DF 2.0: Designing an automated, privacy preserving, and efficient digital forensic framework

The current state of digital forensic investigation is continuously challenged by the rapid technological changes, the increase in the use of digital devices (both the heterogeneity and the count), and the sheer volume of data that these devices could contain. Although it is not directly related to the performance of Digital Forensic Investigation process, preventing data privacy violations during the process is also a big challenge. The investigator gets full access to the forensic image including suspect\u27s private data which may be sensitive at times as well as entirely unrelated to the given case under investigation. With a notion that privacy preservation and completeness of investigation are contradicting to each other, the digital forensics researchers have provided solutions to address the above-stated challenges that either focus on the effectiveness of the investigation process or the data privacy preservation. However, a generalized approach that preserves data privacy by affecting neither the capabilities of the investigator nor the overall efficiency of the investigation process is still an open problem. In the current work, the authors have proposed a digital forensic framework that uses case information, case profile data and expert knowledge for automation of the digital forensic analysis process; utilizes machine learning for finding most relevant pieces of evidence; and preserves data privacy in such a way that the overall efficiency of the digital forensic investigation process increases without affecting the integrity and admissibility of the evidence. The framework improves validation to enhance transparency in the investigation process. The framework also uses a secure logging mechanism to capture investigation steps to achieve a higher level of accountability. Since the proposed framework introduces significant enhancements to the current investigative practices more like the next version of Digital Forensics, the authors named it `Digital Forensics 2.0\u27, or DF 2.0 in short

Precognition: Automated Digital Forensic Readiness System for Mobile Computing Devices in Enterprises

Enterprises are facing an unprecedented risk of security incidents due to the influx of emerging technologies, like smartphones and wearables. Most of the current Mobile security systems are not maturing in pace with technological advances. They lack the ability to learn and adapt from the past knowledge base. In the case of a security incident, enterprises find themselves underprepared for the lack of evidence and data. The systems are not designed to be forensic ready. There is a need for automated security analysis and forensically ready solution, which can learn and continuously adapt to new challenges, improve efficiency and productivity of the system. In this research, the authors have designed a security analysis and digital forensic readiness system targeted at smartphones and wearables in an enterprise environment. The proposed system detects applications violating security policies, analyzes Android and iOS applications to identify possible vulnerabilities on the server, apply machine learning algorithms to improve the efficiency and accuracy of vulnerability prediction. The System continuously learns from past incidents, proactively collect required information from the devices which can help in digital forensics. Machine learning techniques are applied to the set of features extracted from the decompiled Mobile applications and applications classified based on consisting of one or more vulnerabilities. The system was evaluated in a real-world enterprise environment with 14151 mobile applications and vulnerabilities was predicted with an accuracy of 94.2%. The system can also work on virtual instances of the mobile devices

DF 2.0: An Automated, Privacy Preserving, and Efficient Digital Forensic Framework That Leverages Machine Learning for Evidence Prediction and Privacy Evaluation

The current state of digital forensic investigation is continuously challenged by the rapid technological changes, the increase in the use of digital devices (both the heterogeneity and the count), and the sheer volume of data that these devices could contain. Although data privacy protection is not a performance measure, however, preventing privacy violations during the digital forensic investigation, is also a big challenge. With a perception that the completeness of investigation and the data privacy preservation are incompatible with each other, the researchers have provided solutions to address the above-stated challenges that either focus on the effectiveness of the investigation process or the data privacy preservation. However, a comprehensive approach that preserves data privacy without affecting the capabilities of the investigator or the overall efficiency of the investigation process is still an open problem. In the current work, the authors have proposed a digital forensic framework that uses case information, case profile data and expert knowledge for automation of the digital forensic analysis process; utilizes machine learning for finding most relevant pieces of evidence; and maintains data privacy of non-evidential private files. All these operations are coordinated in a way that the overall efficiency of the digital forensic investigation process increases while the integrity and admissibility of the evidence remain intact. The framework improves validation which boosts transparency in the investigation process. The framework also achieves a higher level of accountability by securely logging the investigation steps. As the proposed solution introduces notable enhancements to the current investigative practices more like the next version of Digital Forensics, the authors have named the framework `Digital Forensics 2.0\u27, or `DF 2.0\u27 in short

Diversity and status of migratory and resident wetland birds in Haridwar, Uttarakhand, India

Migration is the seasonal habitual movement, exhibited by many avian species along a flyway from breeding to wintering grounds and vice versa all over the world. Migratory birds are very sensitive to even small changes in water level which may be affected by flood or drought on their breeding and wintering grounds. High rains during monsoon season can cause flood conditions in the lower hills and Gangetic plains including Haridwar district. In our study, conducted during last ten years (2009-2018), we covered Bheemgoda Barrage and Missarpur Ganga Ghat of Haridwar, Uttarakhand, where 46 species of Migratory (M) and Resident Migratory (RM) wetland birds were observed. Bird survey indicated that there was a significant increase (p = 0.064, t-test) in the population of certain species such as Bhraminy Shelduck (67%), Black Headed Gull (31%), Gadwall (7%), Northern Pintail (59%), Red Crested Pochard (10%) and Tufted Pochard (47%) in Missarpur Ganga Ghat as compared to Bheemgoda Barrage (based on the average abundance of the species observed during study period). It may be pointed out that after flood and loss of vegetated island, there was significant decrease (p= 0.023, t-test) in the population of species such as Black necked stork (76%), Great crested grebe (56), Pallas gull (47%) at Bheemgoda barrage, while some species such as Bar headed goose, Common pochard did not arrive in Bheemgoda barrage after the flood. The study would help to understand the effect of climatic change on water birds species distribution in natural and man-made wetlands

COMPARISON OF 3D VOLUME REGISTRATION TECHNIQUES APPLIED TO NEUROSURGERY

poster abstractIntroduction: Image guided surgery requires that the pre-operative da-ta used for planning the surgery should be aligned with the patient during surgery. For this surgical application a fast, effective volume registration al-gorithm is needed. In addition, such an algorithm can also be used to devel-op surgical training presentations. This research tests existing methods of image and volume registration with synthetic 3D models and with 3D skull data. The aim of this research is to find the most promising algorithms in ac-curacy and execution time that best fit the neurosurgery application. Methods: Medical image volumes acquired from MRI or CT medical im-aging scans provided by the Indiana University School of Medicine were used as Test image cases. Additional synthetic data with ground truth was devel-oped by the Informatics students. Each test image was processed through image registration algorithms found in four common medical imaging tools: MATLAB, 3D Slicer, VolView, and VTK/ITK. The resulting registration is com-pared against the ground truth evaluated with mean squared error metrics. Algorithm execution time is measured on standard personal computer (PC) hardware. Results: Data from this extensive set of tests reveal that the current state of the art algorithms all have strengths and weaknesses. These will be categorized and presented both in a poster form and in a 3D video presenta-tion produced by Informatics students in an auto stereoscopic 3D video. Conclusions: Preliminary results show that execution of image registra-tion in real-time is a challenging task for real time neurosurgery applica-tions. Final results will be available at paper presentation. Future research will focus on optimizing registration and also implementing deformable regis-tration in real-time

Engineering nucleotide specificity of succinyl-CoA synthetase in blastocystis: the emerging role of gatekeeper residues

Charged, solvent-exposed residues at the entrance to the substrate binding site (gatekeeper residues) produce electrostatic dipole interactions with approaching substrates, and control their access by a novel mechanism called "electrostatic gatekeeper effect". This proof-of-concept study demonstrates that the nucleotide specificity can be engineered by altering the electrostatic properties of the gatekeeper residues outside the binding site. Using Blastocystis succinyl-CoA synthetase (SCS, EC 6.2.1.5), we demonstrated that the gatekeeper mutant (ED) resulted in ATP-specific SCS to show high GTP specificity. Moreover, nucleotide binding site mutant (LF) had no effect on GTP specificity and remained ATP-specific. However, via combination of the gatekeeper mutant with the nucleotide binding site mutant (ED+LF), a complete reversal of nucleotide specificity was obtained with GTP, but no detectable activity was obtained with ATP. This striking result of the combined mutant (ED+LF) was due to two changes; negatively charged gatekeeper residues (ED) favored GTP access, and nucleotide binding site residues (LF) altered ATP binding, which was consistent with the hypothesis of the "electrostatic gatekeeper effect". These results were further supported by molecular modeling and simulation studies. Hence, it is imperative to extend the strategy of the gatekeeper effect in a different range of crucial enzymes (synthetases, kinases, and transferases) to engineer substrate specificity for various industrial applications and substrate-based drug design

A Reversible Color Polyphenism in American Peppered Moth (Biston betularia cognataria) Caterpillars

Insect body color polyphenisms enhance survival by producing crypsis in diverse backgrounds. While color polyphenisms are often indirectly induced by temperature, rearing density, or diet, insects can benefit from immediate crypsis if they evolve polyphenisms directly induced by exposure to the background color, hence immediately deriving protection from predation. Here, we examine such a directly induced color polyphenism in caterpillars of the geometrid peppered moth (Biston betularia). This larval color polyphenism is unrelated to the genetic polymorphism for melanic phenotypes in adult moths. B. betularia caterpillars are generalist feeders and develop body colors that closely match the brown or green twigs of their host plant. We expand on previous studies examining the proximal cues that stimulate color development. Under controlled rearing conditions, we manipulated diets and background reflectance, using both natural and artificial twigs, and show that visual experience has a much stronger effect than does diet in promoting precise color matching. Their induced body color was not a simple response to reflectance or light intensity but instead specifically matched the wavelength of light to which they were exposed. We also show that the potential to change color is retained until the final (sixth) larval instar. Given their broad host range, this directly induced color polyphenism likely provides the caterpillars with strong protection from bird predation

Detrimental NFKB1 missense variants affecting the Rel-homology domain of p105/p50

Most of the currently known heterozygous pathogenic NFKB1 (Nuclear factor kappa B subunit 1) variants comprise deleterious defects such as severe truncations, internal deletions, and frameshift variants. Collectively, these represent the most frequent monogenic cause of common variable immunodeficiency (CVID) identified so far. NFKB1 encodes the transcription factor precursor p105 which undergoes limited proteasomal processing of its C-terminal half to generate the mature NF-kappa B subunit p50. Whereas p105/p50 haploinsufficiency due to devastating genetic damages and protein loss is a well-known disease mechanism, the pathogenic significance of numerous NFKB1 missense variants still remains uncertain and/or unexplored, due to the unavailability of accurate test procedures to confirm causality. In this study we functionally characterized 47 distinct missense variants residing within the N-terminal domains, thus affecting both proteins, the p105 precursor and the processed p50. Following transient overexpression of EGFP-fused mutant p105 and p50 in HEK293T cells, we used fluorescence microscopy, Western blotting, electrophoretic mobility shift assays (EMSA), and reporter assays to analyze their effects on subcellular localization, protein stability and precursor processing, DNA binding, and on the RelA-dependent target promoter activation, respectively. We found nine missense variants to cause harmful damage with intensified protein decay, while two variants left protein stability unaffected but caused a loss of the DNA-binding activity. Seven of the analyzed single amino acid changes caused ambiguous protein defects and four variants were associated with only minor adverse effects. For 25 variants, test results were indistinguishable from those of the wildtype controls, hence, their pathogenic impact remained elusive. In summary, we show that pathogenic missense variants affecting the Rel-homology domain may cause protein-decaying defects, thus resembling the disease-mechanisms of p105/p50 haploinsufficiency or may cause DNA-binding deficiency. However, rare variants (with a population frequency of less than 0.01%) with minor abnormalities or with neutral tests should still be considered as potentially pathogenic, until suitable tests have approved them being benign.Peer reviewe

A multiwavelength study of the massive star forming region IRAS 06055+2039 (RAFGL 5179)

We present a multiwavelength study of the massive star forming region associated with IRAS 06055+2039 which reveals an interesting scenario of this complex where regions are at different stages of evolution of star formation. Narrow band near-infrared (NIR) observations were carried out with UKIRT-UFTI in molecular hydrogen and Br$\gamma$ lines to trace the shocked and ionized gases respectively. We have used 2MASS $J H K_{s}$ data to study the nature of the embedded cluster associated with IRAS 06055+2039. We obtain a power-law slope of 0.43$\pm$0.09 for the $K_{s}$-band Luminosity Function (KLF) which is in good agreement with other young embedded clusters. We estimate an age of 2 -- 3 Myr for this cluster. The radio emission from the ionized gas has been mapped at 610 and 1280 MHz using the Giant Metrewave Radio Telescope (GMRT), India. Apart from the diffuse emission, the high resolution 1280 MHz map also shows the presence of several discrete sources which possibly represent high density clumps. The morphology of shocked molecular hydrogen forms an arc towards the N-E of the central IRAS point source and envelopes the radio emission. Submillimetre emission using JCMT-SCUBA show the presence of a dense cloud core which is probably at an earlier evolutionary stage compared to the ionized region with shocked molecular gas lying in between the two. Emission from warm dust and the Unidentified Infrared Bands (UIBs) have been estimated using the mid-infrared (8 -- 21 $\mu$m) data from the MSX survey. From the submillimetre emission at 450 and 850 $\mu$m the total mass of the cloud is estimated to be $\sim$ 7000 -- 9000 $\rm M_{\odot}$.Comment: Accepted for publication in A &

Development and validation of an improved algorithm for overlaying flexible molecules

A program for overlaying multiple flexible molecules has been developed. Candidate overlays are generated by a novel fingerprint algorithm, scored on three objective functions (union volume, hydrogen-bond match, and hydrophobic match), and ranked by constrained Pareto ranking. A diverse subset of the best ranked solutions is chosen using an overlay-dissimilarity metric. If necessary, the solutions can be optimised. A multi-objective genetic algorithm can be used to find additional overlays with a given mapping of chemical features but different ligand conformations. The fingerprint algorithm may also be used to produce constrained overlays, in which user-specified chemical groups are forced to be superimposed. The program has been tested on several sets of ligands, for each of which the true overlay is known from protein–ligand crystal structures. Both objective and subjective success criteria indicate that good results are obtained on the majority of these sets