Vishing is the criminal practice of using social engineering and Voice over IP (VoIP) to gain access to private personal and financial information from the public for the purpose of financial reward. The term is a combination of “voice” and phishing. Vishing exploits the public’s trust in landline telephone services, which have traditionally terminated in physical locations which are known to the telephone company, and associated with a bill-payer. The victim is often unaware that VoIP allows for caller ID spoofing, inexpensive, complex automated systems and anonymity for the bill-payer. Vishing is typically used to steal credit card numbers or other information used in identity theft schemes from individuals.

Vishing is very hard for legal authorities to monitor or trace. To protect themselves, consumers are advised to be highly suspicious when receiving messages directing them to call and provide credit card or bank numbers. Rather than provide any information, the consumer is advised to contact their bank or credit card company directly to verify the validity of the message.

There is technology that monitors all PSTN based traffic and can identify vishing attempts as a result of patterns and anomalies in call activity. One example is a multiple calls from a limited set of skype numbers to call centers.

Google File System (GFS) is a proprietary distributed file system developed by Google for its own use. It is designed to provide efficient, reliable access to data using large clusters of commodity hardware.

GFS is optimized for Google’s core data storage and usage needs (primarily the search engine), which can generate enormous amounts of data that needs to be retained; Google File System grew out of an earlier Google effort, “BigFiles”, developed by Larry Page and Sergey Brin in the early days of Google, while it was still located in Stanford.Files are divided into chunks of 64 megabytes, which are only extremely rarely overwritten, or shrunk; files are usually appended to or read. It is also designed and optimized to run on Google’s computing clusters, the nodes of which consist of cheap, “commodity” computers, which means precautions must be taken against the high failure rate of individual nodes and the subsequent data loss. Other design decisions select for high data throughputs, even when it comes at the cost of latency.

The nodes are divided into two types: one Master node and a large number of Chunkservers. Chunkservers store the data files, with each individual file broken up into fixed size chunks (hence the name) of about 64 megabytes, similar to clusters or sectors in regular file systems. Each chunk is assigned a unique 64-bit label, and logical mappings of files to constituent chunks are maintained. Each chunk is replicated several times throughout the network, with the minimum being three, but even more for files that have high demand or need more redundancy.

The Master server doesn’t usually store the actual chunks, but rather all the metadata associated with the chunks, such as the tables mapping the 64-bit labels to chunk locations and the files they make up, the locations of the copies of the chunks, what processes are reading or writing to a particular chunk, or taking a “snapshot” of the chunk pursuant to replicating it (usually at the instigation of the Master server, when, due to node failures, the number of copies of a chunk has fallen beneath the set number). All this metadata is kept current by the Master server periodically receiving updates from each chunk server (“Heart-beat messages”).

Permissions for modifications are handled by a system of time-limited, expiring “leases”, where the Master server grants permission to a process for a finite period of time during which no other process will be granted permission by the Master server to modify the chunk. The modified chunkserver, which is always the primary chunk holder, then propagates the changes to the chunkservers with the backup copies. The changes are not saved until all chunkservers acknowledge, thus guaranteeing the completion and atomicity of the operation.

Programs access the chunks by first querying the Master server for the locations of the desired chunks; if the chunks are not being operated on (if there are no outstanding leases), the Master replies with the locations, and the program then contacts and receives the data from the chunkserver directly (similar to Kazaa and its supernodes).

As opposed to many filesystems, it’s not implemented in the kernel of an Operating System but accessed through a library to avoid overhead.