Anurag RANA

War continues to spread online. Known as cyberwarfare, the spread of malicious online viruses just may be the future of war. Cyber attacks continue to grow in number and sophistication each year. In 2006, Russian Mafia group Russian Business Network (RBN) began using malware for identity theft. By 2007, RBN completely monopolized online identity theft. By September 2007, their Storm Worm was estimated to be running on roughly one million computers, sending millions of infected emails each day. In 2008, cyber attacks moved from personal computers to government institutions. On August 27, 2008 NASA confirmed a worm had been found on laptops in the International Space Station; three months later Pentagon computers were hacked, allegedly by Russian hackers. Financial institutions were next. The State Bank of India (India'’s largest bank) was attacked by hackers located in Pakistan on December 25, 2008. While no data was lost, the attack forced SBI to temporarily shut do

USB encryption Almost half the respondents were lacking when it came to USB encryption. They failed to ensure that data from a device connecting to end points via USB was sufficiently encrypted, were it to end up in an unsecured or hostile environment. Third party device connectivity Some 35% of organizations aren’t controlling end point connectivity solutions like SD cards, Bluetooth, and Fire Wire, to limit the threats they potentially bring. USB control USB devices can be a significant vector for the distribution of cyber attacks. However, over 35% of respondents don’t control or limit any device connecting to end points via USB. Data loss prevention Some 37% of companies have no assurance against loss of information, documents, and IP. Reverse engineering of malware Only 39% of organizations are actively working on reverse engineering of malware, while 32% are still in an initial phase of developing this. Emergency response team Only 16% o

What are Artificial Neural Networks? Artificial Neural Networks are relatively crude electronic models based on the neural structure of the brain. The brain basically learns from experience. It is natural proof that some problems that are beyond the scope of current computers are indeed solvable by small energy efficient packages. This brain modeling also promises a less technical way to develop machine solutions. This new approach to computing also provides a more graceful degradation during system overload than its more traditional counterparts. These biologically inspired methods of computing are thought to be the next major advancement in the computing industry. Even simple animal brains are capable of functions that are currently impossible for computers. Computers do rote things well, like keeping ledgers or performing complex math. But computers have trouble recognizing even simple patterns much less generalizing those patterns of the past into actions of the future.

Amended Fruit fly Optimization According to food finding characteristics of fruit fly swarm, the whole procedure of the original FOAcan be divided into several step as follows:- ALGORITHM FOR aFOA Step 1 Start:             Start the algorithm. Step 2 Parameter Initialization:                      The main parameters of aFOA are maximum iteration number, the population size. Step 3 Population Initialization:             Randomly initialize the population size is NP. Randomly produce solution, half blending and un-blending. Step 4 Neighborhood Generations and Find Best            Neighborhood:             NN neighborhoods are randomly generated. NN neighborhoods are produced by three kinds of neighborhood search. Find out the best neighbor. Step 5 Replacements of Neighbor:             If the best neighbor is better than the fly then replace the fly with the best neighbor and go to next step, else go to next step without replacing. Step 6 Local Neig