Hunting binary code difference without source code (i.e., binary diffing) has compelling applications in software security. Due to the high variability of binary code, existing solutions have been driven towards measuring semantic similarities from syntactically different code. Since compiler optimization is the most common source contributing to binary code differences in syntax, testing the resilience against the changes caused by different compiler optimization settings has become a standard evaluation step for most binary diffing approaches. For example, 47 top-venue papers in the last 12 years compared different program versions compiled by default optimization levels (e.g., -Ox in GCC and LLVM). Although many of them claim they are immune to compiler transformations, it is yet unclear about their resistance to non-default optimization settings. Especially, we have observed that adversaries explored non-default compiler settings to amplify malware differences. This paper takes the first step to systematically studying the effectiveness of compiler optimization on binary code differences. We tailor search-based iterative compilation for the auto-tuning of binary code differences. We develop BinTuner to search near-optimal optimization sequences that can maximize the amount of binary code differences. We run BinTuner with GCC 10.2 and LLVM 11.0 on SPEC benchmarks (CPU2006 & CPU2017), Coreutils, and OpenSSL. Our experiments show that at the cost of 279 to 1,881 compilation iterations, BinTuner can find custom optimization sequences that are substantially better than the general -Ox settings. BinTuner's outputs seriously undermine prominent binary diffing tools' comparisons. In addition, the detection rate of the IoT malware variants tuned by BinTuner falls by more than 50%. Our findings paint a cautionary tale for security analysts that attackers have a new way to mutate malware code cost-effectively, and the research community needs to step back to reassess optimization-resistance evaluations.

With large work space and dexterous manipulation capability, mobile robots with dual arms can be used in complex operation scenes such as active detection, disassembly, spraying, cleaning and assembly, is a promising direction for robot development. In this paper, a hybrid control approach is proposed for a mobile robot with dual arms to fulfil an explosive disposal task. Firstly, the motion planning for mobile base and trajectory planning for dual arms are developed, and a hierarchical task planner is designed using the finite state machine to make the robot system to deal with events sensed by active vision. A rapidly-exploring random tree-based motion planning is developed in task space for the mobile base to realize dynamic collision avoidance, while the trajectory planning approach is proposed in the framework of a dual-arm master-slave coordinated mechanism. Next, for mobile robots to complete complex task such as explosive disposal using two dexterous hands, the impedance control approach with slippage detection is developed by considering slippage tendency and slippage intensity to produce a stable in-hand manipulation. Furthermore, the Faster R-CNN is employed to determine the grasping region for robot manipulation through object detection and learning. Finally, the explosive disposal scene is designed to justify the effectiveness and good performance of the proposed methods.

A novel solid–liquid interdiffusion (SLID) bonding method with the assistance of temperature gradient (TG) was carried out to bonding Cu and Ni substrates with Sn as interlayer. The element distribution and grain morphology of interfacial intermetallic compound (IMC) in Cu/Sn/Ni micro-joints during both SLID and TG-SLID bonding and in the final Cu/(Cu,Ni)₆Sn₅/Ni full IMC micro-joints were analyzed. Under the effect of Cu-Ni cross-interaction, interfacial (Cu,Ni)₆Sn₅ dominated the IMC growth at all the interfaces. The morphology of the (Cu,Ni)₆Sn₅ grains was closely related to Ni content with three levels of low, medium and high. The full IMC micro-joints consisted of L-(Cu,Ni)₆Sn₅, M-(Cu,Ni)₆Sn₅ and H-(Cu,Ni)₆Sn₅ grains after SLID bonding or TG-SLID bonding with Ni as hot end, while only L-(Cu,Ni)₆Sn₅ grains after TG-SLID bonding with Cu as hot end, showing that the direction of TG had a remarkably effect on the growth and morphology of the interfacial (Cu,Ni)₆Sn₅ during TG-SLID bonding. Thermodynamic analysis revealed the key molar latent heat and critical Ni content between fine-rounded-like (Cu,Ni)₆Sn₅ and block-like (Cu,Ni)₆Sn₅ were 17,725.4 J and 11.0 at.% at 260 °C, respectively. Moreover, the growth kinetic of the interfacial IMC was analyzed in detail during bonding with and without TG. Under the combination of TG and Cu-Ni cross-interaction, void-free full IMC micro-joints were fast formed by TG-SLID bonding with Cu as hot end. This bonding method may present a feasible solution to solve the problems of low formation efficiency and inevitable Cu₃Sn growth of full IMC joints for 3D packaging applications.

Zigbee is widely adopted as a resource-efficient wireless protocol in the IoT network. IoT devices from manufacturers have recently been affected due to major vulnerabilities in Zigbee protocol implementations. Security testing of Zigbee protocol implementations is becoming increasingly important. However, applying existing vulnerability detection techniques such as fuzzing to the Zigbee protocol is not a simple task. Dealing with low-level hardware events still remains a big challenge. For the Zigbee protocol, which communicates over a radio channel, many existing protocol fuzzing tools lack a sufficient execution environment. To narrow the gap, we designed Z-Fuzzer , a device-agnostic fuzzing tool for detecting security flaws in Zigbee protocol implementations. To simulate Zigbee protocol execution, Z-Fuzzer leverages a commercial embedded device simulator with pre-defined peripherals and hardware interrupt setups to interact with the fuzzing engine. Z-Fuzzer generates more high-quality test cases with code-coverage heuristics. We compare Z-Fuzzer with advanced protocol fuzzing tools, BooFuzz and Peach fuzzer, on top of Z-Fuzzer’s simulation platform. Our findings suggest that Z-Fuzzer can achieve greater code coverage in Z-Stack, a widely used Zigbee protocol implementation. Compared to BooFuzz and Peach, Z-Fuzzer found more vulnerabilities with fewer test cases. Three of them have been assigned CVE IDs with high CVSS scores (7.5~8.2).