Another Top Search Number 21 on my blog

Another Top search
Another Top Search Number 21 on my blog :

“Security Risk management in healthcare over cloud” on google
My blog on top

https://sandyclassic.wordpress.com/2014/04/10/security-risk-management-in-healthcare-on-cloud/

Wireless Security Analytics- Approach

How To model wireless security mathematically. (its topmost search in Google Type(Wireless Sensor network Security Analytics) Result:
TopMostSearchWirelessSensorNetworkSecurityAnalyticsRead:

1. Go through the Slides about Modelling the Wireless sensor Network and Internet of Things

  • 10 PROJECT GOALS 1. Routing algorithm: SPIN,CTP. 2. measure energy consumed 3. Validate PPECEM Model 4. Improve in existing model for efficiency, reliability, availability.
  • 2. 10 PROJECT GOALS 5. New Model: ERAECEM Efficiency Reliability Availability Energy consumption Estimation Model. 6. ERAQP BASED on ERAECEM Model for WSN a new energy aware routing algorithm (ERAQP)
  • 3. 10 PROJECT GOALS 7. Configurable Routing Algorithm Approach Proposed on WSN motes utilizing user defined QoS parameters 8. Model for WSN: Leader-Follower Model, Directed Diffusion Model
  • 4. 10 PROJECT GOALS 9. Fuzzy routing Algorithm 10. Fuzzy Information Neural Network representation of Wireless Sensor Network.
  • 5. MOTIVATION
  • 6. 1.1 SPIN
  • 7. 1.2 CTP  Collection tree protocol
  • 8. 2 ENERGY MEASUREMENT  Agilent 33522B Waveform Generator was used to measure the Current and voltage graph .  The Graph measurement were then converted to numerical power Power= Voltage X current = V X I. The Power consumed during motes routing on SPIN and CTP then taken into is added up to give power consumption and values are applied to PPECEM.
  • 9. 1.3 WSN SECURITY
  • 10. 3.1COST OF SECURITY  Cost of security In WSN can only be estimated by looking at extra burden of secure algorithm and security of Energy Consumption as the Energy is key driver or critical resource in design of WSN. As design is completely dominated by size of battery supplying power to mote.
  • 11. 3.2 PPECEM  QCPU = PCPU * TCPU = PCPU * (BEnc * TBEnc + BDec * TBDec +BMac * TBMac + TRadioActive) Eq.2)
  • 12. 4 ERA  Efficiency = Ptr X Prc X Pcry … (Eq.2)  Reliability = Rnode1 = FtrX FrcX Fcy  Availability= TFNode1 = Ftr+ Frc+Fcry
  • 13. 5. IMPROVE EXISTING  . ERA = fed  Efficiency of Energy Model: QEff=QCPU X Eff (improvement #1 in Zang model)
  • 14. ERAECEM  Etotal = Average(Eff + R +A)= (E+R+A)/3  Efficiency of Energy Model: QEff=QCPU X Etotal (improvement #1 in Zang model)
  • 15. 6 ERAQP  Efficiency ,Reliability, Availability QoS prioritized routing Algorithm  ERA ranked and routing based Ranking Cost on Dijesktra to find most suitable path
  • 16. 7.CONFIG. ROUTING  q1, q2, q3 as QoS parameter algorithm rank Motes/nodes based on combined score of these parameters. Based on this we rank we apply Dijesktra algorithm to arrive at least path or elect Cluster head to node. Thus q1, q2, q3 can be added, deleted.
  • 17. 8 MATHEMATICAL MODEL  Leader Follower EACH node share defined diffusion rate given by slider control on UI which tells quantity it is diffusing with its neighbors.Since it’s a directed graph so Node B gives data towards Node A while traffic from A towards B may be non-existent  Directed Diffusion Mathematical model represent diffusion of quantity towards a directed network. Helps to understand topology, density and stability of network and a starting point for designing complex , realistic Network Model.
  • 18. 9 FUZZY ROUTING  Fuzzy set A {MoteA, p(A))  Where, p(A) is probability Of Data Usage Or Percentage Load in Fraction Compared With Global Load
  • 19. 10 FUZZY TOPOLOGY  Based on this Utilization p(A) nodes can be ranked in ascending order to find most data dwarfed node at the top. Then We can apply Dijkstra’s algorithm on the network to find best route based on weight on each node represented by Rank.

2. WSN and BPEL and Internet Of Things (IoT)
https://sandyclassic.wordpress.com/2013/10/06/bpm-bpel-and-internet-of-things/

3. Internet Of Things (IoT) and effects on other device ecosystem.
The Changing Landscape:
https://sandyclassic.wordpress.com/2013/10/01/internet-of-things/

4. How application development changes with IoT, Bigdata, parallel computing, HPC High performance computing.
https://sandyclassic.wordpress.com/2013/09/18/new-breed-of-app-development-is-here/

5. Landslide detection and mpact reduction using wireless sensor network.
https://sandyclassic.wordpress.com/2013/06/23/landslide-detection-impact-reduction-using-wireless-sensor-network

6. Mathematical modelling Energy Wireless sensor Network.
https://sandyclassic.wordpress.com/2014/02/04/mathematical-modelling-energy-security-of-wireless-sensor-network/

New Breed of App development is here

Here are reasons Why next generation app will be totally different:
1. – In few years we will be seeing ending dominance of physical routers, switches , firewall to virtual soft switches, virtual routers , software defined routers and switches. More open routing technology would be program driven rather than configuration on boxes.
Companies like application firewall maker Palo Alto Networks and virtual programmable router maker nicira have huge role to play.
https://sandyclassic.wordpress.com/2012/07/16/cloud-innovation-heating-up-network-protocol-stack-and-telecom-stack/

its also affected by trends in Network technology
https://sandyclassic.wordpress.com/2012/09/11/trends-in-computer-networking-and-communication-2/
2. – in next year we will see 20+ processors on single machine making parallel processing one of important requirement. Huge software would be re written to meet this requirement.
https://sandyclassic.wordpress.com/2012/11/11/parallel-programming-take-advantage-of-multi-core-processors-using-parallel-studio/

3. The changes in business and systems are occurring very fast as system and getting more understood and cross functional due to intense competition Where only innovation can make you stay ahead of curve: Read more reasons why?
https://sandyclassic.wordpress.com/2013/09/16/new-age-enterprise-resource-planning-systems/

4. Cloud will increase innovation to change way we think about software:
Software As service SAAS, PAAS, IAAS going to make more deeper innovation as defined in above article (https://sandyclassic.wordpress.com/2013/07/02/data-warehousing-business-intelligence-and-cloud-computing/).
How innovation on cloud will be much quicker read :
https://sandyclassic.wordpress.com/2013/07/02/data-warehousing-business-intelligence-and-cloud-computing/

5. Laptop will never go (large screen requirement) but Mobile will be mass platform:
As we can move we can see virtually wearable shirts made of graphene with storage and data streamed on walls .. as when we want we can just grab wall data to graphene shirts..
Read more about Graphene: https://sandyclassic.wordpress.com/2013/01/18/graphene-the-wonder-material-foldable-cell-phones-wearable-computerbionic-devices-soon-reality/
surfaces will keep emerging we would see virtually display in air without any device but what it would be added with augmented reality and virtual reality.
https://sandyclassic.wordpress.com/2012/06/27/future-of-flex-flash-gamification-of-erp-enterprise-software-augmented-reality-on-mobile-apps-iptv/
we can in future just stream data to wall and program on wall outside our house.
6. Internet of things : where Machine to machine transfer of information and data and semantic web will make possible more intelligent feedback to user by all devices based on user need. so when you pick up milk from shelf next time. your fridge will search for you and alert you on latest offer of cheapest milk from various retailer.
And it will be displayed on fridge itself.. not only that it would order for you when its empty if you configure so. it will calculate you calorie consumed by family of fridge item and send updates to doctor monitoring you and display return messages from doctors.
More: https://sandyclassic.wordpress.com/2013/05/03/classifying-ubiquitious-data-images-into-emotion-for-target-advertisement-campaign/
7. Sensors will be everywhere and huge and Ubiquity will rule :
https://sandyclassic.wordpress.com/2012/10/28/ubiquity-the-most-crucial-challenge-in-business-intelligence/

Authentication market segment and future

Electronic authentication (e-authentication) is the process of establishing confidence in user identities electronically presented to an information system.

Authentication provider Market size estimated by Gartner estimate stand at 2 billion dollar growing at average 30% year on year with about 150 vendors.

Authentication technologies companies can be segmented to 3 types :

  1. Client-side software or hardware, such as PC middleware, smart cards and biometric capture devices (sensors)
  2. Software, hardware or a service, such as access management or Web fraud detection (WFD), that makes a real-time access decision and may interact with discrete user authentication software, hardware or services (for example, to provide “step up” authentication)
  3. Credential management software, hardware or services, such as password management tools, card management (CM) tools and public-key infrastructure (PKI) certification authority (CA) and registration authority (RA) tools (including OCSP responders)
  4. Software, hardware or services in other markets, such as Web access management (WAM) or VPN, that embed native support for one or many authentication method.

Specialist vendor provide SDK,while commodity vendor provide one-time password (OTP) tokens (hardware or software) and out of band (OOB) authentication methods.

Shift is happening in industry from traditional hardware tokens to phone-based authentication methods or supporting knowledge-based authentication (KBA) methods or X.509 tokens (such as smart cards). NIST defines three types of authentication methods:

Agile project management for security project

As Agile project management incorporates principles of Lean techniques , kaban and six sigma into software development life cycle. Lean comes into picture as instead of huge inventory of requirements getting stacked in Product/Project Backlog an inventory is kept as small or as lean as possible. Security feature or requirements are more costly if not caught early in life cycle or product development life cycle. Paper discusses lean management of security requirements. Also application of Security Testing Methodology , application of Security patterns anti-patterns to increase Reuse and reduce time and reduce cost.

UserStoryScrum

click to download document in word format: