Detecting network intrusions by data mining and variable-length sequence pattern matching

Anomaly detection has been an active research topic in the field of network intrusion detection for many years. A novel method is presented for anomaly detection based on system calls into the kernels of Unix or Linux systems. The method uses the data mining technique to model the normal behavior of a privileged program and uses a variable-length pattern matching algorithm to perform the comparison of the current behavior and historic normal behavior, which is more suitable for this problem than the fixed-length pattern matching algorithm proposed by Forrest et al. At the detection stage, the particularity of the audit data is taken into account, and two alternative schemes could be used to distinguish between normalities and intrusions. The method gives attention to both computational efficiency and detection accuracy and is especially applicable for on-line detection. The performance of the method is evaluated using the typical testing data set, and the results show that it is significantly better than the anomaly detection method based on hidden Markov models proposed by Yan et al. and the method based on fixed-length patterns proposed by Forrest and Hofmeyr. The novel method has been applied to practical hosted-based intrusion detection systems and achieved high detection performance.

The Quality Assessment of Non-Integer-Hour Data in GPS Broadcast Ephemerides and Its Impact on the Accuracy of Real- Time Kinematic Positioning Over the South China Sea

Abnormal effects in GPS broadcast ephemerides can have a significant effect on real-time navigation and positioning solutions that use the orbit and clock error data provided by GPS broadcast ephemerides.This paper describes three types of non-integerhour navigation data in GPS broadcast ephemeris data.Compared with GPST integer hour data,we find that there are two types of data blocks for non-integer-hour navigation containing gross errors with different levels of precision,which is reflected in the user range accuracy(URA)of the broadcast ephemeris.These gross errors can cause large deviations when using the GPS broadcast ephemeris for orbit calculation and lead to a decrease in the kinematic positioning accuracy.An improved weighting method which is based on the consistency relationship between the URA value and the orbital precision is proposed to improve the positioning accuracy by controlling the effect of gross errors in the broadcast ephemerides.The correction algorithm proposed in this paper was applied to real-time kinematic positioning with shipborne GPS data over the South China Sea.The results showed that the proposed positioning algorithm can effectively reduce the effects of gross errors in the broadcast ephemeris,and significantly improve the accuracy of the navigation and positioning.

Scheduling for Uncertain Data Broadcast in Mobile Networks

With the increasing popularity of wireless sensor network and GPS （ global positioning system）, uncertain data as a new type of data brings a new challenge for the traditional data processing methods. Data broadcast is an effective means for data dissemination in mobile networks. In this paper, the def＇mition of the mean uncertainty ratio of data is presented and a broadcasting scheme is proposed for uncertain data dissemination. Simulation results show that the scheme can reduce the uncertainty of the broadcasted uncertain data effectively at the cost of a minor increase in data access time, in the case of no transmission error and presence of transmission errors. As a result, lower uncertainty of data benefits the qualifies of the query results based on the data.

Scheduling for constantly-evolving data broadcasting in asymmetric communication networks

Recent advances in wireless sensor networks and GPS have made constantly-evolving data a new type of data which bring a new challenge to traditional data processing methods. Data broadcasting is an effective means for data dissemination in asymmetric communication networks, such as wireless networks. In this paper, definition of the mean uncertainty ratio of data is presented and a broadcasting scheme is proposed for constantly-evolving data dissemination. Simulation results show that the scheme can reduce the uncertainty of the broadcasted constantly-evolving data effectively at the cost of minor increase in data access time, in the case of no transmission error, transmission errors present, and multiple broadcast channels. As a result it benefits the qualities of the query results based on the data.

Storing and Searching Metadata for Digital Broadcasting on Set-Top Box Environments

Digital broadcasting is a novel paradigm for the next generation broadcasting. Its goal is to provide not only better quality of pictures but also a variety of services that is impossible in traditional airwaves broadcasting. One of the important factors for this new broadcasting environment is the interoperability among broadcasting applications since the environment is distributed. Therefore the broadcasting metadata becomes increasingly important and one of the metadata standards for a digital broadcasting is TV-Anytime metadata. TV-Anytime metadata is defined using XML schema, so its instances are XML data. In order to fulfill interoperability, a standard query language is also required and XQuery is a natural choice. There are some researches for dealing with broadcasting metadata. In our previous study, we have proposed the method for efficiently managing the broadcasting metadata in a service provider. However, the environment of a Set-Top Box for digital broadcasting is limited such as low-cost and low-setting. Therefore there are some considerations to apply general approaches for managing the metadata into the Set-Top Box. This paper proposes a method for efficiently managing the broadcasting metadata based on the Set-Top Box and a prototype of metadata management system for evaluating our method. Our system consists of a storage engine to store the metadata and an XQuery engine to search the stored metadata and uses special index for storing and searching. Our two engines are designed independently with hardware platform therefore these engines can be used in any low-cost applications to manage broadcasting metadata.

高山无线发射台站智慧运维管理系统设计

自智慧广电战略提出以来,广播电视无线覆盖智慧化已成为广电行业技术研究的热点。本文详细介绍了高山无线发射台站的智慧化改造,通过在自台播出监控系统的基础上进行重新设计,构建了智慧运维管理系统。该系统实现了广播电视节目传输、发射的监控一体化云管理,并依托大数据、人工智能等技术,扩展了链路设备故障定位、智能诊断和播出预警等功能。这些改进措施全面提升了高山发射台站的安全播出保障能力。

大数据技术在新闻采编中的应用

介绍大数据技术和新闻采编的基本概念,探讨新闻采编中大数据技术的具体应用,包括新闻内容生成、趋势预测与深度分析、媒体监控与分析、新闻可视化报道、反假新闻与验证以及社会情感分析等,详细总结大数据技术的应用优势以及应用的注意事项,旨在为大数据时代背景下新闻采编工作的进步和创新提供借鉴与帮助。

权利束视角下体育赛事转播权数据财产权说的补正、型构与平衡——基于新《体育法》第52条第2款的制度解释

运用文献资料法、逻辑分析法等研究方法,阐释体育赛事转播权数据财产权说的证成及不足,对引入权利束理论的必要性、可行性及功能展开路径进行学理分析。研究发现,数据财产权说为体育赛事转播权的权属界定、请求权基础规范的确定提供了思路,但仍存在以下不足:忽略了新《体育法》第52条第2款所规定的体育赛事转播权存在多个主体的可能;未能实现对体育赛事转播权的积极权能构造;可能加剧体育赛事组织者对体育赛事数据的绝对垄断和独占。对此,权利束理论作为分析方法,能够解释体育赛事转播链条上多元主体权利交织的现象,更弹性地认识和描述不同的权利主张,阐明权利冲突后价值顺位的确定依据。同时,鉴于体育赛事转播权利束存在束点,且具备财产权的利益性、享有性和排他性,因而权利束的功能展开具备可行性。据此,探索其功能展开路径:弥合既有研究成果与新《体育法》相关条款的脱节;厘清体育赛事转播权的积极权能构造;实现体育赛事转播权链条上多元主体间的利益衡平。

Machine-Learning Based Packet Switching Method for Providing Stable High-Quality Video Streaming in Multi-Stream Transmission

Broadcasting gateway equipment generally uses a method of simply switching to a spare input stream when a failure occurs in a main input stream.However,when the transmission environment is unstable,problems such as reduction in the lifespan of equipment due to frequent switching and interruption,delay,and stoppage of services may occur.Therefore,applying a machine learning(ML)method,which is possible to automatically judge and classify network-related service anomaly,and switch multi-input signals without dropping or changing signals by predicting or quickly determining the time of error occurrence for smooth stream switching when there are problems such as transmission errors,is required.In this paper,we propose an intelligent packet switching method based on the ML method of classification,which is one of the supervised learning methods,that presents the risk level of abnormal multi-stream occurring in broadcasting gateway equipment based on data.Furthermore,we subdivide the risk levels obtained from classification techniques into probabilities and then derive vectorized representative values for each attribute value of the collected input data and continuously update them.The obtained reference vector value is used for switching judgment through the cosine similarity value between input data obtained when a dangerous situation occurs.In the broadcasting gateway equipment to which the proposed method is applied,it is possible to perform more stable and smarter switching than before by solving problems of reliability and broadcasting accidents of the equipment and can maintain stable video streaming as well.

AI技术在电视节目自动化剪辑与制播流程中的应用与挑战

随着人工智能(Artificial Intelligence,AI)技术的不断发展,其在电视节目制播中的应用逐渐普及,通过场景识别与智能分割、情感分析与内容筛选、自动生成叙事线索以及个性化推荐与智能优化等技术,显著提高了节目制作的效率和质量。然而,技术瓶颈、法律与伦理问题、人力资源变革以及数据安全与隐私保护等挑战随之而来。为了应对这些挑战,提出一系列对策。这些对策的实施将有助于电视节目制播行业更好地应对AI技术带来的挑战,推动行业的创新发展,为观众提供更加优质、个性化的节目体验。

广播电视融媒体云平台内容生产系统的设计与实现

近年来,河北广播电视台融媒体云平台依托互联网的云服务,支撑传统电视内容的远程制作、新媒体内容生产,实现内容多渠道分发和多平台网络直播矩阵,通过融媒体云平台各模块智能协同,形成全媒布局矩阵发力的业态传播体系,全方位提升了河北广播电视台技术平台的融合水平。

使用Broadcast Disks方法分布的空中位图索引

提出一种使用BroadcastDisks算法来分布位图索引的空中索引方法,根据数据项访问概率,使用位图作为数据广播的索引,减少了移动终端等待数据时保持激活状态的时间,达到节能的目的。

广电工程中8K超高清电视显示技术的关键问题与解决方案

探讨8K超高清电视显示技术在数据传输与处理、显示设备与技术、节目制作与播出标准等方面所面临的挑战,并提出相应的解决方案。针对数据传输与处理的瓶颈,建议采用先进的压缩编码技术和高效的传输协议。在显示设备与技术方面,应加大研发力度,推动新型显示材料和器件的应用,并提高与现有技术的兼容性。在节目制作与播出标准方面,需要制定统一的流程和标准以降低制作难度和成本。通过这些措施,有望推动8K技术在广电领域的广泛应用和发展。

5G在电视直播中的应用

5G以高速率、大带宽、低时延的特性,为电视直播行业带来了前所未有的发展机遇。电视直播作为信息传播的重要方式,其质量与效率直接影响观众的观看体验。基于此,探讨5G在电视直播领域的优势及具体应用,包括4K超高清视频、多视角和虚拟现实(Virtual Reality,VR)直播、移动直播以及个性化和安全传输等应用。在5G的加持下,电视直播正迈向一个全新的时代,为观众带来更加丰富、互动和个性化的观看体验。

语音报警系统在破碎车间自动化控制系统中的应用

破碎车间中控室操作人员配置较少情况下,为能够让中控室操作人员及时获取设备故障报警信息,搭建了一个统一的语音报警系统进行故障报警。语音报警系统能够将设备报警和故障信息及时通过语音播报出来,并将相应报警故障等信息进行存储,以便后期查找总结。语音报警系统在破碎车间自动化控制系统中的应用,能够避免因破碎车间中控室操作人员发现、处理设备故障不及时而造成的事故,有效提高了破碎车间报警处理率,保证了生产安全,实际应用效果良好。

基于大数据技术的广播电视监测工作研究

广播电视监测工作能够有效把控广播电视播出进程,科学维护广播电视播出环境,精准提升电视节目产出质量。基于此,分析广播电视监测监管工作存在的监测对象繁多、监测系统孤立、监测资源缺失等问题,提出基于大数据技术完成对不同监测对象的数据采集、独立监测系统的信息融合、多类监测资源的优化调度等工作,并运用数据挖掘算法和解析模型提升广播电视监测工作的整体效能。

云南广播电视台信息安全平台建设概述

当前,一些融合效果显著的广播电视台已从信息化向数字化转型。以云南广播电视台为例,从核心理念、关键技术和建设方案等方面,介绍其信息安全平台建设情况,以期为其他电视台的相关工作提供参考。

广播电视智慧运维体系建设研究

广播电视智慧运维体系是围绕发射台的核心功能,以信息技术为支撑形成的数字化、标准化、智能化管理体系,其建设原则体现在实用性、兼容性、全面性等方面。广播电视智慧运维体系是在信息技术、数据中心、人工智能的支持下构建的集设备监测、信号监控、运维监管于一体的服务体系,实现信息技术与传统运维工作的结合,既保证全面的运营维护功能,又能从根本上提升运营维护的效率和质量。介绍广播电视智慧运维体系建设的背景、原则、目标及整体架构,为广播电视行业在数字时代背景下的智慧化转型提供理论支持和实践指导。

基于全流程数据交互的媒资版权管理平台的设计与实现

本文以“媒资+版权”的设计理念,聚焦节目信息、媒资信息、生产流程信息、版权信息和管理行为等数据,设计了基于全流程数据交互的媒资版权管理平台,用于实现节目、素材、片段资源与版权权利之间全流程的生产经营关联管理,可为传统广电媒体版权经营开发提供有力的数据和服务支撑。

基于区块链技术的广播电视系统内容安全管理方法

在数字化时代,广播电视系统面临着前所未有的内容安全管理挑战。内容盗版问题、数据篡改和安全漏洞、内容分发的透明度和可追溯性问题以及用户隐私保护等问题日益凸显,对行业的可持续发展构成严峻挑战。对此,深入探讨区块链技术如何应对广播电视系统内容安全管理中的关键挑战,分析区块链技术的基本原理和应用案例,阐述区块链技术在广播电视系统中的具体应用方法和潜在价值,提出一套基于区块链技术的广播电视系统内容安全管理方案。