Deleting Collected Digital Evidence by Exploiting a Widely Adopted Hardware Write Blocker

In this primary work we call for the importance of integrating security testing into the process of testing digital forensic tools. We postulate that digital forensic tools are increasing in features (such as network imaging), becoming networkable, and are being proposed as forensic cloud services. This raises the need for testing the security of these tools, especially since digital evidence integrity is of paramount importance. At the time of conducting this work, little to no published anti-forensic research had focused on attacks against the forensic tools/process.We used the TD3, a popular, validated, touch screen disk duplicator and hardware write blocker with networking capabilities and designed an attack that corrupted the integrity of the destination drive (drive with the duplicated evidence) without the user\u27s knowledge. By also modifying and repackaging the firmware update, we illustrated that a potential adversary is capable of leveraging a phishing attack scenario in order to fake digital forensic practitioners into updating the device with a malicious operating system. The same attack scenario may also be practiced by a disgruntled insider. The results also raise the question of whether security standards should be drafted and adopted by digital forensic tool makers

DROP (DRone Open source Parser) Your Drone: Forensic Analysis of the DJI Phantom III

The DJI Phantom III drone has already been used for malicious activities (to drop bombs, remote surveillance and plane watching) in 2016 and 2017. At the time of writing, DJI was the drone manufacturer with the largest market share. Our work presents the primary thorough forensic analysis of the DJI Phantom III drone, and the primary account for proprietary file structures stored by the examined drone. It also presents the forensically sound open source tool DRone Open source Parser (DROP) that parses proprietary DAT files extracted from the drone\u27s nonvolatile internal storage. These DAT files are encrypted and encoded. The work also shares preliminary findings on TXT files, which are also proprietary, encrypted, encoded, files found on the mobile device controlling the drone. These files provided a slew of data such as GPS locations, battery, flight time, etc. By extracting data from the controlling mobile device, and the drone, we were able to correlate data and link the user to a specific device based on extracted metadata. Furthermore, results showed that the best mechanism to forensically acquire data from the tested drone is to manually extract the SD card by disassembling the drone. Our findings illustrated that the drone should not be turned on as turning it on changes data on the drone by creating a new DAT file, but may also delete stored data if the drone\u27s internal storage is full

Forensic State Acquisition from Internet of Things (FSAIoT): A General Framework and Practical Approach for IoT Forensics through IoT Device State Acquisition

IoT device forensics is a difficult problem given that manufactured IoT devices are not standardized, many store little to no historical data, and are always connected; making them extremely volatile. The goal of this paper was to address these challenges by presenting a primary account for a general framework and practical approach we term Forensic State Acquisition from Internet of Things (FSAIoT). We argue that by leveraging the acquisition of the state of IoT devices (e.g. if an IoT lock is open or locked), it becomes possible to paint a clear picture of events that have occurred. To this end, FSAIoT consists of a centralized Forensic State Acquisition Controller (FSAC) employed in three state collection modes: controller to IoT device, controller to cloud, and controller to controller. We present a proof of concept implementation using openHAB -- a device agnostic open source IoT device controller -- and self-created scripts, to resemble a FSAC implementation. Our proof of concept employed an Insteon IP Camera as a controller to device test, an Insteon Hub as a controller to controller test, and a nest thermostat for a a controller to cloud test. Our findings show that it is possible to practically pull forensically relevant state data from IoT devices. Future work and open research problems are shared

Experimental Fracture Model versus Osteotomy Model in Metacarpal Bone Plate Fixation

Introduction. Osteotomy or fracture models can be used to evaluate mechanical properties of fixation techniques of the hand skeleton in vitro. Although many studies make use of osteotomy models, fracture models simulate the clinical situation more realistically. This study investigates monocortical and bicortical plate fixation on metacarpal bones considering both aforementioned models to decide which method is best suited to test fixation techniques. Methods. Porcine metacarpal bones (n = 40) were randomized into 4 groups. In groups I and II bones were fractured with a modified 3-point bending test. The intact bones represented a further control group to which the other groups after fixation were compared. In groups III and IV a standard osteotomy was carried out. Bones were fixated with plates monocortically (group I, III) and bicortically (group II, IV) and tested for failure. Results. Bones fractured at a mean maximum load of 482.8 N ± 104.8 N with a relative standard deviation (RSD) of 21.7%, mean stiffness was 122.3 ± 35 N/mm. In the fracture model, there was a significant difference (P = 0.01) for maximum load of monocortically and bicortically fixed bones in contrast to the osteotomy model (P = 0.9). Discussion. In the fracture model, because one can use the same bone for both measurements in the intact state and the bone-plate construct states, the impact of inter-individual differences is reduced. In contrast to the osteotomy model there are differences between monocortical and bicortical fixations in the fracture model. Thus simulation of the in vivo situation is better and seems to be suitable for the evaluation of mechanical properties of fixation techniques on metacarpals

NF-kB functions in synaptic signaling and behavior

Ca^(2+)-regulated gene transcription is essential to diverse physiological processes, including the adaptive plasticity associated with learning. We found that basal synaptic input activates the NF-kB transcription factor by a pathway requiring the Ca^(2+)/calmodulin-dependent kinase CaMKII and local submembranous Ca^(2+) elevation. The p65:p50 NF-kB form is selectively localized at synapses; p65-deficient mice have no detectable synaptic NF-kB. Activated NF-kB moves to the nucleus and could directly transmute synaptic signals into altered gene expression. Mice lacking p65 show a selective learning deficit in the spatial version of the radial arm maze. These observations suggest that long-term changes to adult neuronal function caused by synaptic stimulation can be regulated by NF-kB nuclear translocation and gene activation

Electronic sculpting of ligand-GPCR subtype selectivity:the case of angiotensin II

GPCR subtypes possess distinct functional and pharmacological profiles, and thus development of subtype-selective ligands has immense therapeutic potential. This is especially the case for the angiotensin receptor subtypes AT1R and AT2R, where a functional negative control has been described and AT2R activation highlighted as an important cancer drug target. We describe a strategy to fine-tune ligand selectivity for the AT2R/AT1R subtypes through electronic control of ligand aromatic-prolyl interactions. Through this strategy an AT2R high affinity (<i>K</i>_i = 3 nM) agonist analogue that exerted 18,000-fold higher selectivity for AT2R versus AT1R was obtained. We show that this compound is a negative regulator of AT1R signaling since it is able to inhibit MCF-7 breast carcinoma cellular proliferation in the low nanomolar range

Atmospheric stilling offsets the benefits from reduced nutrient loading in a large shallow lake

As part of a global phenomenon, a 30% decrease in average wind speed since 1996 in southern Estonia together with more frequent easterly winds resulted in 47% decrease in bottom shear stress in the large (270 km2), shallow (mean depth 2.8 m), and eutrophic Lake Võrtsjärv. Following a peak in eutrophication pressure in the 1970s–80s, the concentrations of total nutrients were declining. Nonmetric Multidimensional Scaling (NMDS) ordination of a 54-year phytoplankton community composition time-series (1964–2017) revealed three distinct periods with breaking points coinciding with changes in wind and/or water level. Contrary to expectations, we detected no decrease in optically active substances that could be related to wind stilling, whereas phytoplankton biomass showed an increasing trend despite reduced nutrient levels. Here we show how opening of the “light niche,” caused by declining amount of suspended sediments, was capitalized and filled by the light-limited phytoplankton community. We suggest that wind stilling is another global factor, complementary to climate warming that counteracts eutrophication mitigation in lakes and may provide a challenge to assessment of the lake ecological status.Main financial support for EMU: European Union’s Horizon 2020 research and innovation programme Under the Marie Skłodowska-Curie Action, Innovative Training Networks, European Joint Doctorates.Project name, acronym and grant number: Management of climatic extreme events in lakes and reservoirs for the protection of ecosystem services, MANTEL, grant agreement No 722518.Publication date and, if applicable, length of embargo period: Published as Early View on 07.10.2019, no embargo period.Main financial support for EMU: European Union’s Horizon 2020 research and innovation programme Under the Marie Skłodowska-Curie Action, Innovative Training Networks, European Joint Doctorate

Author correction : a global database for metacommunity ecology, integrating species, traits, environment and space

Correction to: Scientific Data https://doi.org/10.1038/s41597-019-0344-7, published online 08 January 202

Author correction : a global database for metacommunity ecology, integrating species, traits, environment and space

Correction to: Scientific Data https://doi.org/10.1038/s41597-019-0344-7, published online 08 January 202