Going beyond few-shot action recognition (FSAR), cross-domain FSAR (CDFSAR) has attracted recent research interests by solving the domain gap lying in source-to-target transfer learning. Existing CDFSAR methods mainly focus on joint training of source and target data to mitigate the side effect of domain gap. However, such kind of methods suffer from two limitations: First, pair-wise joint training requires retraining deep models in case of one source data and multiple target ones, which incurs heavy computation cost, especially for large source and small target data. Second, pre-trained models after joint training are adopted to target domain in a straightforward manner, hardly taking full potential of pre-trained models and then limiting recognition performance. To overcome above limitations, this paper proposes a simple yet effective baseline, namely Temporal-Aware Model Tuning (TAMT) for CDFSAR. Specifically, our TAMT involves a decoupled paradigm by performing pre-training on source data and fine-tuning target data, which avoids retraining for multiple target data with single source. To effectively and efficiently explore the potential of pre-trained models in transferring to target domain, our TAMT proposes a Hierarchical Temporal Tuning Network (HTTN), whose core involves local temporal-aware adapters (TAA) and a global temporal-aware moment tuning (GTMT). Particularly, TAA learns few parameters to recalibrate the intermediate features of frozen pre-trained models, enabling efficient adaptation to target domains. Furthermore, GTMT helps to generate powerful video representations, improving match performance on the target domain. Experiments on several widely used video benchmarks show our TAMT outperforms the recently proposed counterparts by 13% ∼31%, achieving new state-of-the-art CDFSAR results.

Summary In recent years, mobile apps have become the infrastructure of many popular Internet services. It is now common that a mobile app serves millions of users across the globe. By examining the code of these apps, reverse engineers can learn various knowledge about the design and implementation of the apps. Real‐world cases have shown that the disclosed critical information allows malicious parties to abuse or exploit the app‐provided services for unrightful profits, leading to significant financial losses. One of the most viable mitigations against malicious reverse engineering is to obfuscate the apps. Despite that security by obscurity is typically considered to be an unsound protection methodology, software obfuscation can indeed increase the cost of reverse engineering, thus delivering practical merits for protecting mobile apps. In this paper, we share our experience of applying obfuscation to multiple commercial iOS apps, each of which has millions of users. We discuss the necessity of adopting obfuscation for protecting modern mobile business, the challenges of software obfuscation on the iOS platform, and our efforts in overcoming these obstacles. We especially focus on factors that are unique to mobile software development that may affect the design and deployment of obfuscation techniques. We report the outcome of our obfuscation with empirical experiments. We additionally elaborate on the follow‐up case studies about how our obfuscation affected the app publication process and how we responded to the negative impacts. This experience report can benefit mobile developers, security service providers, and Apple as the administrator of the iOS ecosystem.

The prosperity of smartphone markets has raised new concerns about software security on mobile platforms, leading to a growing demand for effective software obfuscation techniques. Due to various differences between the mobile and desktop ecosystems, obfuscation faces both technical and non-technical challenges when applied to mobile software. Although there have been quite a few software security solution providers launching their mobile app obfuscation services, it is yet unclear how real-world mobile developers perform obfuscation as part of their software engineering practices.

Web browsers are one of the most important enduser applications to browse, retrieve, and present Internet resources. Malicious or compromised resources may endanger Web users by hijacking web browsers to execute arbitrary malicious code in the victims' systems. Unfortunately, the widely-adopted Just-In-Time compilation (JIT) optimization technique, which compiles source code to native code at runtime, significantly increases this risk. By exploiting JIT compiled code, attackers can bypass all currently deployed defenses. In this paper, we systematically investigate threats against JIT compiled code, and the challenges of protecting JIT compiled code. We propose a general defense solution, JITScope, to enforce Control-Flow Integrity (CFI) on both statically compiled and JIT compiled code. Our solution furthermore enforces the W⊕X policy on JIT compiled code, preventing the JIT compiled code from being overwritten by attackers. We show that our prototype implementation of JITScope on the popular Firefox web browser introduces a reasonably low performance overhead, while defeating existing real-world control flow hijacking attacks.

Modern web applications store sensitive data on their servers. Such data is prone to theft resulting from exploits against vulnerabilities in the server software stacks. In this work, we propose a new architecture for web servers, called CryptServer, in which we pre-determine and fix a small amount of application code that can compute over sensitive data. By encrypting sensitive data before making it available to the rest of untrusted application code, CryptServer provides strong defense against all malicious code that an attacker may run in the server software stack. As a step towards making this approach practical, we develop an assistance tool to identify the portion of server-side logic that requires computation over sensitive data. Our preliminary results show that the size of such logic is small in six popular web applications we study. To the extent of our evaluation, converting these applications to a CryptServer architecture requires modest developer effort.

Web browsers isolate web origins, but do not provide direct abstractions to isolate sensitive data and control computation over it within the same origin. As a result, guaranteeing security of sensitive web content requires trusting all code in the browser and client-side applications to be vulnerability-free. In this paper, we propose a new abstraction, called Crypton, which supports intra-origin control over sensitive data throughout its life cycle. To securely enforce the semantics of Cryptons, we develop a standalone component called Crypton-Kernel, which extensively leverages the functionality of existing web browsers without relying on their large TCB. Our evaluation demonstrates that the Crypton abstraction supported by the Crypton-Kernel is widely applicable to popular real-world applications with millions of users, including webmail, chat, blog applications, and Alexa Top 50 websites, with low performance overhead.

Web servers are vulnerable to a large class of attacks which can allow network attacker to steal sensitive web content. In this work, we investigate the feasibility of a web server architecture, wherein the vulnerable server VM runs on a trusted cloud. All sensitive web content is made available to the vulnerable server VM in encrypted form, thereby limiting the effectiveness of data-stealing attacks through server VM compromise.

Function pointers have recently become an important attack vector for control-flow hijacking attacks. However, no protection mechanisms for function pointers have yet seen wide adoption. Methods proposed in the literature have high overheads, are not compatible with existing development process, or both. In this paper, we investigate several protection methods and propose a new method called FPGate (i.e., Function Pointer Gate). FPGate rewrites x86 binary executables and implements a novel method to overcome compatibility issues. All these protection methods are then evaluated and compared from the perspectives of performance and ease of deployment. Experiments show that FPGate achieves a good balance between performance, robustness and compatibility.

Control Flow Integrity (CFI) provides a strong protection against modern control-flow hijacking attacks. However, performance and compatibility issues limit its adoption. We propose a new practical and realistic protection method called CCFIR (Compact Control Flow Integrity and Randomization), which addresses the main barriers to CFI adoption. CCFIR collects all legal targets of indirect control-transfer instructions, puts them into a dedicated "Springboard section" in a random order, and then limits indirect transfers to flow only to them. Using the Springboard section for targets, CCFIR can validate a target more simply and faster than traditional CFI, and provide support for on-site target-randomization as well as better compatibility. Based on these approaches, CCFIR can stop control-flow hijacking attacks including ROP and return-into-libc. Results show that ROP gadgets are all eliminated. We observe that with the wide deployment of ASLR, Windows/x86 PE executables contain enough information in relocation tables which CCFIR can use to find all legal instructions and jump targets reliably, without source code or symbol information. We evaluate our prototype implementation on common web browsers and the SPEC CPU2000 suite: CCFIR protects large applications such as GCC and Firefox completely automatically, and has low performance overhead of about 3.6%/8.6% (average/max) using SPECint2000. Experiments on real-world exploits also show that CCFIR-hardened versions of IE6, Firefox 3.6 and other applications are protected effectively.