A multi-agent architecture for supporting distributed normality-based intelligent surveillance

Intelligent surveillance involves the use of AI techniques to monitor environments whose analysis is becoming more and more complex because of the large number of sensors used and the need of monitoring multiple events of interest simultaneously. Most of the current surveillance systems provide solutions for particular problems but still suffer from lack of flexibility and scalability when they are used on different or related surveillance problems. To overcome this limitation, two aspects should be addressed: a knowledge-based surveillance model flexible enough to deal with different events of interest and an architecture that gives support to this model when deploying the surveillance system within a particular scenario. This paper discusses the architecture devised to deploy intelligent surveillance systems by means of a set of autonomous agents that are responsible for the management of different surveillance tasks and for cooperating to monitor complex environments. This multi-agent architecture is inspired by a normality-based formal model used to define the knowledge needed to analyze general-purpose surveillance concepts. We use the architecture to deploy a surveillance system to monitor an urban traffic scenario.     

The robustness of stability under link and node failures

In the area of communication systems, stability refers to the property of keeping the amount of traffic in the system always bounded over time. Different communication system models have been proposed in order to capture the unpredictable behavior of some users and applications. Among those proposed models the adversarial queueing theory (aqt) model turned out to be the most adequate to analyze an unpredictable network. Until now, most of the research done in this field did not consider the possibility of the adversary producing failures on the network structure. The adversarial models proposed in this work incorporate the possibility of dealing with node and link failures provoked by the adversary. Such failures produce temporal disruptions of the connectivity of the system and increase the collisions of packets in the intermediate hosts of the network, and thus the average traffic load. Under such a scenario, the network is required to be equipped with some mechanism for dealing with those collisions.In addition to proposing adversarial models for faulty systems we study the relation between the robustness of the stability of the system and the management of the queues affected by the failures. When the adversary produces link or node failures the queues associated to the corresponding links can be affected in many different ways depending on whether they can receive or serve packets, or rather that they cannot. In most of the cases, protocols and networks containing very simple topologies, which were known to be universally stable in the aqt model, turn out to be unstable under some of the newly proposed adversarial models. This shows that universal stability of networks is not a robust property in the presence of failures.     

Multi‐agent system for knowledge‐based event recognition and composition

This work presents a multi‐agent system for knowledge‐based high‐level event composition, which interprets activities, behaviour and situations semantically in a scenario with multi‐sensory monitoring. A perception agent (plurisensory agent and visual agent)‐based structure is presented. The agents process the sensor information and identify (agent decision system) significant changes in the monitored signals, which they send as simple events to the composition agent that searches for and identifies pre‐defined patterns as higher‐level semantic composed events. The structure has a methodology and a set of tools that facilitate its development and application to different fields without having to start from scratch. This creates an environment to develop knowledge‐based systems generally for event composition. The application task of our work is surveillance, and event composition/inference examples are shown which characterize an alarming situation in the scene and resolve identification and tracking problems of people in the scenario being monitored.     

Symmetry of ignorance, social creativity, and meta-design

Complex design problems require more knowledge than any one single person can possess, and the knowledge relevant to a problem is often distributed and controversial. Rather than being a limiting factor, “symmetry of ignorance” can provide the foundation for social creativity. Bringing different points of view together and trying to create a shared understanding among all stakeholders can lead to new insights, new ideas, and new artifacts. Social creativity can be supported by new media that allow owners of problems to contribute to framing and solving these problems. These new media need to be designed from a meta-design perspective by creating environments in which stakeholders can act as designers and be more than consumers.     

Adversarial queuing theory with setups

We look at routing and scheduling problems on Kelly type networks where the injection process is under the control of an adversary. The novelty of the model we consider is that the adversary injects requests of distinct types. Resources are subject to switch-over delays or setups when they begin servicing a new request class. In this new setting, we study the behavior of sensible policies as introduced by Dai and Jennings [J. Dai, O. Jennings, Stabilizing queueing networks with setups, Math. Oper. Res. (2004) 891–922].We first show that the model is robust in the sense that under some mild conditions universal stability of work conserving packet routing protocols is preserved for natural variants of the underlying model. Also, the model’s equivalence to so called token networks is established.We adapt to the multi-type request and setup setting, standard arguments for proving stability. Nevertheless, we provide counterexamples that show that for several reasonable adaptations of contention resolution protocols to the multi-type case, stability results do not carry over from the single-type scenario. This motivates us to explore fluid model based arguments that could be used for proving stability for a given network. Specifically we show analogues of results obtained by Gamarnik [D. Gamarnik, Stability of adversarial queues via fluid model, in: Proc. of the 39th Annual Symposium on Foundations of Computer Science, 1998, pp. 60–70] but in the multi-type request with setups scenario.     

Information systems theory

The overview presented covers a wide spectrum of aspects on information systems. Consequently, we had to be very brief and for detailed definitions and discussions we must refer the interested reader to the underlying literature. We have described how information systems present complex problems to their designers and we argued that it is hardly possible for any one individual to acquire (and continuously update) sufficient skill over the whole spectrum of problems. It is shown how the partitioning of the design task into two major areas, the infological or behavioral area on the one hand and the datalogical and computer technology oriented area on the other hand, makes it possible to combine the skills of two (or more) groups of people. In addition, the users are to be directly involved in the (infological part of) design. Development in the “infological area”, as surveyed in the paper, has brought us to the situation where it is possible to apply a documentation technique that is computer independent and intelligible to the lay users in its infological parts and yet is precise enough to the data and program design stage. Actual research problems in the infological area are associated with how one could develop the understanding and the motivation of the users so that they can better exploit the possibility to control the design process that is now offered to them. Such research is not covered by the paper. Development in the “datalogical area”, as presented has increased the possibilities for using computers as aid to the designers and to base the design on more system-wide information. A research field which is presently of high interest, but not presented in the paper, is the development of more formalized methods for handling the interface between the infological and the datalogical design stages. Such research is presently making promising progress in combining recent results from “structured programming” and ”structured information analysis”.     

A lightweight secure mobile Payment protocol for vehicular ad-hoc networks (VANETs)

In the last few years, many value-added applications (such as Payment services) in Vehicular Ad hoc NETworks (VANETs) have emerged. Although these applications offer great business opportunities they also introduce new concerns regarding security and privacy. Moreover, the wide range of scenarios (with or without connectivity restrictions) arising from vehicle-to-vehicle and vehicle-to-roadside communications have opened up new security challenges which must be considered by Payment system designers to achieve the same security capabilities independent of the scenario where Payment occurs. We designed and implemented a lightweight (using symmetric-key operations which requires low computational power) secure Payment protocol for those scenarios in VANETs and other mobile environments where the Merchant cannot communicate directly with the Acquirer (the Merchant’s financial institution) to process the Payment Request. We also present practical performance results that can be achieved with the proposed Payment protocol.     

Performance analysis for automated gait extraction and recognition in multi-camera surveillance

Many studies have confirmed that gait analysis can be used as a new biometrics. In this research, gait analysis is deployed for people identification in multi-camera surveillance scenarios. We present a new method for viewpoint independent markerless gait analysis that does not require camera calibration and works with a wide range of walking directions. These properties make the proposed method particularly suitable for gait identification in real surveillance scenarios where people and their behaviour need to be tracked across a set of cameras. Tests on 300 synthetic and real video sequences, with subjects walking freely along different walking directions, have been performed. Since the choice of the cameras’ characteristics is a key-point for the development of a smart surveillance system, the performance of the proposed approach is measured with respect to different video properties: spatial resolution, frame-rate, data compression and image quality. The obtained results show that markerless gait analysis can be achieved without any knowledge of camera’s position and subject’s pose. The extracted gait parameters allow recognition of people walking from different views with a mean recognition rate of 92.2% and confirm that gait can be effectively used for subjects’ identification in a multi-camera surveillance scenario.     

Scenario-based query processing for video-surveillance archives

Automated video surveillance has emerged as a trendy application domain in recent years, and accessing the semantic content of surveillance video has become a challenging research area. The results of a considerable amount of research dealing with automated access to video surveillance have appeared in the literature; however, significant semantic gaps in event models and content-based access to surveillance video remain. In this paper, we propose a scenario-based query-processing system for video surveillance archives. In our system, a scenario is specified as a sequence of event predicates that can be enriched with object-based low-level features and directional predicates. We introduce an inverted tracking scheme, which effectively tracks the moving objects and enables view-based addressing of the scene. Our query-processing system also supports inverse querying and view-based querying, for after-the-fact activity analysis. We propose a specific surveillance query language to express the supported query types in a scenario-based manner. We also present a visual query-specification interface devised to facilitate the query-specification process. We have conducted performance experiments to show that our query-processing technique has a high expressive power and satisfactory retrieval accuracy in video surveillance.     

Interaction Unit Analysis: A New Interaction Design Framework

ABSTRACT

A pragmatic approach to interaction modeling is presented by which a designer can describe how the user gets tasks done with a newly developing system. The notation proposed allows an interaction designer to make explicit both how user actions cause visible or noticeable changes in the state of the machine and how the user is expected to use this feedback to generate the next action. Interaction Unit (IU) scenarios are constructed where each IU specifies one step in the cycle of interaction. Each IU specifies the visible system state that leads the user to take some action. In addition, the IU makes explicit the state of the goal stack at the start and end of the unit and the mental processes (recall, recognition, or affordance) required. In this way one can describe the intimate connection between goal, action, and the environment in user–machine interaction.

To demonstrate the completeness of IU scenario analysis, IU models are presented for some well-known problems in interaction design: hidden and partially hidden modes leading to unexpected system effects, insufficient cues for subgoal construction, insufficient cues for subgoal elimination, and inappropriate affordances for action. These scenarios are accompanied by procedures that designers can use to detect similar problems in putative interaction designs.

To demonstrate the feasibility of using IU scenario analysis in design, 4 graduate students were taught to use IU scenario analysis in a 3-hr session. They then worked as a group to evaluate a prototype handheld warehouse application. A comparable group was taught and then applied Cognitive Walkthrough. Both groups successfully completed the task and detected several problems rated as being of high severity by the designers of the prototype. Analysis of the problems detected by each group suggests that the two techniques are complimentary. IU scenario analysis may be most cost-effective for devices using new interaction paradigms, whereas Cognitive Walkthrough may be most cost-effective for designs using established interaction paradigms.     

A suspicious behaviour detection using a context space model for smart surveillance systems

Video surveillance systems using Closed Circuit Television (CCTV) cameras, is one of the fastest growing areas in the field of security technologies. However, the existing video surveillance systems are still not at a stage where they can be used for crime prevention. The systems rely heavily on human observers and are therefore limited by factors such as fatigue and monitoring capabilities over long periods of time. This work attempts to address these problems by proposing an automatic suspicious behaviour detection which utilises contextual information. The utilisation of contextual information is done via three main components: a context space model, a data stream clustering algorithm, and an inference algorithm. The utilisation of contextual information is still limited in the domain of suspicious behaviour detection. Furthermore, it is nearly impossible to correctly understand human behaviour without considering the context where it is observed.This work presents experiments using video feeds taken from CAVIAR dataset and a camera mounted on one of the buildings Z-Block) at the Queensland University of Technology, Australia. From these experiments, it is shown that by exploiting contextual information, the proposed system is able to make more accurate detections, especially of those behaviours which are only suspicious in some contexts while being normal in the others. Moreover, this information gives critical feedback to the system designers to refine the system.     

Implementation and performance evaluation of a payment protocol for vehicular ad hoc networks

Vehicular ad hoc networks (VANETs) are envisioned to support the development of a wide range of attractive applications such as payment services which require the design of payment systems that satisfy additional requirements associated with VANETs. The wide range of scenarios (with or without connectivity restriction) arising from vehicle-to-vehicle and vehicle-to-roadside communications have opened up new security challenges which must be considered by payment system designers to achieve the same security capabilities independent of the scenario where payment occurs. We propose and implement a new payment protocol (called KCMS-VAN protocol) for those scenarios where the client cannot communicate directly with the credit card issuer (the client’s financial institution) for authentication. Our proposed protocol uses symmetric-key operations which require low computational power and can be processed much faster than asymmetric ones. We also present a performance evaluation of the proposed payment protocol and the results obtained demonstrate that optimal performance can be achieved with it.     

Computational support for collective creativity

The goal of our research is to develop computer systems that support designers’ collective creativity; such systems support individual creative aspects in design through the use of representations created by others in the community. We have developed two systems, IAM-eMMa and EVIDII, that both aim at supporting designers in finding visual images that would be useful for their creative design task. IAM-eMMa uses knowledge-based rules, which are constructed by other designers, to retrieve images related to a design task, and infers the underlying “rationale” when a designer chooses one of the images. EVIDII allows designers to associate affective words and images, and then shows several visual representations of the relationships among designers, images and words. By observing designers interacting with the two systems, we have identified that systems for supporting collective creativity need to be based on design knowledge that: (1) is contextualized; (2) is respectable and trustful; and (3) enables “appropriation” of a design task.     

Performing a course material enhancement process with asynchronous interactive online system

Online systems have come to be heavily used in education, particularly for online learning and collecting information not otherwise readily available. Most e-learning systems, including interactive learning systems, have been designed to “push” course materials to students but rarely to “collect” or “pull” ideas from them. The interactive mechanisms in proposed instructional design models, however, prevent many potential designers from improving course quality, even though some believe that the learning experience and the comments of students are important for enhancing course materials. As well, students could actually contribute to instructional design.This paper presents a course material enhancement process that elicits ideas from students by encouraging students to modify course materials. This process had been tested on different higher education programs, both graduate and undergraduate. It aims to understand which programs’ students have a higher willingness to participate in this work and if they can benefit from this process. To facilitate this research, an asynchronous interaction system, teacher digital assistant (TDA), was designed for teachers to receive responses, recommendations, and modified materials from students at any time. The major advantage of this process is that it could embed students’ thoughts into the course material to improve the curriculum, which can benefit future students.     

Design strategies for maximising human force capability (HFC) when using spanners

One of the principal ergonomic limitations experienced by those whose job it is to maintain equipment is the requirement for excessive levels of force in the use of spanners or “wrenches”. In studies conducted by the Institute of Occupational Medicine, designers of mining equipment reported that they would like to have guidelines on what force a man can be expected to exert. They also reported that they would like the information to show how the force capability is reduced as the designer moves away from the ergonomic optimum. However, information which could suit this purpose is almost non-existent. This paper describes a study of human force capability in which subjects adopting realistic working postures exerted maximal forces on a standard spanner. The extent to which maximal force is influenced by fastener height, direction of effort, and the use of rigid structures against which the man can brace himself is demonstrated. Guidelines for equipment designers were produced on the basis of the results of this study, and these also are described in this paper.     

From critiquing to representational talkback: computer support for revealing features in design

Computational critiquing mechanisms support designers in refining a partial design solution in an alternating cycle of reflection and action. This paper argues that critiquing mechanisms can support designers not only in refining a partial solution, but also in gaining a better understanding of the problem. We further argue that different types of critiquing are possible, ranging from conventional rule-based messages to an implicit type of critiquing based on the notion of “representational talkback” – representations that can reveal to the user otherwise implicit features of a design. We support these claims with user studies of three types of design support systems: Kid, IAM-eMMa, and Art.     

Toward a real-time model-based training system

This article describes the development of a real-time model-based training system that provides adaptive “over-the-shoulder” (OTS) instructions to trainees as they learn to perform an Anti-Air Warfare Coordinator (AAWC) task. The long-term goal is to develop a system that will provide real-time instructional materials based on learners’ actions, so that eventually the initial set of instructions on a task can be strengthened, complemented, or overridden at different stages of training. The training system is based on the ACT-R architecture, which serves as the theoretical background for the cognitive model that monitors the learning process of the trainee. An experiment was designed to study the impact of OTS instructions on learning. Results showed that while OTS instructions facilitated short-term learning, (a) they took time away from the processing of current information, (b) their effects tended to decay rapidly in initial stages of training, and (c) their effects on training diminished when the OTS instructions were proceduralized in later stages of training. A cognitive model that learned from both the upfront and OTS instructions was created and provided good fits to the learning and performance data collected from human participants. Our results suggest that to fully capture the symbiotic performance between humans and intelligent training systems, it is important to closely monitor the learning process of the trainee so that instructional interventions can be delivered effectively at different stages of training. We proposed that such a flexible system can be developed based on an adaptive cognitive model that provides real-time predictions on learning and performance.     

Algorithm substitution attacks against receivers

This work describes a class of Algorithm Substitution Attack (ASA) generically targeting the receiver of a communication between two parties. Our work provides a unified framework that applies to any scheme where a secret key is held by the receiver; in particular, message authentication schemes (MACs), authenticated encryption (AEAD) and public key encryption (PKE). Our unified framework brings together prior work targeting MAC schemes (FSE’19) and AEAD schemes (IMACC’19); we extend prior work by showing that public key encryption may also be targeted. ASAs were initially introduced by Bellare, Paterson and Rogaway in light of revelations concerning mass surveillance, as a novel attack class against the confidentiality of encryption schemes. Such an attack replaces one or more of the regular scheme algorithms with a subverted version that aims to reveal information to an adversary (engaged in mass surveillance), while remaining undetected by users. Previous work looking at ASAs against encryption schemes can be divided into two groups. ASAs against PKE schemes target key generation by creating subverted public keys that allow an adversary to recover the secret key. ASAs against symmetric encryption target the encryption algorithm and leak information through a subliminal channel in the ciphertexts. We present a new class of attack that targets the decryption algorithm of an encryption scheme for symmetric encryption and public key encryption, or the verification algorithm for an authentication scheme. We present a generic framework for subverting a cryptographic scheme between a sender and receiver, and show how a decryption oracle allows a subverter to create a subliminal channel which can be used to leak secret keys. We then show that the generic framework can be applied to authenticated encryption with associated data, message authentication schemes, public key encryption and KEM/DEM constructions. We consider practical considerations and specific conditions that apply for particular schemes, strengthening the generic approach. Furthermore, we show how the hybrid subversion of key generation and decryption algorithms can be used to amplify the effectiveness of our decryption attack. We argue that this attack represents an attractive opportunity for a mass surveillance adversary. Our work serves to refine the ASA model and contributes to a series of papers that raises awareness and understanding about what is possible with ASAs.

     

Privacy-aware routing in sensor networks

A typical sensor network application is to monitor objects, including wildlife, vehicles and events, in which information about an object is periodically sent back to the sink. Many times, the object needs to be protected for security reasons. However, an adversary can detect message flows and trace the message back to its source by moving in the reverse direction of the flows. This paper aims to maximize source location privacy, which is evaluated by the adversary’s traceback time, by designing routing protocols that distribute message flows to different routes. First, we give the performance bound for any routing scheme. Then, we present our routing schemes, which maximize the adversary’s average traceback time and achieve max–min traceback time given certain energy constraints. We then propose WRS, a suboptimal but practical privacy-aware routing scheme, and provide simulation results. Finally, we extend the discussion to an extreme adversary model, which allows the adversary to deploy an adversary sensor network to monitor the message routing activities. Accordingly, we propose a random schedule scheme to confuse the adversary. To reduce the message delivery time, we give an approximation algorithm for message routing.     

基于ARM9的嵌入式数字示波器参数测量模块的设计

针对当前数字存储示波器参数测量算法均是基于DSP和内嵌微处理器型FPGA实现的,提出了一种基于S3C2410微控制器(ARM9内核)和μC/OS-Ⅱ实时操作系统的嵌入式数字示波器参数测量软件模块的设计方法;详细分析了参数测量模块中幅度类参数和时间类参数测量算法的设计与实现过程;最后对参数测量软件模块的性能进行了详细测试,同时对测试结果的误差进行了深入的分析;测试结果验证了参数测量模块的准确性和高效性。