Security Orchestration, Automation, and Response Engine for Deployment of Behavioural Honeypots

Upendra Bartwal, Subhasis Mukhopadhyay, R. Negi, S. Shukla
{"title":"Security Orchestration, Automation, and Response Engine for Deployment of Behavioural Honeypots","authors":"Upendra Bartwal, Subhasis Mukhopadhyay, R. Negi, S. Shukla","doi":"10.1109/DSC54232.2022.9888808","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":368903,"journal":{"name":"2022 IEEE Conference on Dependable and Secure Computing (DSC)","volume":"58 11","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Conference on Dependable and Secure Computing (DSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DSC54232.2022.9888808","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

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.
行为蜜罐部署的安全编排、自动化和响应引擎
对于拥有IT/ OT网络的组织来说,网络安全是一个关键话题,因为它们总是容易受到攻击,无论是内部还是外部。由于网络环境瞬息万变,我们必须不断升级保安系统,以加强基础设施的保安。安全信息和事件管理(SIEM)、端点检测和响应(EDR)、威胁情报平台(TIP)、信息技术服务管理(ITSM)等工具,以及入侵检测系统(IDS)、入侵防护系统(IPS)等其他防御技术,增强了基础设施的网络安全态势。然而,所提出的保护机制有其局限性,不足以保证安全性,并且攻击者会渗透到网络中。欺骗技术,连同蜜罐,为攻击者提供了目标系统中存在漏洞的错误感觉。被骗的攻击者透露了有关其作案手法的威胁情报。我们已经开发了一个安全编排、自动化和响应(SOAR)引擎,它可以根据攻击者的行为在内部网络基础设施中动态部署自定义蜜罐。该体系结构足够健壮,可以支持连接到系统并用于编排的多个vlan。在网络蜜罐上检测到僵尸网络流量和DDoS攻击的存在,以及恶意软件收集系统。在暴露于实时流量四天之后,我们的引擎动态编排了40次蜜罐,检测到7823次攻击,965个DDoS攻击数据包和3个恶意样本。我们对静态蜜罐的实验显示,攻击者在每个实例中的平均交战时间为102秒,而基于SOAR引擎的动态蜜罐与攻击者的交战时间平均为3148秒。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信