论文标题
安全编排,自动化和响应引擎,用于部署行为蜜罐
Security Orchestration, Automation, and Response Engine for Deployment of Behavioural Honeypots
论文作者
论文摘要
对于具有IT/OT网络的组织来说,网络安全是一个关键的话题,因为它们总是容易受到攻击,无论是内部人士还是局外人。由于网络景观是一种不断发展的情况,因此必须继续升级其安全系统以增强基础架构的安全性。诸如安全信息和事件管理(SIEM),端点检测和响应(EDR),威胁智能平台(TIP),信息技术服务管理(ITSM)等工具,以及其他防御技术,例如入侵检测系统(IDS),入侵保护系统(IPS)以及许多其他工具,以及许多其他工具,增强了基础结构的网络安全姿势。但是,提议的保护机制有其局限性,它们不足以确保安全,并且攻击者渗透了网络。欺骗技术以及蜜罐,为攻击者提供了错误的脆弱感。攻击者欺骗了Intel对他们的作案手法的威胁。我们已经开发了安全编排,自动化和响应(SOAR)引擎,该发动机根据攻击者的行为动态部署内部网络基础架构内的自定义蜜饯。该体系结构足以支持与系统连接并用于编排的多个VLAN。检测到网络中的蜜饯的僵尸网络流量和DDOS攻击以及恶意软件收集系统。在接触了四天的现场交通后,我们的引擎动态策划了40次蜜罐,检测到7823次攻击,965个DDOS攻击包和三个恶意样本。虽然我们使用静态蜜罐进行的实验表明,每个实例的平均攻击者参与时间为102秒,但我们基于发动机的动态蜜饯平均使攻击者平均3148秒。
Cyber Security is a critical topic for organizations with IT/OT networks as they are always susceptible to attack, whether insider or outsider. Since the cyber landscape is an ever-evolving scenario, one must keep upgrading its security systems to enhance the security of the infrastructure. Tools like Security Information and Event Management (SIEM), Endpoint Detection and Response (EDR), Threat Intelligence Platform (TIP), Information Technology Service Management (ITSM), along with other defensive techniques like Intrusion Detection System (IDS), Intrusion Protection System (IPS), and many others enhance the cyber security posture of the infrastructure. However, the proposed protection mechanisms have their limitations, they are insufficient to ensure security, and the attacker penetrates the network. Deception technology, along with Honeypots, provides a false sense of vulnerability in the target systems to the attackers. The attacker deceived reveals threat intel about their modus operandi. We have developed a Security Orchestration, Automation, and Response (SOAR) Engine that dynamically deploys custom honeypots inside the internal network infrastructure based on the attacker's behavior. The architecture is robust enough to support multiple VLANs connected to the system and used for orchestration. The presence of botnet traffic and DDOS attacks on the honeypots in the network is detected, along with a malware collection system. After being exposed to live traffic for four days, our engine dynamically orchestrated the honeypots 40 times, detected 7823 attacks, 965 DDOS attack packets, and three malicious samples. While our experiments with static honeypots show an average attacker engagement time of 102 seconds per instance, our SOAR Engine-based dynamic honeypots engage attackers on average 3148 seconds.