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Embedded Policing and Policy Enforcement Approach for Future Secure IoT Technologies

机译:嵌入式警务和策略执法方法,以备将来安全物联网技术

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The Internet of Things (IoT) holds great potential for productivity, quality control, supply chain efficiencies and overall business operations. However, with this broader connectivity, new vulnerabilities and attack vectors are being introduced, increasing opportunities for systems to be compromised by hackers and targeted attacks. These vulnerabilities pose severe threats to a myriad of IoT applications within areas such as manufacturing, healthcare, power and energy grids, transportation and commercial building management. While embedded OEMs offer technologies, such as hardware Trusted Platform Module (TPM), that deploy strong chain-of-trust and authentication mechanisms, still they struggle to protect against vulnerabilities introduced by vendors and end users, as well as additional threats posed by potential technical vulnerabilities and zero-day attacks. This paper proposes a pro-active policy-based approach, enforcing the principle of least privilege, through hardware Security Policy Engine (SPE) that actively monitors communication of applications and system resources on the system communication bus (ARM AMBA-AXI4). Upon detecting a policy violation, for example, a malicious application accessing protected storage, it counteracts with predefined mitigations to limit the attack. The proposed SPE approach widely complements existing embedded hardware and software security technologies, targeting the mitigation of risks imposed by unknown vulnerabilities of embedded applications and protocols.
机译:事物互联网(物联网)拥有生产力,质量控制,供应链效率和整体业务运营的巨大潜力。然而,随着这种更广泛的连接,正在引入新的漏洞和攻击向量,增加了系统受到黑客妥协的机会和有针对性的攻击。这些漏洞在制造,医疗保健,电力和能源网,运输和商业建筑管理等领域内对无数的物联网申请构成严重威胁。虽然嵌入式OEM提供了硬件可信平台模块(TPM)的技术,但部署了强大的信任链和认证机制,仍然努力保护供应商和最终用户引入的漏洞,以及潜在构成的额外威胁技术漏洞和零日攻击。本文提出了一种基于积极的基于策略的方法,通过硬件安全策略引擎(SPE)来强制执行最小特权的原理,该发动机(SPE)积极监控系统通信总线(ARM AMBA-AXI4)上的应用程序和系统资源的通信。在检测到策略违规时,例如,访问受保护存储的恶意应用程序,它抵消了预定义的缓解以限制攻击。所提出的SPE方法广泛补充了现有的嵌入式硬件和软件安全技术,针对嵌入式应用和协议的未知漏洞所强加的风险。

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