints. In designing this application, the author uses the SDLC Waterfall model method, which is carried out step by step in accordance with the procedures in the Waterfall method. The admin application is built using the Codeigniter Framework version 3 with the PHP programming language. While the client/user uses Android which is built with the Flutter Framework which uses the Dart programming language. The resulting application is in the form of a Client Server. Adam uses the WEB Service view while the client/user uses the Android version. This application will exchange information between the community and the village and between the village and the community. This application aims to make it easier for both the community and the village in exchanging information, which then the information data can be stored intact in the database

A Study of Message Arrival Timestamps on Controller Area Networks

A Study of Message Arrival Timestamps on Controller Area Networks

On the Stability Region of Intermittent Interference Networks

Recent information-theoretic studies have resulted in several interference management (IM) techniques that promise significant capacity improvements over interference avoidance techniques. However, in practice, the stable throughput region is a more relevant metric compared to the capacity region. In this work, we focus on the stable throughput region of a two-pair intermittent interference network with distributed transmitters and propose a queue-based transmission protocol in different regimes to handle the data between queues. In this context, we translate physical-layer IM protocols to accommodate stochastic message arrivals. To evaluate our proposed techniques, we compare the stable throughput region to the capacity region and show, through simulations, that the stable throughput region matches the capacity region when the latter is known. We show that in order to achieve the optimal stable throughput region, new ingredients are needed when compared to prior results. We quantify the trade-off between encoding/decoding complexity of the proposed scheme (in terms of number of required algebraic operations), and the achievable rates. Finally, we study the lifetime of messages (i.e. the duration from arrival to successful delivery) versus the total communication time, and we observe that the average lifetime scales as the square root of the total communication time.

ADS-B Crowd-Sensor Network and Two-Step Kalman Filter for GNSS and ADS-B Cyber-Attack Detection.

Automatic Dependent Surveillance-Broadcast is an Air Traffic Control system in which aircraft transmit their own information (identity, position, velocity, etc.) to ground sensors for surveillance purposes. This system has many advantages compared to the classical surveillance radars: easy and low-cost implementation, high accuracy of data, and low renewal time, but also limitations: dependency on the Global Navigation Satellite System, a simple unencrypted and unauthenticated protocol. For these reasons, the system is exposed to attacks like jamming/spoofing of the on-board GNSS receiver or false ADS-B messages’ injection. After a mathematical model derivation of different types of attacks, we propose the use of a crowd sensor network capable of estimating the Time Difference Of Arrival of the ADS-B messages together with a two-step Kalman filter to detect these attacks (on-board GNSS/ADS-B tampering, false ADS-B message injection, GNSS Spoofing/Jamming). Tests with real data and simulations showed that the algorithm can detect all these attacks with a very high probability of detection and low probability of false alarm.

Cooperative Localization for Multiple Soccer Agents Using Factor Graphs and Sequential Monte Carlo

This paper addresses the cooperative localization problem for a multiagent system in the framework of belief propagation. In particular, we consider the RoboCup 3D Soccer Simulation scenario, in which the networked agents are able to obtain simulated measurements of the distance and bearing to both known landmarks and teammates as well as the direction of arrival (DOA) of messages received from allies around the field. There are, however, severe communication restrictions between the agents, which limit the size and periodicity of the information that can be exchanged between them. We factorize the joint probability density function of the state of the robots conditioned on all measurements in the network in order to derive the corresponding factor graph representation of the cooperative localization problem. Then we apply the sum-product-algorithm (SPA) and introduce suitable implementations thereof using hybrid Gaussian-Mixture Model (GMM) / Sequential Monte Carlo (SMC) representations of the individual messages that are passed at each network location. Simulated results show that the cooperative estimates for position and orientation converge faster and present smaller errors when compared to the non-cooperative estimates in situations where agents do not observe landmarks for a long period.

Proactive Fault Tolerance using Heartbeat Strategy for Fault Detection

Failure is something which causes services on the cloud to go down for some time period. Most of the times instead of recovery and repair, we opt for virtual machine migration where failover of the failed service is done on some other running virtual server so that the service is revived. Virtual migrations and recovery mechanisms consume a lot of energy and many approaches are implemented to make them energy efficient. Failure Detection is a topic of equal importance and comes under fault tolerance. Failure detection if done properly can be more effective and energy/cost saving than fault recovery. Heartbeat strategy is one such failure detection approach where live processes send an “I am alive” message to the host device at some pre-defined fixed intervals which ensures that the process is running fine. In this paper, we propose to mark the nodes whose processes have failed to send the heartbeat message and prepare a count (confidence factor, α) for the same. In primary testing, if this confidence factor reaches a specific threshold then that particular node is sent for confidence testing (second level failure detection testing using a different time sequence of heartbeat message arrival) and later marked for failure recovery (if found faulty). Fault recovery techniques are then applied to it so that it can be corrected and reused and the current jobs can be migrated to the better node during the recovery period. If the confidence factor, α is below the threshold value then no action is taken and only network parameters and connections can be rechecked. This method will re-ensure the trust on heartbeat strategy for fault detection and save the device from failure.

Proactive Fault Tolerance using Heartbeat Strategy for Fault Detection

Failure is something which causes services on the cloud to go down for some time period. Most of the times instead of recovery and repair, we opt for virtual machine migration where failover of the failed service is done on some other running virtual server so that the service is revived. Virtual migrations and recovery mechanisms consume a lot of energy and many approaches are implemented to make them energy efficient. Failure Detection is a topic of equal importance and comes under fault tolerance. Failure detection if done properly can be more effective and energy/cost saving than fault recovery. Heartbeat strategy is one such failure detection approach where live processes send an “I am alive” message to the host device at some pre-defined fixed intervals which ensures that the process is running fine. In this paper, we propose to mark the nodes whose processes have failed to send the heartbeat message and prepare a count (confidence factor, α) for the same. In primary testing, if this confidence factor reaches a specific threshold then that particular node is sent for confidence testing (second level failure detection testing using a different time sequence of heartbeat message arrival) and later marked for failure recovery (if found faulty). Fault recovery techniques are then applied to it so that it can be corrected and reused and the current jobs can be migrated to the better node during the recovery period. If the confidence factor, α is below the threshold value then no action is taken and only network parameters and connections can be rechecked. This method will re-ensure the trust on heartbeat strategy for fault detection and save the device from failure.

ADS-B Anomalies and Intrusions Detection by Sensor Clocks Tracking

Automatic dependent surveillance-broadcast (ADS-B) is an air traffic control system in which aircraft transmit their own information (identity, position, velocity etc.) to ground sensors for surveillance scope. The tracking of the different sensors’ clocks by the use of time difference of arrival of ADS-B messages is proposed to check the veracity of the position information contained in the ADS-B messages. The method allows detecting possible on-board anomalies or the malicious injection of fake messages (intrusion) without the use of the multilateration (or any other) location algorithm. It follows that it does not need the inversion of the location problem (usually strong nonlinear and ill-posed), and, contrary to the multilateration, it works also with less than four sensors.

WhatsApp messaging improves communication in an oral and maxillofacial surgery team

ObjectiveSmartphones have become very popular among oral and maxillofacial surgeons. WhatsApp is an application that enables users to send voice, text, and multimedia messages using the group communication feature. The purpose of this study was to evaluate the efficiency of WhatsApp messaging as a mode of consultation within an oral and maxillofacial surgery team. Materials and methodsA retrospective study on WhatsApp group conversations amongst oral and maxillofacial surgeons was performed between July 2015 and July 2016. A WhatsApp group consisting of senior and junior surgeons was created, and many consultations were recorded. Seven hundred fifty-six consultations were included in the study. In this study, the arrival and response times of messages, types of cases, timing of consultation’s end, consultant locations, contents of multimedia messages, and the categories/types of messages were evaluated. During consultations, some cases were discussed with text messages via WhatsApp, and some cases with voice and image messages via WhatsApp, with or without WhatsApp text messages. In addition, several cases were discussed with video messages via WhatsApp. Thus, a total of 1747 messages reflecting four different message types were included in this study: 754 (43%) were text messages, 752 (43%) were photographic images, 213 (12%) were videos, and 28 (nearly 2%) were voice messages. ResultsThe most frequent consultations concerned impacted teeth (n = 363, 48.01%). Most consultations were resolved using WhatsApp (n = 306, 64.4%), and consultants were often not in the hospital during these consultations (n = 411, 54.3%). Most messages sent by consultants were conclusive (n = 306, 74.4%). ConclusionWe conclude that WhatsApp is a simple, free, and practical application, which allows efficient consultation when consultants are not in the hospital.

Performance and energy aware robust specification of control execution patterns under dropped samples

Embedded control systems are prevalent in a multitude of domains such as automotive, avionics, industrial control etc. For such systems, robustness against non-idealities of the compute platform created by situations such as hardware level transient faults (memory errors, sensor reading errors), network packet drops, late arrival of messages etc., is needed to be ensured at the design level. In traditional regular periodic execution of control loops, such guarantees are obtained by oversampling the plant, which requires extra rounds of sensing, control law computation, and actuation. One possible measure for reducing such over-provisioning of computing and communication resources is allowing occasional drops in the execution leading to better resource management as well as energy efficiency. This work showcases a methodology for deriving window-based bounds on possible drops in control loop executions while assuring formal performance guarantees even in the presence of platform-level non-idealities. Derivation of such relaxation bounds in terms of control loop executions help in deciding energy efficient scheduling solutions for low-power resource-constrained embedded control platforms while retaining control performance. The present work provides a structured methodology for deriving performance-aware control execution patterns given an energy-budget and uncertainty specification of the platform executing a set of embedded control loops.

An Efficient Message Forwarding Scheme with Epidemic Routing Considering the Number of Stopover Nodes in Delay Tolerant Network Environment

This paper proposes an efficient message transmission method by direct short-range communications with mobile terminals based on epidemic routing. In a previous study, when a message packet arrives at its destination node, it floods the network with packets called “anti-packets,” and deletes packets with the same message in an effort to enhance the efficiency of the buffer memories of the other terminals. Because anti-packets are not issued until the message arrives at its destination, there is not an efficient termination process. In this paper, the timing to issue anti-packets is accelerated by observing the number of nodes that a message packets has gone through, allowing wasted message packets to be eliminated earlier. Computer simulations show that the proposed method improves the messagearrival rate and reduces the average time required for message arrival.