Security Enhancements in Voice Over Ip Networks

Voice delivery over IP networks including VoIP (Voice over IP) and VoLTE (Voice over LTE) are emerging as the alternatives to the conventional public telephony networks. With the growing number of subscribers and the global integration of 4/5G by operations, VoIP/VoLTE as the only option for voice delivery becomes an attractive target to be abused and exploited by malicious attackers. This dissertation aims to address some of the security challenges in VoIP/VoLTE. When we examine the past events to identify trends and changes in attacking strategies, we find that spam calls, caller-ID spoofing, and DoS attacks are the most imminent threats to VoIP deployments. Compared to email spam, voice spam will be much more obnoxious and time consuming nuisance for human subscribers to filter out. Since the threat of voice spam could become as serious as email spam, we first focus on spam detection and propose a content-based approach to protect telephone subscribers\u27 voice mailboxes from voice spam. Caller-ID has long been used to enable the callee parties know who is calling, verify his identity for authentication and his physical location for emergency services. VoIP and other packet switched networks such as all-IP Long Term Evolution (LTE) network provide flexibility that helps subscribers to use arbitrary caller-ID. Moreover, interconnecting between IP telephony and other Circuit-Switched (CS) legacy telephone networks has also weakened the security of caller-ID systems. We observe that the determination of true identity of a calling device helps us in preventing many VoIP attacks, such as caller-ID spoofing, spamming and call flooding attacks. This motivates us to take a very different approach to the VoIP problems and attempt to answer a fundamental question: is it possible to know the type of a device a subscriber uses to originate a call? By exploiting the impreciseness of the codec sampling rate in the caller\u27s RTP streams, we propose a fuzzy rule-based system to remotely identify calling devices. Finally, we propose a caller-ID based public key infrastructure for VoIP and VoLTE that provides signature generation at the calling party side as well as signature verification at the callee party side. The proposed signature can be used as caller-ID trust to prevent caller-ID spoofing and unsolicited calls. Our approach is based on the identity-based cryptography, and it also leverages the Domain Name System (DNS) and proxy servers in the VoIP architecture, as well as the Home Subscriber Server (HSS) and Call Session Control Function (CSCF) in the IP Multimedia Subsystem (IMS) architecture. Using OPNET, we then develop a comprehensive simulation testbed for the evaluation of our proposed infrastructure. Our simulation results show that the average call setup delays induced by our infrastructure are hardly noticeable by telephony subscribers and the extra signaling overhead is negligible. Therefore, our proposed infrastructure can be adopted to widely verify caller-ID in telephony networks

Transcriptional Profiling of PRKG2-Null Growth Plate Identifies Putative Down-Stream Targets of PRKG2

Kinase activity of cGMP-dependent, type II, protein kinase (PRKG2) is required for the proliferative to hypertrophic transition of growth plate chondrocytes during endochondral ossification. Loss of PRKG2 function in rodent and bovine models results in dwarfism. The objective of this study was to identify pathways regulated or impacted by PRKG2 loss of function that may be responsible for disproportionate dwarfism at the molecular level. Microarray technology was used to compare growth plate cartilage gene expression in dwarf versus unaffected Angus cattle to identify putative downstream targets of PRGK2. Pathway enrichment of 1284 transcripts (nominal p \u3c 0.05) was used to identify candidate pathways consistent with the molecular phenotype of disproportionate dwarfism. Analysis with the DAVID pathway suite identified differentially expressed genes that clustered in the MHC, cytochrome B, WNT, and Muc1 pathways. A second analysis with pathway studio software identified differentially expressed genes in a host of pathways (e.g. CREB1, P21, CTNNB1, EGFR, EP300, JUN, P53, RHOA, and SRC). As a proof of concept, we validated the differential expression of five genes regulated by P53, including CEBPA, BRCA1, BUB1, CD58, and VDR by real-time PCR (p \u3c 0.05). Known and novel targets of PRKG2 were identified as enriched pathways in this study. This study indicates that loss of PRKG2 function results in differential expression of P53 regulated genes as well as additional pathways consistent with increased proliferation and apoptosis in the growth plate due to achondroplastic dwarfism

Induced pluripotent stem cell reporter systems for smooth muscle cell sheet engineering

Smooth muscle cells exist in many different locations within the body, including blood vessels and airways, where their principal function is contraction and relaxation. The heterogeneity of smooth muscle cells has been related to their embryological origins and could have implications in many diseases, including atherosclerosis, pulmonary hypertension, and asthma. Many of these diseases require an expandable cell source of smooth muscle cells for regenerative medicine or disease modeling. Here, we have developed Acta2hrGFP and ACTA2eGFP (GFP reporters for smooth muscle α-actin) reporter mouse and human induced pluripotent stem cells lines to track and isolate populations of smooth muscle-like cells. iPSCs were patterned to a KDR-expressing (kinase insert domain receptor) mesodermal progenitor, which was further specified towards a smooth muscle-like lineage through exposure to platelet derived growth factor (PDGF-BB) and transforming growth factor (TGF-β). The Acta2hrGFP+ or ACTA2eGFP+ cells were enriched for characteristic markers of smooth muscle cells, and these cells expressed low levels of contractile markers, reminiscent of an immature or synthetic smooth muscle cell. Aligned smooth muscle-like cell sheets were generated using these iPSC-derived populations in an enzymatically degradable hydrogel system. The cell sheets displayed mechanical behavior similar to native blood vessels, with the Acta2hrGFP+ cell sheets displaying a higher ultimate tensile strength than Acta2hrGFP- cell sheets. Furthermore, we performed global transcriptomic profiling of primary adult mouse lung vascular (Acta2hrGFP+ Cspg4DsRed+) and airway (Acta2hrGFP+ Cspg4DsRed-) smooth muscle cells from a double transgenic reporter mouse, where we identified distinct gene signatures of lung vascular SMCs and airway SMCs, with Hhip and Acta2 co-expression distinguishing airway SMCs from lung vascular SMCs. When comparing our miPSC-derived Acta2hrGFP+ cells to these primary SMC signatures, the in vitro derived cells cluster closer to aortic SMCs and lung vascular SMCs, but their transcriptomic signatures still remain significantly distinct. In addition, we have generated an Acta2hrGFP Cspg4DsRed reporter mouse iPSC line, which can be used to understand the signaling pathways involved in specification of these different smooth muscle cell subtypes. Thus, we have developed systems for isolating smooth muscle-like populations which have potential in tissue engineering applications, and we have identified gene signatures of adult lung vascular and airway smooth muscle cells to begin to address the heterogeneity of smooth muscle cell lineages

The biophysics of bacterial collective motion: Measuring responses to mechanical and genetic cues

Mechanobiology is an emerging field investigating mechanical signals as a necessary component of cellular and developmental regulation. These mechanical signals play a well-established role in the differentiation of animal cells, whereby cells with identical genes specialize their function and create distinct tissues depending on the physical properties of their environment, such as shear stiffness. These differences arise from the cell’s ability to use those incoming signals to inform which genes it expresses and what molecular machinery it builds and activates. Understanding the various missing factors that cause cells with specific genes to express an emergent phenotype is termed the genotype-to-phenotype problem, and mechanical signaling pathways present themselves as a significant piece of this puzzle. Despite the strong evidence for mechanosensing in eukaryotes, the pathways by which prokaryotes respond to mechanical stimuli are still largely unknown. Bacteria are among the simplest and yet most abundant forms of life. Many of their survival strategies depend on multicellular development and the coordinated formation of a colony into functional structures that may also feature cellular differentiation. This dissertation employs bacteria as a model system to investigate multiple biophysical questions of collective motion through novel experimental and analytical techniques. This work addresses the understudied mechanical relationship between a bacterial colony and the substrate it colonizes by asking “what is the effect of substrate stiffness on colony growth?” This is done by measuring bacterial growth on hydrogel substrates that decouple the effects of substrate stiffness from other material properties of the substrate that vary with stiffness. We report a previously unobserved effect in which bacteria colonize stiffer substrates faster than softer substrates, in opposition to previous studies done on agar, where permeability, viscoelasticity, and other material properties vary with stiffness.A second theme of this work probes the genetic inputs to the genotype-to-phenotype problem in multicellular development. The bacterial species Myxococcus xanthus producing macroscopic aggregates called fruiting bodies is used as a model organism for these studies. It has long been conjectured that genes may stand in for each other functionally, allowing for development to be more consistent and stable, but the extent of this redundancy has resisted measurement. We approach the question “how does redundancy among related genes lead to robust collective behavior?” by quantifying developmental phenotype in a large dataset of time lapse microscopy videos that show development in many mutant strains. We observe that when knocking out multiple genes that have a common origin (i.e. homologous genes), the resulting phenotypes differ from wild-type in a similar way. These phenotype clusters also differ from knockouts from other homologous gene families. These distinct phenotypic clusters provide evidence for the existence of networks of redundant genes that are larger than could previously be tested directly. Because of this robustness, the effects of individual gene mutations can be hidden or damped. We thus develop our analytical techniques further to address the question “how can subtle changes in phenotype be measured?” This involves quantifying the breadth of variation observed in wild-type development and creating a statistical technique to distinguish probabilistic distributions of phenotypic outcomes. We present a coherent method of visualizing large phenotypic datasets that include multiple metrics that we use to distinguish small developmental differences from wild-type, giving each mutant strain a phenotypic fingerprint that can be used in future studies on gene annotation and environmental impacts on phenotype

Synthetic biology—putting engineering into biology

Synthetic biology is interpreted as the engineering-driven building of increasingly complex biological entities for novel applications. Encouraged by progress in the design of artificial gene networks, de novo DNA synthesis and protein engineering, we review the case for this emerging discipline. Key aspects of an engineering approach are purpose-orientation, deep insight into the underlying scientific principles, a hierarchy of abstraction including suitable interfaces between and within the levels of the hierarchy, standardization and the separation of design and fabrication. Synthetic biology investigates possibilities to implement these requirements into the process of engineering biological systems. This is illustrated on the DNA level by the implementation of engineering-inspired artificial operations such as toggle switching, oscillating or production of spatial patterns. On the protein level, the functionally self-contained domain structure of a number of proteins suggests possibilities for essentially Lego-like recombination which can be exploited for reprogramming DNA binding domain specificities or signaling pathways. Alternatively, computational design emerges to rationally reprogram enzyme function. Finally, the increasing facility of de novo DNA synthesis—synthetic biology’s system fabrication process—supplies the possibility to implement novel designs for ever more complex systems. Some of these elements have merged to realize the first tangible synthetic biology applications in the area of manufacturing of pharmaceutical compounds.