조영필 교수

Remote computing has emerged as a trendy computing model that enables users to process an immense number of computations efficiently on the remote server where the necessary data and high-performance computing power are provisioned. Unfortunately, despite such an advantage, this computing model suffers from insider threats that are committed by adversarial administrators of remote servers who attempt to steal or corrupt users' private data. These security threats are somewhat innate to remote co

TrustZone is a hardware security technique in ARM mobile devices. Using TrustZone, software components running within the secure world can be completely isolated from the normal world, which ensures hardware-enforced security access control over the underlying computing resources. In order to support multiple trusted applications, TrustZone runs its own operating system, called the secure OS, within the secure world. Unfortunately, attackers have been exploiting privilege escalation vulnerabilit

Pointer invalidation has been a popular approach adopted in many recent studies to mitigate use-after-free errors. The approach can be divided largely into two different schemes: explicit invalidation and implicit invalidation. The former aims to eradicate the root cause of use-after-free errors by explicitly invalidating every dangling pointer. In contrast, the latter aims to prevent dangling pointers by freeing an object only if there is no pointer referring to it. A downside of the explicit s

With the exponential growth of Internet of Things (IoT) devices, IoT has become a transformative technology with applications spanning various domains. It encompasses a wide range of public and industrial vertical services that come with diverse and stringent Quality of Service (QoS) requirements. Traditional networks often struggle to meet the demands of these diverse IoT services. As a result, the introduction of 5G and Beyond 5G (B5G) networks holds promise in accommodating these diverse IoT

Against spatial memory violations threatening a vast amount of legacy software, various safety solutions have been suggested for decades. However, their practical uses have been impeded by diverse reasons, such as significant overheads and mandatory modifications of existing architectures. Accordingly, there has been a clear need for a practical safety solution that is fast enough and yet runs on commodity systems for its wide applicability in the field. As an effort to meet this need, a major p

Large OS kernels always suffer from attacks due to their numerous inherent vulnerabilities. To protect the kernel, hypervisors have been employed by many security solutions. However, relying on a hypervisor has a detrimental impact on the system performance due mainly to nested paging. In this paper, we present Hypernel, a security framework combining hardware and software components to address this problem. Hypersec, the software component, provides an isolated execution environment for securit

As ARM is becoming more popular in today’s processor market, the OS kernel on ARM is gradually bloated to meet the market demand for more sophisticated services by absorbing diverse kernel extensions. Since this kernel bloating inevitably increases the attack surface, there has been a continuous effort to decrease the surface by dissociating or isolating untrusted extensions from the kernel. One approach in this effort is using software fault isolation (SFI) that instruments memory and control-t

Security monitoring has long been considered as a fundamental mechanism to mitigate the damage of a security attack. Recently, intra-level security systems have been proposed that can efficiently and securely monitor system software without any involvement of more privileged entity. Unfortunately, there exists no full intra-level security system that can universally operate at any privilege level on ARM. However, as malware and attacks increase against virtually every level of privileged softwar

Field programmable gate arrays (FPGAs) have been increasingly mounted on commodity systems. As a matter of fact, such an emerging adoption of FPGAs in the commodity systems is attributed to their versatility came from the programmable property. Accordingly many industrial and academic attempts have been performed to exploit FPGAs in a variety of applications. In this paper, we note that FPGAs also can be used to protect the host CPU from a nasty security threat, called code reuse attacks (CRAs).

Accommodating novel and diverse services with different quality of service requirements (QoS), including Web 3.0, metaverse, AR/VR, smart industries, smart hospitals, etc., is very challenging for Beyond 5G (B5G) networks. These services require high-speed, low latency, and seamless connectivity. Conversely, network slicing in B5G networks is the best candidate to support these services by providing dedicated resources. However, automatically orchestrating and managing network slicing for these

Attacks on embedded devices are likely to occur any time in unexpected manners. Thus, the defense systems based on fixed sets of rules will easily be subverted by such unexpected, unknown attacks. Learning-based anomaly detection may potentially prevent new unknown zero-day attacks by leveraging the capability of machine learning (ML) to learn the intricate true nature of software hidden within raw information. This paper introduces our work to develop an MPSoC, called RTAD, which can efficientl

AMD's Secure Encrypted Virtualization (SEV) is a hardware-based Trusted Execution Environment (TEE) designed to secure tenants' data on the cloud, even against insider threats. The latest version of SEV, SEV-Secure Nested Paging (SEV-SNP), offers protection against most well-known attacks such as cold boot and hypervisor-based attacks. However, it remains susceptible to a specific type of attack known as Active DRAM Corruption (ADC), where attackers manipulate memory content using specially craf

Much compelling evidence urges that the isolation provided by the hypervisor in a virtualized system is not complete at all, and in practice can be neutralized by elaborated adversaries, which consequently emphasizes the need of techniques to detect attacks on the guest VM kernels. In this regard, learning-based HIDSs have received much attention, which inspect the internals of each VM through monitoring models built by machine learning techniques. The inspection capability of learning-based HID