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Scientific computing sometimes involves computation on sensitive data. Depending on the data and the execution environment, the HPC (high-performance computing) user or data provider may require confidentiality and/or integrity guarantees.…

It has been a long standing problem to securely outsource computation tasks to an untrusted party with integrity and confidentiality guarantees. While fully homomorphic encryption (FHE) is a promising technique that allows computations…

Android malware detection based on machine learning (ML) and deep learning (DL) models is widely used for mobile device security. Such models offer benefits in terms of detection accuracy and efficiency, but it is often difficult to…

Users are demanding increased data security. As a result, security is rapidly becoming a first-order design constraint in next generation computing systems. Researchers and practitioners are exploring various security technologies to meet…

CPUs provide isolation mechanisms like virtualization and privilege levels to protect software. Yet these focus on architectural isolation while typically overlooking microarchitectural side channels, exemplified by Meltdown and Foreshadow.…

Software debloating seeks to mitigate security risks and improve performance by eliminating unnecessary code. In recent years, a plethora of debloating tools have been developed, creating a dense and varied landscape. Several studies have…

With the continuous rise of malicious campaigns and the exploitation of new attack vectors, it is necessary to assess the efficacy of the defensive mechanisms used to detect them. To this end, the contribution of our work is twofold. First,…

Cloud computing is a ubiquitous solution to handle today's complex computing demands. However, it comes with data privacy concerns, as the cloud service provider has complete access to code and data running on their infrastructure. VM-based…

Hardware-assisted trusted execution environments (TEEs) are critical building blocks of many modern applications. However, they have a one-way isolation model that introduces a semantic gap between a TEE and its outside world. This lack of…

As Machine Learning (ML) gets applied to security-critical or sensitive domains, there is a growing need for integrity and privacy for outsourced ML computations. A pragmatic solution comes from Trusted Execution Environments (TEEs), which…

The ongoing trend of moving data and computation to the cloud is met with concerns regarding privacy and protection of intellectual property. Cloud Service Providers (CSP) must be fully trusted to not tamper with or disclose processed data,…

General-purpose operating systems (GPOS), such as Linux, encompass several million lines of code. Statistically, a larger code base inevitably leads to a higher number of potential vulnerabilities and inherently a more vulnerable system. To…

To counter man-at-the-end attacks such as reverse engineering and tampering, software is often protected with techniques that require support modules to be linked into the application. It is well-known, however, that attackers can exploit…

This paper presents an approach to provide strong assurance of the secure execution of distributed event-driven applications on shared infrastructures, while relying on a small Trusted Computing Base. We build upon and extend security…

For the dramatic increase of Android malware and low efficiency of manual check process, deep learning methods started to be an auxiliary means for Android malware detection these years. However, these models are highly dependent on the…

Privacy and security challenges in Machine Learning (ML) have become increasingly severe, along with ML's pervasive development and the recent demonstration of large attack surfaces. As a mature system-oriented approach, Confidential…

Enclaves, such as those enabled by Intel SGX, offer a hardware primitive for shielding user-level applications from the OS. While enclaves are a useful starting point, code running in the enclave requires additional checks whenever control…

Covert channels can be utilized to secretly deliver information from high privileged processes to low privileged processes in the context of a high-assurance computing system. In this case study, we investigate the possibility of covert…

Modern computer systems tend to rely on large trusted computing bases (TCBs) for operations. To address the TCB bloating problem, hardware vendors have developed mechanisms to enable or facilitate the creation of a trusted execution…

In this research paper, our intent is to outline different types of malware, their means of operation, and how they are detected in order to protect yourself against such attacks. Varied permission, and limited technical resources mean that…