随着移动互联网+的广泛发展,各行各业的线上线下电子商务模式(online to offline,O2O)也应运而生,然而,同质化竞争和数据价值挖掘不足的问题限制了市场的持续向好发展。聚焦于O2O模式下的顾客满意度研究,提出了一种新型的中文文本预测模...随着移动互联网+的广泛发展,各行各业的线上线下电子商务模式(online to offline,O2O)也应运而生,然而,同质化竞争和数据价值挖掘不足的问题限制了市场的持续向好发展。聚焦于O2O模式下的顾客满意度研究,提出了一种新型的中文文本预测模型,命名为W2V-ATT-LSTM。该模型引入Attention机制以提高对重要文本的感知能力,进一步融合W2V和LSTM结构,深度挖掘头部企业真实交易数据进行分析处理、特征选择和模型训练。通过LDA模型进行主题挖掘,深入了解消费者对产品或服务的感受,为企业提供有针对性的改进建议。实验结果显示,W2V-ATT-LSTM模型在公开数据集任务中的准确率(91.4%)、精确率(82.2%)、召回率(81.7%)和F1(81.4%)等指标均优于KNN、贝叶斯、决策树、SVM等传统机器学习算法;在爬虫真实数据集任务中的准确率(94%)、精确率(90%)、召回率(89%)和F1(89%)也优于W2V、LSTM、Bi-LSTM和Bert;在多个公开中文情感分析数据集上的优越性能也表明W2V-ATT-LSTM对于理解和处理自然语言文本具有显著的实际应用价值。在当前竞争激烈的O2O市场,W2V-ATT-LSTM模型能为顾客与商家提供可靠的决策参考,有望帮助企业更好地理解顾客需求,提升服务水平,推动行业良性发展。展开更多
Digital integration within healthcare systems exacerbates their vulnerability to sophisticated ransomware threats, leading to severe operational disruptions and data breaches. Current defenses are typically categorize...Digital integration within healthcare systems exacerbates their vulnerability to sophisticated ransomware threats, leading to severe operational disruptions and data breaches. Current defenses are typically categorized into active and passive measures that struggle to achieve comprehensive threat mitigation and often lack real-time response effectiveness. This paper presents an innovative ransomware defense system, ERAD, designed for healthcare environments that apply the MITRE ATT&CK Matrix to coordinate dynamic, stage-specific countermeasures throughout the ransomware attack lifecycle. By systematically identifying and addressing threats based on indicators of compromise (IOCs), the proposed system proactively disrupts the attack chain before serious damage occurs. Validation is provided through a detailed analysis of a system deployment against LockBit 3.0 ransomware, illustrating significant enhancements in mitigating the impact of the attack, reducing the cost of recovery, and strengthening the cybersecurity framework of healthcare organizations, but also applicable to other non-health sectors of the business world.展开更多
工业控制系统(Industrial Control Systems,ICSs)是关系国计民生的关键基础设施系统。针对工业控制系统的网络攻击可造成严重的经济损失和社会负面效应。随着工业互联网的发展,越来越多的工业控制系统接入互联网,在提高生产效率的同时,...工业控制系统(Industrial Control Systems,ICSs)是关系国计民生的关键基础设施系统。针对工业控制系统的网络攻击可造成严重的经济损失和社会负面效应。随着工业互联网的发展,越来越多的工业控制系统接入互联网,在提高生产效率的同时,也使得工业控制系统面临着更加严峻的网络攻击威胁态势。由此,企业会部署各类安全措施,以期有效保护系统。然而,由于“攻防不对等”,防御者普遍缺乏对于攻击的有效了解,所部署安全措施的防护效果无法做出有效的评估,从而难以做出改进。ICS ATT&CK(Adversarial Tactics,Techniques and Common Knowledge)框架的提出,为工控领域提供了统一的攻击战术、技术知识库。该框架可有效指导工业控制系统的安全防护建设。本文针对工业控制系统所面临的检测能力评估、防护策略制定、威胁狩猎等难题,结合美国国家标准和技术协会(NIST)提出的IPDRR(Identify-Protect-Detection-Respond-Recover)能力模型、钻石模型(Diamond Model)等,探索利用ICS ATT&CK框架制定更加稳健的工业控制系统安全防护策略,为企业的网络安全防护体系建设提供借鉴和指导。展开更多
文摘随着移动互联网+的广泛发展,各行各业的线上线下电子商务模式(online to offline,O2O)也应运而生,然而,同质化竞争和数据价值挖掘不足的问题限制了市场的持续向好发展。聚焦于O2O模式下的顾客满意度研究,提出了一种新型的中文文本预测模型,命名为W2V-ATT-LSTM。该模型引入Attention机制以提高对重要文本的感知能力,进一步融合W2V和LSTM结构,深度挖掘头部企业真实交易数据进行分析处理、特征选择和模型训练。通过LDA模型进行主题挖掘,深入了解消费者对产品或服务的感受,为企业提供有针对性的改进建议。实验结果显示,W2V-ATT-LSTM模型在公开数据集任务中的准确率(91.4%)、精确率(82.2%)、召回率(81.7%)和F1(81.4%)等指标均优于KNN、贝叶斯、决策树、SVM等传统机器学习算法;在爬虫真实数据集任务中的准确率(94%)、精确率(90%)、召回率(89%)和F1(89%)也优于W2V、LSTM、Bi-LSTM和Bert;在多个公开中文情感分析数据集上的优越性能也表明W2V-ATT-LSTM对于理解和处理自然语言文本具有显著的实际应用价值。在当前竞争激烈的O2O市场,W2V-ATT-LSTM模型能为顾客与商家提供可靠的决策参考,有望帮助企业更好地理解顾客需求,提升服务水平,推动行业良性发展。
文摘Digital integration within healthcare systems exacerbates their vulnerability to sophisticated ransomware threats, leading to severe operational disruptions and data breaches. Current defenses are typically categorized into active and passive measures that struggle to achieve comprehensive threat mitigation and often lack real-time response effectiveness. This paper presents an innovative ransomware defense system, ERAD, designed for healthcare environments that apply the MITRE ATT&CK Matrix to coordinate dynamic, stage-specific countermeasures throughout the ransomware attack lifecycle. By systematically identifying and addressing threats based on indicators of compromise (IOCs), the proposed system proactively disrupts the attack chain before serious damage occurs. Validation is provided through a detailed analysis of a system deployment against LockBit 3.0 ransomware, illustrating significant enhancements in mitigating the impact of the attack, reducing the cost of recovery, and strengthening the cybersecurity framework of healthcare organizations, but also applicable to other non-health sectors of the business world.
文摘工业控制系统(Industrial Control Systems,ICSs)是关系国计民生的关键基础设施系统。针对工业控制系统的网络攻击可造成严重的经济损失和社会负面效应。随着工业互联网的发展,越来越多的工业控制系统接入互联网,在提高生产效率的同时,也使得工业控制系统面临着更加严峻的网络攻击威胁态势。由此,企业会部署各类安全措施,以期有效保护系统。然而,由于“攻防不对等”,防御者普遍缺乏对于攻击的有效了解,所部署安全措施的防护效果无法做出有效的评估,从而难以做出改进。ICS ATT&CK(Adversarial Tactics,Techniques and Common Knowledge)框架的提出,为工控领域提供了统一的攻击战术、技术知识库。该框架可有效指导工业控制系统的安全防护建设。本文针对工业控制系统所面临的检测能力评估、防护策略制定、威胁狩猎等难题,结合美国国家标准和技术协会(NIST)提出的IPDRR(Identify-Protect-Detection-Respond-Recover)能力模型、钻石模型(Diamond Model)等,探索利用ICS ATT&CK框架制定更加稳健的工业控制系统安全防护策略,为企业的网络安全防护体系建设提供借鉴和指导。
