Abnormal Behavior Analysis in Office Automation System within Organizations

There are many abnormal user behavior in the enterprise network environment, how to monitor it effectively is a hot research hotspot. At present, the analysis of abnormal behavior is mainly through the means of traffic monitoring, but there is no precise definition and related research on the behavior of enterprise network users. Therefore, the paper propose a model to analyze the abnormal behavior of enterprise network users. First, the data from the monitoring log of enterprise network should be pre-processing and the user behavior are serializing; then, for each user behavior sequence in sequence databases, calculating the user behavior similarity and correlation coefficient in a week by the improved algorithm; finally, comparing the similarity and the correlation coefficient between users and finding the user abnormal behavior. In this paper, we use the model to verify the feasibility of the internal network of the company, and find out the user’s abnormal behavior.

14 - Office Automation

Efficiency and security is very important in office automation systems, this paper analyses how the role-based access control model (RBAC) works, and presents an effective authority control method based on RBAC model in Web applications. Practice shows that the Web application based on RABC model has excellent safety and stability. We have successfully developed a universal office automation management system based on RBAC model. The system has been successfully applied to several colleges in Jiangxi province. It has played an important role in improving administrative efficiency.

To be highly useful, office automation systems require customization to individual users, work environments, and tasks. We consider the question of whether office automation systems can be developed that allow users who are not skilled programmers to easily “program”, or customize, these tools themselves. In other words, can we deploy very general, non-customized programs that can be extended and adapted during usage? Besides the well-known knowledge acquisition and automated learning methods we propose an approach called dialog-based learning (DBL), that allows the user to teach the system directly while performing the task. It acquires knowledge through a dialog in which the user both illustrates the procedure using a grounded example, and provides instructions about how to perform the task in the general case. We focus discussion on CAP II (a program that schedules meetings by negotiation via email), and on RAP (a program that makes room reservation via email).

Office automation system can effectively improve office efficiency and enhance collaborative work capacity, reduce repetitive work and complexity of manual operation. This paper studies office automation system functions for the application of software development enterprise. Using use case model to describe the system requirements, using the module structure diagram to build the system function framework, the main functions of the system are described. Specific functions include: System management, Training management, Project management, Staff management, Office supplies management, Reimbursement management, Evaluation management, Conference management, Overtime management, Official document management, Books management, Vehicle management. The system successful application can improve the office conditions, and standardize the process, making software enterprise management more scientific and modern.

Protocol's abnormal behavior analysis is an important task in protocol reverse analysis. Traditional protocol reverse analysis focus on the protocol message format, but protocol behavior especially the abnormal behavior is rare studied. In this paper, protocol behavior is represented by the labeled behavior instruction sequences. Similar behavior instruction sequences mean the similar protocol behavior. Using our developed virtual analysis platform HiddenDisc, we can capture a variety of known or unknown protocols' behavior instruction sequences. All kinds of executed or unexecuted instruction sequences can automatic clustering by our designed instruction clustering algorithm. Thereby we can distinguish and mine the unknown protocols' potential abnormal behavior. The mined potential abnormal behavior instruction sequences are executed, monitored and analyzed on HiddenDisc to determine whether it is an abnormal behavior and what is the behavior's nature. Using the instruction clustering algorithm, we have analyzed 1297 protocol samples, mined 193 potential abnormal instruction sequences, and determined 187 malicious abnormal behaviors by regression testing. Experimental results show that our proposed instruction clustering algorithm has high efficiency and accuracy, can mine unknown protocols' abnormal behaviors effectively, and enhance the initiative defense capability of network security.

A number of concurrent technological and organizational developments in the office automation area offer an excellent opportunity to greatly improve information systems management. This paper will attempt to show how information systems control could be taken over by managers through office automation. The emphasis is first on showing how office automation can contribute in designing manageable and controllable information systems from offices. Next, some organizational implications are discussed including possible structural changes and roles of the involved actors. Finally, a research design approach is outlined. It provides a practical framework to tackle implementation issues taking into account some critical constraints generated by office automation systems, notably from an organizational and social perspective.KeywordsText ProcessingOffice StaffOffice EnvironmentWharton SchoolOffice FunctionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Abnormal behavior analysis in crowded scenes is a challenging task in the computer vision field. Determining how to quickly and accurately locate abnormal behavior in a crowd, especially in airports, shopping malls, stations, and other practical application scenarios, has become the key to the timely handling of mass incidents. The authors have developed an embedded video analysis robot capable of local processing for crowd anomaly detection in application scenarios. In recent years, many methods of crowd anomaly detection have been proposed by scholars, but the performance of these methods when applied to video service robots is unsatisfactory. In this paper, an anomaly analysis method based on improved k-means is proposed. This method combines mean shift and the k-means classification method to achieve rapid and accurate crowd anomaly detection. A quantitative experimental evaluation was carried out on a video service robot, and the results demonstrate that the method is effective for the detection of abnormal behavior on multiple and publicly available video sequences.

Assessing the organizational climate for OA implementation

The dangerous and harmful factors of machinery manufacturing mainly include human unsafe behavior and consciousness factors, unsafe state factors of equipment and adverse environmental factors. The characteristics and classification of abnormal behavior are analyzed, the detection methods of operators' abnormal running behavior are compared, and the discrimination basis of operators' abnormal running behavior is analyzed. The wearable inertial sensor is studied. The acceleration sensor is used to measure the acceleration of the measured object, and the gyroscope sensor can measure the angle of the human body relative to the ground. MPU9250 is selected as the measurement tool of acceleration and angle to identify the abnormal behavior of the human body, and cooperate with the single chip microcomputer, It is conducive to the detection and early warning of abnormal behavior of mechanical operators.

Forms have been used in the design of at least three office automation systems (OfficeTalk, Odyssey, and OFS). Forms help ease the transition from a manual office system based on paper forms to a computer office system based on electronic forms. Forms also exhibit other advantages, not exploited presently, that make them very desirable for inclusion in office automation systems of the future. Potential capabilities of electronic forms are explored by focusing on three important aspects-fields, abstraction, and access rights. Electronic forms can have a large variety of fields; constraints and rules can be associated with these fields and automatically enforced. Moreover, forms are similar to abstract data types. Treating forms as abstract data types allows their being used as an abstraction tool and facilitates many kinds of automatic error checking. Finally, access rights can be associated with forms to ensure that forms are accessed and/or modified by appropriate users only. To illustrate the ideas presented, an exemplary form definition is presented and some implementation details discussed.

The purpose of this research is to study employee responses to a new office automation system over an extended period of time. Following the conceptual framework proposed by O'Connor, Parsons, Liden, and Herold (1990), constructs of interest were categorized as individual differences, implementation outcomes. The research occurred in a life insurance trade association over an 18-month period. Three waves of questionnaires focused on different parts of the conceptual framework. Support was found for the direct relationships between inputs, facilitators (or resistors), and outcomes. The role of facilitators/resistors as intervening variables received mixed support. These results and others are discussed in the context of a conceptual model and future research suggestions are made.

Energy Production System Management – Renewable energy power supply integration with Building Automation System

BackgroundTo date, the differentiated requirements for network performance in various health care service scenarios—within, outside, and between hospitals—remain a key challenge that restricts the development and implementation of digital medical services.ObjectiveThis study aims to construct and implement a private 5G (the 5th generation mobile communication technology) standalone (SA) medical network in a smart health environment to meet the diverse needs of various medical services.MethodsBased on an analysis of network differentiation requirements in medical applications, the system architecture and functional positioning of the proposed private 5G SA medical network are designed and implemented. The system architecture includes the development of exclusive and preferential channels for medical use, as well as an ordinary user channel. A 3-layer network function architecture is designed, encompassing resource, control, and intelligent operation layers to facilitate management arrangements and provide network open services. Core technologies, including edge cloud collaboration; service awareness; and slicing of access, bearer, and core networks, are employed in the construction and application of the 5G SA network.ResultsThe construction of the private 5G SA medical network primarily involves system architecture, standards, and security measures. The system, featuring exclusive, preferential, and common channels, supports a variety of medical applications. Relevant standards are adhered to in order to ensure the interaction and sharing of medical service information. Security is achieved through mechanisms such as authentication, abnormal behavior analysis, and dynamic access control. Three typical medical applications that rely on the 5G network in intrahospital, interhospital, and out-of-hospital scenarios—namely, mobile ward rounds, remote first aid, and remote ultrasound—were conducted. Testing of the 5G-enabled mobile ward rounds showed an average download rate of 790 Mbps and an average upload rate of 91 Mbps. Compared with 4G, the 5G network more effectively meets the diverse requirements of various business applications in prehospital emergency scenarios. For remote ultrasound, the average downlink rate of the 5G network is 4.82 Mbps, and the average uplink rate is 2 Mbps, with an average fluctuation of approximately 8 ms. The bandwidth, performance, and delay of the 5G SA network were also examined and confirmed to be effective.ConclusionsThe proposed 5G SA medical network demonstrates strong performance in typical medical applications. Its construction and application could lead to the development of new medical service models and provide valuable references for the further advancement and implementation of 5G networks in other industries, both in China and globally.

Recently, indiscriminate ransomware attacks targeting a wide range of victims for monetary gains have become a worldwide social issue. In the early years, ransomware has used e-mails as attack method. The most common spreading method was through spam mail or harmful websites. In addition, social networking sites or smartphone messages are used. Ransomware can encrypt the user's files and issues a warning message to the user and requests payment through bitcoin, which is a virtual currency that is hard to trace. It is possible to analyze ransomware but this has its limitations as new ransomware is being continuously created and disseminated. In this paper, we propose an enhanced ransomware prevention system based on abnormal behavior analysis and detection in cloud analysis system--CloudRPS. This proposed system can defend against ransomware through more in-depth prevention. It can monitors the network, file, and server in real time. Furthermore, it installs a cloud system to collect and analyze various information from the device and log information to defend against attacks. Finally, the goal of the system is to minimize the possibility of the early intrusion. And it can detect the attack quickly more to prevent at the user's system in case of the ransomware compromises.