Intellectual Property and Antitrust Limits on Contract: Comment

In their chapter in Dynamic Competition and Public Policy (2001, Cambridge University Press), Burtis and Kobayashi never defined their model\u27s discount rate, making replicating their simulation results difficult. Through our own simulations, we were able to verify their results when using a discount rate of 0.10. We also identified two new types of equilibria that the authors overlooked, doubling the number of distinct equilibria in the model

Intellectual property and antitrust limitations on contract: comment

In their chapter in Dynamic Competition and Public Policy (2001, Cambridge University Press), Burtis and Kobayashi never defined their model's discount rate, making replicating their simulation results difficult. Through our own simulations, we were able to verify their results when using a discount rate of 0.10. We also identified two new types of equilibria that the authors overlooked, doubling the number of distinct equilibria in the model.

Creating Synthetic Attacks with Evolutionary Algorithms for Proactive Defense of Industrial Control Systems

Industrial control systems (ICS) play an important role in critical infrastructure. Cybersecurity defenders can use honeypots (decoy systems) to capture and study malicious ICS traffic. A problem with existing ICS honeypots is their low interactivity, causing intruders to quickly abandon the attack attempts. This research aims to improve ICS honeypots by feeding them realistic artificially generated packets and examining their behavior to proactively identify functional gaps in defenses. Our synthetic attack generator (SAGO) uses an evolutionary algorithm on known attack traffic to create new variants of Log4j exploits (CVE-2021-44228) and Industroyer2 malware. We tested over 5,200 and 256 unique Log4j and IEC 104 variations respectively, with success rates up to 70 percent for Log4j and 40 percent for IEC 104. We identified improvements to our honeypot’s interactivity based on its responses to these attacks. Our technique can aid defenders in hardening perimeter protection against new attack variants

Hardening Honeypots for Industrial Control Systems

Honeypots are computers that collect intelligence about new cyberattacks and malware behavior. To be successful, these decoys must allow attackers to probe a system without compromising data collection. Previously, we developed an industrial control system (ICS) honeypot simulating a small electric-distribution system, but this honeypot was attacked, and its log data was deleted. The current work analyzed the attacks and developed methods to harden the main weaknesses of the public user interface. The hardened honeypot included more robust data collection and logging capabilities, and was deployed in a commercial cloud environment. We observed significant scanning and new attacks, including the well-known BlueKeep exploit and activity related to Russian cyberattacks on Ukraine. Our results showed that the added security controls, monitoring, and logging were more effective in protecting the honeypot’s data and event logs

Retrospectively Using Multilayer Deception in Depth Against Advanced Persistent Threats

Defensive cyber deception is useful in both the information and cognitive domains of warfare. Such deception works better when it is multilayer as a defense-in-depth strategy. We developed a tool to analyze the offensive tactics in the MITRE ATT&CK Enterprise framework that were popular with sixteen Advanced Persistent Threat (APT) groups, and identified deceptive defense methods that can counter each technique. With this knowledge defenders can make more informed decisions while planning the deception to use in different layers. We use as examples three recent high-profile APT events, and review how well the deception methods could interfere with them

Creating Synthetic Attacks with Evolutionary Algorithms for Proactive Defense of Industrial Control Systems

Industrial control systems (ICS) play an important role in critical infrastructure. Cybersecurity defenders can use honeypots (decoy systems) to capture and study malicious ICS traffic. A problem with existing ICS honeypots is their low interactivity, causing intruders to quickly abandon the attack attempts. This research aims to improve ICS honeypots by feeding them realistic artificially generated packets and examining their behavior to proactively identify functional gaps in defenses. Our synthetic attack generator (SAGO) uses an evolutionary algorithm on known attack traffic to create new variants of Log4j exploits (CVE-2021-44228) and Industroyer2 malware. We tested over 5,200 and 256 unique Log4j and IEC 104 variations respectively, with success rates up to 70 percent for Log4j and 40 percent for IEC 104. We identified improvements to our honeypot’s interactivity based on its responses to these attacks. Our technique can aid defenders in hardening perimeter protection against new attack variants

Origin of conductivity cross over in entangled multi-walled carbon nanotube network filled by iron

A realistic transport model showing the interplay of the hopping transport between the outer shells of iron filled entangled multi-walled carbon nanotubes (MWNT) and the diffusive transport through the inner part of the tubes, as a function of the filling percentage, is developed. This model is based on low-temperature electrical resistivity and magneto-resistance (MR) measurements. The conductivity at low temperatures showed a crossover from Efros-Shklovski (E-S) variable range hopping (VRH) to Mott VRH in 3 dimensions (3D) between the neighboring tubes as the iron weight percentage is increased from 11% to 19% in the MWNTs. The MR in the hopping regime is strongly dependent on temperature as well as magnetic field and shows both positive and negative signs, which are discussed in terms of wave function shrinkage and quantum interference effects, respectively. A further increase of the iron percentage from 19% to 31% gives a conductivity crossover from Mott VRH to 3D weak localization (WL). This change is ascribed to the formation of long iron nanowires at the core of the nanotubes, which yields a long dephasing length (e.g. 30 nm) at the lowest measured temperature. Although the overall transport in this network is described by a 3D WL model, the weak temperature dependence of inelastic scattering length expressed as L_phi ~T^-0.3 suggests the possibility for the presence of one-dimensional channels in the network due to the formation of long Fe nanowires inside the tubes, which might introduce an alignment in the random structure.Comment: 29 pages,10 figures, 2 tables, submitted to Phys. Rev.

Propagation of highly nonlinear signals in a two dimensional network of granular chains

We report the first experimental observation of highly nonlinear signals propagating in a two dimensional system composed of granular chains. In this system one of the chains contacts two others to allow splitting and redirecting the solitary-like signal formed in the first chain. The system consists of a double Y-shaped guide in which high- and low-modulus chains of spheres are arranged in various geometries. We observed fast splitting of the initial pulse, rapid chaotization of the signal and sharp bending of the propagating acoustic information. Pulse and energy trapping was also observed in composite systems assembled from hard- and soft-particles in the branches

Implications of Shock Wave Experiments with Precompressed Materials for Giant Planet Interiors

This work uses density functional molecular dynamics simulations of fluid helium at high pressure to examine how shock wave experiments with precompressed samples can help characterizing the interior of giant planets. In particular, we analyze how large of a precompression is needed to probe a certain depth in a planet's gas envelope. We find that precompressions of up to 0.1, 1.0, 10, or 100 GPa are needed to characterized 2.5, 5.9, 18, to 63% of Jupiter's envelope by mass.Comment: Submitted As Proceedings Article For The American Physical Society Meeting On Shock Compression Of Condensed Matter, Hawaii, June, 200