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Starting with a random initial seed, fuzzers search for inputs that trigger bugs or vulnerabilities. However, fuzzers often fail to generate inputs for program paths guarded by restrictive branch conditions. In this paper, we show that by first identifying rare-paths in programs (i.e., program paths with path constraints that are unlikely to be satisfied by random input generation), and then, generating inputs/seeds that trigger rare-paths, one can improve the coverage of fuzzing tools. In particular, we present techniques 1) that identify rare paths using quantitative symbolic analysis, and 2) generate inputs that can explore these rare paths using path-guided concolic execution. We provide these inputs as initial seed sets to three state of the art fuzzers. Our experimental evaluation on a set of programs (that contain a lot of restrictive branch conditions) shows that the fuzzers achieve better coverage with the rare-path based seed set compared to a random initial seed.

Recent years have seen more critical applications designed to protect human lives (e.g., environmental sensing, emergency response, and tactical defense) being deployed over wireless networks. These critical deployments expect higher data rates, ultra-low latency, and ultra-high reliability. 6G wireless networks are expected to fill the gap in terms of the first two aspects (i.e., higher data rates and ultra-low latency), however providing ultra-high reliability is a wide open challenge. All is well when everything works but when there is a failure or a security attack, the entire system collapses exposing the associated human lives to imminent danger. Avoiding this requires the strongest of assurances that safety and security aspects are protected no matter what. Large scale critical applications are waiting for this piece of the puzzle to be solved. At this juncture, we envision the bold theme of La R\'esistance 6G (LR6G) that would pave the way for deploying mission-critical applications and services over 6G networks. It aims to achieve ultra-high reliability and resiliency to any disruptions, be it failures or security attacks. A few disruptions are easy to handle such as a cloud VM or primary link failure. In both of these cases, applications can be restored by activating the standby resource. However, some disruptions can be detrimental such as when a cut-vertex fails or when the disruption leaves the critical application to fail without access to a standby resource. These critical applications (e.g. Smart Manufacturing, Smart City, Ocean monitoring, Wildfire monitoring, etc.) are highly distributed in nature. They must continue to deliver their mission objectives during a disruption to protect human lives. In this paper, we present our LR6G vision and outline the challenges towards achieving this vision.

Data centers require high-performance network equipment that consume low power and support high bandwidth requirements. In this context, a combinatorial approach was proposed to design data center network (DCN) equipment from a library of components in \cite{infocom}. This library includes power splitter, wavelength multiplexers, reconfigurable add-drop multiplexers and optical amplifiers. When interconnecting optical components, it must be ensured that the resultant network supports specified target bit-error-rates (typically, at most $10^{-12}$). This paper reports experiment conducted on component interconnections and their computed bit-error-rates. From the experimental analysis, it was observed that the desired objective can be decided by considering a zeroth-order threshold for optical power at the receiver and before the amplifier. This paves way for the theoretical evaluation of several other such designs using this empirically derived model., Comment: 4 pages

In power networks where multiple fuel cell stacks are employed to deliver the required power, optimal sharing of the power demand between different stacks is an important problem. This is because the total current collectively produced by all the stacks is directly proportional to the fuel utilization, through stoichiometry. As a result, one would like to produce the required power while minimizing the total current produced. In this paper, an optimization formulation is proposed for this power distribution control problem. An algorithm that identifies the globally optimal solution for this problem is developed. Through an analysis of the KKT conditions, the solution to the optimization problem is decomposed into on-line and on-line computations. The on-line computations reduce to simple equation solving. For an application with a specific v-i function derived from data, we show that analytical solutions exist for on-line computations. We also discuss the wider applicability of the proposed approach for similar problems in other domains.