Convolutional Radio Modulation Recognition Networks

We study the adaptation of convolutional neural networks to the complex temporal radio signal domain. We compare the efficacy of radio modulation classification using naively learned features against using expert features which are widely used in the field today and we show significant performance improvements. We show that blind temporal learning on large and densely encoded time series using deep convolutional neural networks is viable and a strong candidate approach for this task especially at low signal to noise ratio

An analysis on decentralized adaptive MAC protocols for Cognitive Radio networks

The scarcity of bandwidth in the radio spectrum has become more vital since the demand for more and more wireless applications has increased. Most of the spectrum bands have been allocated although many studies have shown that these bands are significantly underutilized most of the time. The problem of unavailability of spectrum and inefficiency in its utilization has been smartly addressed by the Cognitive Radio (CR) Technology which is an opportunistic network that senses the environment, observes the network changes, and then using knowledge gained from the prior interaction with the network, makes intelligent decisions by dynamically adapting their transmission characteristics. In this paper some of the decentralized adaptive MAC protocols for CR networks have been critically analyzed and a novel adaptive MAC protocol for CR networks, DNG-MAC which is decentralized and non-global in nature, has been proposed. The results show the DNG-MAC out performs other CR MAC protocols in terms of time and energy efficiency

Concurrent bandits and cognitive radio networks

We consider the problem of multiple users targeting the arms of a single multi-armed stochastic bandit. The motivation for this problem comes from cognitive radio networks, where selfish users need to coexist without any side communication between them, implicit cooperation or common control. Even the number of users may be unknown and can vary as users join or leave the network. We propose an algorithm that combines an $\epsilon$-greedy learning rule with a collision avoidance mechanism. We analyze its regret with respect to the system-wide optimum and show that sub-linear regret can be obtained in this setting. Experiments show dramatic improvement compared to other algorithms for this setting

Anti-angiogenic activity of the flavonoid precursor 4-hydroxychalcone.

Angiogenesis, the growth of new blood vessels, is necessary for cancerous tumors to keep growing and spreading. Suppression of abnormal angiogenesis may provide therapeutic strategies for the treatment of angiogenesis-dependent disorders. In the present study, we describe the in vitro and in vivo anti-angiogenic activities of the flavonoid precursor 4-hydroxychalcone (Q797). This chalcone (22μg/ml) suppressed several steps of angiogenesis, including endothelial cell proliferation, migration and tube formation without showing any signs of cytotoxicity. Moreover, we found a selective effect on activated endothelial cells, in particular with resting endothelial cells and the human epithelial tumor cell lines (HeLa, MCF-7, A549). In addition, Q797 was able to modulate both vascular endothelial growth factor (VEGF)- and basic fibroblast growth factor (FGF)- induced phosphorylation of extracellular signal-regulated kinase (ERK)-1/-2 and Akt kinase. It did not influence the nuclear translocation of p65 subunit of the nuclear factor-κB (NF-κB) when human endothelial cells were stimulated with tumor necrosis factor (TNF)-α. Taken together this indicates that the Q797-mediated inhibition of in vitro angiogenic features of endothelial cells is most likely caused by suppression of growth factor pathways. The potent inhibitory effect of Q797 on bFGF-driven neovascularization was also demonstrated in vivo using the chick chorioallantoic membrane (CAM) assay. In summary, this chalcone could serve as a new leading structure in the discovery of new potent synthetic angiogenesis inhibitors

The COOH-Terminal Peptide of Platelet Factor-4 Variant (CXCL4L1/PF-4var47-70) Strongly Inhibits Angiogenesis and Suppresses B16 Melanoma Growth In vivo.

Chemokines influence tumor growth directly or indirectly via both angiogenesis and tumor-leukocyte interactions. Platelet factor-4 (CXCL4/PF-4), which is released from alpha-granules of activated platelets, is the first described angiostatic chemokine. Recently, it was found that the variant of CXCL4/PF-4 (CXCL4L1/PF-4var) could exert a more pronounced angiostatic and antitumoral effect than CXCL4/PF-4. However, the molecular mechanisms of the angiostatic activities of the PF-4 forms remain partially elusive. Here, we studied the biological properties of the chemically synthesized COOH-terminal peptides of CXCL4/PF-4 (CXCL4/PF-4(47-70)) and CXCL4L1/PF-4var (CXCL4L1/PF-4var(47-70)). Both PF-4 peptides lacked monocyte and lymphocyte chemotactic activity but equally well inhibited (25 nmol/L) endothelial cell motility and proliferation in the presence of a single stimulus (i.e., exogenous recombinant fibroblast growth factor-2). In contrast, when assayed in more complex angiogenesis test systems characterized by the presence of multiple mediators, including in vitro wound-healing (2.5 nmol/L versus 12.5 nmol/L), Matrigel (60 nmol/L versus 300 nmol/L), and chorioallantoic membrane assays, CXCL4L1/PF-4var(47-70) was found to be significantly (5-fold) more angiostatic than CXCL4/PF-4(47-70). In addition, low (7 mug total) doses of intratumoral CXCL4L1/PF-4var(47-70) inhibited B16 melanoma growth in mice more extensively than CXCL4/PF-4(47-70). This antitumoral activity was predominantly mediated through inhibition of angiogenesis (without affecting blood vessel stability) and induction of apoptosis, as evidenced by immunohistochemical and fluorescent staining of B16 tumor tissue. In conclusion, CXCL4L1/PF-4var(47-70) is a potent antitumoral and antiangiogenic peptide. These results may represent the basis for the design of CXCL4L1/PF-4var COOH-terminal-derived peptidomimetic anticancer drugs. Mol Cancer Res; 8(3); 322-34

Type I collagen limits VEGFR-2 signaling by a SHP2 protein-tyrosine phosphatase-dependent mechanism 1.

During angiogenesis, a combined action between newly secreted extracellular matrix proteins and the repertoire of integrins expressed by endothelial cells contributes in the regulation of their biological functions. Extracellular matrix-engaged integrins influence tyrosine kinase receptors, thus promoting a regulatory cross-talk between adhesive and soluble stimuli. For instance, vitronectin has been reported to positively regulate VEGFR-2. Here, we show that collagen I downregulates VEGF-A-mediated VEGFR-2 activation. This activity requires the tyrosine phosphatase SHP2, which is recruited to the activated VEGFR-2 when cells are plated on collagen I, but not on vitronectin. Constitutive expression of SHP2(C459S) mutant inhibits the negative role of collagen I on VEGFR-2 phosphorylation. VEGFR-2 undergoes internalisation, which is associated with dynamin II phosphorylation. Expression of SHP2(C459S) impairs receptor internalisation suggesting that SHP2-dependent dephosphorylation regulates this process. These findings demonstrate that collagen I in provisional extracellular matrix surrounding nascent capillaries triggers a signaling pathway that negatively regulates angiogenesis

Farsighted Risk Mitigation of Lateral Movement Using Dynamic Cognitive Honeypots

Lateral movement of advanced persistent threats has posed a severe security challenge. Due to the stealthy and persistent nature of the lateral movement, defenders need to consider time and spatial locations holistically to discover latent attack paths across a large time-scale and achieve long-term security for the target assets. In this work, we propose a time-expanded random network to model the stochastic service links in the user-host enterprise network and the adversarial lateral movement. We design cognitive honeypots at idle production nodes and disguise honey links as service links to detect and deter the adversarial lateral movement. The location of the honeypot changes randomly at different times and increases the honeypots' stealthiness. Since the defender does not know whether, when, and where the initial intrusion and the lateral movement occur, the honeypot policy aims to reduce the target assets' Long-Term Vulnerability (LTV) for proactive and persistent protection. We further characterize three tradeoffs, i.e., the probability of interference, the stealthiness level, and the roaming cost. To counter the curse of multiple attack paths, we propose an iterative algorithm and approximate the LTV with the union bound for computationally efficient deployment of cognitive honeypots. The results of the vulnerability analysis illustrate the bounds, trends, and a residue of LTV when the adversarial lateral movement has infinite duration. Besides honeypot policies, we obtain a critical threshold of compromisability to guide the design and modification of the current system parameters for a higher level of long-term security. We show that the target node can achieve zero vulnerability under infinite stages of lateral movement if the probability of movement deterrence is not less than the threshold