Category Archives: Computer Science

New Software Fights Ransomware

Ransomware, a harmful new type of malware that encrypts computer files and only releases digital information back to its rightful owners for a fee, may finally have met its match.

Much to the dismay of the increasing number of victims of cyber crime, ransomware is extremely well-suited to the current digital landscape. Hackers are paid using cryptocurrencies like bitcoin, making all illegal transactions virtually untraceable. The files that they take hostage tend to be of great value and the fees that they demand tend to be just under what it would take to pay to have the files recovered, so more often than not, desperate victims are willing to pay the ransom. Because of these advantageous circumstances, the instances of ransomware-related cybercrime have more than quadrupled over the past year, making it one of the most prevalent threats of the digital world.

cryptodrop2Luckily, scientists at the  University of Florida recently announced their development of a software that can stop ransomware in its tracks. According to the researchers, their CryptoDrop software can detect malware and stop it after has encrypted just a few files.

“Our system is more of an early-warning system,” explained Nolan Scaife, who worked with Patrick Traynor, an associate professor in UF’s department of computer and information science, to co-create the software along Henry Carter.

“It doesn’t prevent the ransomware from starting… it prevents the ransomware from completing its task… so you lose only a couple of pictures or a couple of documents rather than everything that’s on your hard drive, and it relieves you of the burden of having to pay the ransom.”

CryptoDrop has proven extremely effective in testing, during which it has flagged 100% of the malware samples and stopped it after an average of 10 files had suffered encryption.

This miracle solution couldn’t come at a more pressing time. According to the United States’ Federal Bureau of Investigation, the number of ransomware attacks has more than doubled in the past year and is expected to keep growing. The FBI further stated that it has received over 2,400 complains in 2015 and that the estimated losses from these attacks clocked in at around $24 million.

Everyone from governments to large corporations, banks, hospitals, and educational institutions have fallen victim to the attacks.

Expert at security firm Alert Logic Richard Cassidy had this to say about the recent development of CryptoDrop:

“Whilst the step taken by researchers at the University of Florida are indeed a novel way in which to detect and contain ransomware, it doesn’t serve as the ‘silver bullet’ for ransomware as a whole.”

crypt“There are new variants being written all the time,” Cassidy continued,” and ransomware writers will indeed take the time to dissect and understand how this new technology operates, creating versions that will attempt to either bypass detection, or at the very least search more effectively for likely sensitive files, before encrypting them, with the hope of having the biggest impact of securing a ransom payment.”

The UF team has a working prototype for Windows-based systems and is seeking a commercial partner for its new software.

Facebook Tacked On Suicide Prevention

This week, Facebook announced that it would be putting forth new tools for its users to use for suicide prevention. While those tools are already available in the United States, the resources are now going to be made readily accessible to users on a global scale.

The tools in Facebook’s suicide prevention arsenal are designed to help both members who are considering committing suicide or otherwise hurting themselves and the friends and families of people who are concerned about the health of their loved ones.

fb2If a Facebook user falls under any of these categories, he or she can contact the vulnerable person directly or use Facebook as an intermediary, as Facebook has recently hired entire teams of workers trained to help members in distress. According to the Global Head of Safety Antigone Davis and researcher Jennifer Guadagno, the teams are trained to help the member find help “before pain or sadness turns into something far more serious.”

Facebook’s original suicide prevention program was launched in partnership with other mental healthcare providers like Forefront, Lifeline and Suicide Awareness Voices of Education. These entities supply tools on their websites such as links to suicide prevention hotlines, links to guide users to friends, family or other professionals who might be able to comfort them and talk them through whatever situation, and links to toll-free numbers to mental health groups.

Facebook has also started to provide links to eating disorder organizations, websites offering self-care tips, and websites made for reporting cyber bullying and other unacceptable and abusive behavior. Links for parents or teachers who believe a child may be at risk are also listed.

Now that Facebook will be listing resources globally, they have organized all of these resources into local languages where members are based. For people in difficult situations where it’s a real challenge to communicate through traditional challenges, these resources can be the difference between a problem being managed and it spiraling our of control.

“The idea is that Facebook provides assistance vis a vis their network to people who are concerned about somebody,” explained Jennifer Stuber, faculty director at Forefront. “They see a post about a potential suicide or people who are suicidal, [and] they provide access to information about resources.”

fb3“Facebook has been incredibly responsive and interested in hearing from experts and users of their tools to improve them,” observed Save’s executive director Dan Reidenberg. “They have continually worked to try and help people who are in anything from a minor crisis to a major life-threatening situation, and they have developed some of the best technology and tools to save lives.”

While suicide may be an unfamiliar thought to some, almost 43,000 Americans killed themselves in 2014 alone. Tragically, suicide was the 10th leading cause of death in America overall and the second leading cause of death among those ages 15-24.

Facebook’s status as having over 1.65 billion active users makes it the world’s most powerful social network and gives it a unique and enormous opportunity to reach out to those struggling with thoughts of suicide.

Back Up; What Was the Dot Com Bubble?

As the today’s tech bubble, comprised of over-valued giants like Uber, AirBnb, and even Apple, prepares to burst (or bursts, as many are coming to say), many look to the dot com bubble as a reference point. But what was the dot com bubble, and how and why did it pop? Here’s a quick overview for those of you that are curious.

dot com bubThe “Dot Com Bubble” is said to have started in April of 1997 and spanned through June of 2003, before it popped. In order to explain how and why all of it happened, it’s first important to establish  working definition of what exactly an economic bubble even is. Let’s use the definition provided by business insider:

“An economic bubble exists whenever the price of an asset that may be freely exchanged in a well-established market first soars then plummets over a sustained period of time at rates that are decoupled from the rate of growth of the income that might reasonably be expected to be realized from owning or holding the asset.”

In other words, an economic bubble occurs when the value of something, be it a service or a company itself, becomes unrooted from what it can be consistently expected to be worth and instead its value enters a volatile and inconsistent state. According to a paper released by Zhonglan Dai, Douglas A. Shackelford, and Harold h. Zhang, this is how the Dot Com Bubble started to inflate:

rise and fall“We use the Taxpayer Relief Act of 1997 as our event to empirically test the impact of a change in the capital gains tax rate on stock return volatility. TRA97 lowered the maximum tax rate on capital gains for individual investors from 28 percent to 20 percent for assets held more than 18 months. TRA97 is particularly attractive for an event study because the capital gains tax cut was large and relatively unexpected, and the bill included few other changes that might confound our analysis. Little information was released about TRA97, until Wednesday, April 30, 1997, when the Congressional Budget Office (CBO) surprisingly announced that the estimate of the 1997 deficit had been reduced by $45 billion. Two days later, on May 2, the President and Congressional leaders announced an agreement to balance the budget by 2002 and, among other things, reduce the capital gains tax rate. These announcements greatly increased the probability of a capital gains tax cut. On Wednesday, May 7, 1997, Senate Finance Chairman William Roth and House Ways and Means Chairman William Archer jointly announced that the effective date on any reduction in the capital gains tax rate would be May 7, 1997. As promised, the lower rate on long-term capital gains (eventually set at 20 percent) became retroactively effective to May 7, 1997, when the president signed the legislation on August 5, 1997.”

The researchers then came across a stunning finding through testing stock market return data before and after May 7, 1997 (the date when investors would understand that a reduction in the capital gains tax would become effective):

“To provide more compelling evidence that the 1997 tax cut affected volatility (and mitigate concerns about omitted correlated variables), we focus on cross-sectional tests which are designed to detect the differential responses in return volatility of stocks with different characteristics. We hypothesize that the effect of a capital gains tax change on stock return volatility should vary depending upon dividend policy and the size of the unrealized capital losses (or gains). Consistent with expectations, we find that non- and lower dividend-paying stocks experienced a larger increase in return volatility than high dividend-paying stocks. We also find that stocks with large unrealized capital losses had a larger increase in return volatility after a capital gains tax rate reduction than stocks with small unrealized capital losses. However, we do not find a similar relation with unrealized capital gains.”

TRA 1997 ended up leaving dividend tax rates at the same rate as regular income in the United States, creating incentive for investors to favor low-to-no dividend paying stocks over those that paid out more significant dividends.

This came to a close when the Jobs and Growth Tax Relief Reconciliation Act of 2003 rolled around, which set both tax rates for capital gains and for dividends at equal rates once again, which they had been from 1986 to 1997. That act ended market volatility and effectively ended the Dot Com Bubble.

Chinese Aerospace Businessman Pleads Guilty in Data Conspiracy Case

Su Bin (also known as Stephen Su and Stephen Subin), a resident of the People’s Republic of China, recently pleaded guilty to participating in a conspiracy to steal sensitive military and export-controlled data from major U.S. defense contractors. The Chinese aviation and aerospace businessmen allegedly entered into a deal in which he would steal the data and then send the information to China, according to the United States Department of Justice.

su bin4Su Bin entered his plea before Judge Christina A. Snyder of the Central District of California. Bin’s original indictment was issued against him in 2014. According to the indictment, Bin was part of a criminal conspiracy to steal military technical data, including data relating to the C-17 strategic transport aircraft and a variety of other fighter jets produced for the U.S. military. Bin was arrested from Canada and transported to the United States shortly after the indictment was issued and Su waived his extradition.

“This plea sends a strong message that stealing from the United States and our companies has a significant cost; we can and will find these criminals and bring them to justice,” stated assistant attorney general for national security John P. Carlin.

Su’s plea agreement involved him admitting to conspiring with two people in China from October 2008 to March 2014 to break into protected American computer networks, including computers belonging to Boeing in Orange County, California, with the intention of stealing “sensitive” military detail and sharing it with counterparts located in China. Su’s plan was to email his co-conspirators and inform them regarding who and what to target after having penetrated a computer network, according to the Department of Justice.

Su’s co-conspirators would then send Su lists of files and folders that were successfully accessed during a network invasion. Su would then instruct the conspirators on which files and folders should be stolen of the list provided.

Su also held another skill valuable to his co-conspirators; he was able to translate stolen files and folders from English to Chinese. He could then write reports regarding the thieved data, approximating its value to its beneficiary.

su bin3Although Su in many ways played the role of a spy, at no point during the proceedings was there any mention of Su and his co-conspirators being associated with the Chinese central government.

“The plea agreement steers clear of accusing China of being behind it, even thouh Su Bin was working with two members of the military,” stated Richard Steinnon, chief research analyst with IT-Harvest.

“The two co-conspirators were identified as military officers, but it seems like these guys were moonlighting,” ventured CEO of Taia Global Jeffrey Carr. “This was not a PLA (People’s Liberation Army) operation. If it was, they wouldn’t have needed Su Bin,” he continued. “Neither would one of the co-conspirators be trying to buy malware on the dark web. The PLA doesn’t have to buy malware on the dark Web to attack a targeted company.”

The true story may be impossible for any standard onlookers to access, but it looks like either way Su Bin will be doing five years in American prison and a fine of around $250,000 for his snooping.

Toyota Creates Device for Blind People

Toyota recently announced its development of a wearable device engineered with the intention of enabling blind and visually impaired people to have greater mobility.

The gadget is a cushioned U shaped object worn around the neck, somewhat like a long and thin neck pillow. It is packed with sensors and cameras that, with the help of computers, can recognize surroundings and direct the wearer accordingly using speakers and vibration motors.

Toyota released these details last week, but the actual day that the product will become available has yet to be specified. That said, the Royal National Institute of Blind People (RNIB) has stated that it finds the creation an exciting development.

*COMPOSITE*The device owes its existence to the research and development team working on Project Blaid. According to the researchers, they’re working on plans to introduce mapping, object identification and facial recognition technologies to the device as well.

This news all came after Microsoft claimed that it was designing a headset that utilizes location and navigation data along with a network of information beacons in urban locations to verbally inform visually impaired people of where they are and how to get where they want to go in urban areas.

“This is a very exciting development within the rapidly growing field of wearable assistive technology,” stated Robin Spinks, senior strategy manager at the RNIB. “Mobility is at the heart of so much in our society and a device like Blaid could open up limitless possibilities for millions of blind and partially sighted people.”

Toyota stated during its announcement that its device was not made with the intention of replacing the aids currently available to blind and visually impaired people. The device would be complimentary to the devices already owned by any visually impaired people, and perhaps “help to fill the gaps left by canes, dogs, and basic GPS devices by providing users with more information about their surroundings.”

For example, a video that Toyota shared online demonstrated the way that the device could inform the user/wearer about the distinction between a bathroom door marked gentlemen’s toilet and another marked exit. This is a crucial detail that unfortunately no amount of hearing aids or seeing eye dogs will be able to explain to a blind or partially-sighted person.

toyotaAccording to Toyota, Project Blaid’s device is made primarily with the intention of allowing the partially-sighted or blind to navigate indoors.

“Project Blaid is one example of how Toyota is leading the way to the future of mobility, when getting around will be about more than just cars,” stated Totoya executive Simon Nagata. “We want to extend the freedom of mobility for all, no matter their circumstance, location or ability.”

Project Blaid has certainly been a team effort; Toyota apparently requested employees to submit videos of common indoor landmarks so that developers could use them to teach the device to recognize them.

Toyota is likely to also come out with an autonomous car sometime soon in the future; autonomous driving has been seen as one of the most mobilizing and empowering upcoming technologies to hit the blind and partially sighted community.

Get the Most out of Google Search

Everyone’s familiar with Google search, but not everyone knows that there’s a lot of ways to make their searching methods more effective. After all, the internet’s immense store of information is only useful so much as it can be sorted, and you have a hand in how you trigger what information is deemed important for you to see based on your question. Here are some tips on how to get to the details you want as directly and effectively as possible.

1. If you’re searching for a particular phrase, be sure to include quotation marks in your search. For example, “Here’s Johnny” or “Let them eat cake.” If you can remember most of the phrase but not all of it, put an asterisk where the missing word should be and Google will help you fill it in.

2. If you’re searching for a word with a variety of connotations, you can delete out the irrelevant results by adding a “-” and then putting all the unimportant topics that a search engine might show you. For example, if you wanted to search about red hot chili peppers but not the band, you could try typing “red hot chili peppers -music”

3. Search within a site by inputting the domain name into the service bar like so: “site:theguardian.com” If I wanted to search what CNN had to say about Bernie Sanders I could search “Bernie Sanders site:cnn.com”

site-4. Now say you have a website that you like but you want to see if there are sites similar to that one. All you have to do is write “related” and then enter a colon and the site you like. You loved neopets but need to move on? Try “related:neopets.com”

5. Maybe you have a very specific set of keywords and you only want to see search results that contain every single one of them in their text. simply write “allintext:” and then whichever words you need.

6. Similarly, you can use the “allintitle” function to search words that you specifically want to see in the title of any document that comes up. If you want to search some key words that can occur throughout the document and some that you want in the title, you can do that too using “intitle”  like this: “jerry garcia intitle:death”.

7. Last iteration: use allinurl: for… you get it. For example “allinurl:chimmychonga”.

8. Search for news related to a particular location with “location:”, like you could search “Hillary Clinton location:Iowa”.

choco cake9. Search only for certain file types by adding “filetype:” like “filetype:mp3” or “filetype:pdf”.

10. This one really helps with shopping: search only for results with numbers between a certain range by adding two periods between the lowest and highest number. “used canoe $200..$600”.

Now you’re all grown up and ready to use the Google search engine to the best of yours and its ability. Good luck with all your searching efforts and may you find all the information that you need to fulfill your life and move on to the next step! You can do it, I bet!

Wikipedia Develops Application with AI

The Wikimedia Foundation just released a new service engineered to heighten the accuracy and detail of Wikipedia articles.

Known as the Objective Revision Evaluation Service (ORES), the application uses artificial intelligence (AI) and machine learning (ML) to help Wikipedia editors to identify bad articles with faster speeds and assign them with appropriate scores almost immediately.

Unknown to most Wikipedia users, Wikipedia is actively edited over 500,000 times a day. Volunteer editors must then review those changes, making a lot of man power necessary to keep the site alive and accurate.

oresORES makes it easier for these editors to look through and organize incoming content, identify poor edits and mark them for further scrutiny. Bad edits occur often and range from the deletion of accurate information, addition of inaccurate information, addition of an opinion and addition of an obscenity.

Principal analyst of the Enderle Group Rob Enderle had this to say: “If you’re in the media at all, there’s a chance that someone is going to dislike something that you said and is going to try to damage your Wikipedia page.”

“Low-level AI is really good at identifying patterns and taking prescribed action against the patterns it recognizes. Unless you have a ton more people than Wikipedia has, you’d never be able to keep up with the bad edits. Wikipedia can be more trusted and less likely to be used as a tool to harm somebody [now that it has developed ORES]).”

Wikimedia Senior Research Scientist Aaron Halfaker reiterated the improvement in accuracy and timely edits that ORES is sure to bring: “That allows the editor to review the most likely to be damaging edits first. That can reduce the workload of reviewing edits by about 90 percent.”

So how does it work? ORES is engineered in such a way that it can predict the probability that an edit is damaging by checking in on the before-and-after edits common to all articles that appear on Wikipedia. It then assigns a score to a proposed edit depending on its likelihood of being damaging.

half“Our machine learning model is good enough at sorting those edits by the probability that they’re damaging that you would have to review 10 percent of the incoming edits to know that you caught all of the damaging edits,” continued Halfaker. “Without this tool, you’d have to review all the edits to know you caught all the damaging edits.”

“One of the reasons we want to reduce the workload around quality control is so that editors can spend more of their time working on new article content rather than removing vandalism.”

Despite Wikipedia’s reception of about 12 million hours of volunteer labor a year, they could never get enough volunteers to manage all of the internet vandalism that occurs under their business model in a timely and reliable manner.

Transistors; The Brain Cells of Computers

Like the neurons in human brains, billions of transistors allow for your computer to function. Despite having been invented 50 years ago, little is known about transistors by the general public; here’s a quick rundown to get you up to date.

Transistors are electronic components made of silicon. They can work either as amplifiers or switchers. Let’s start with their work as amplifiers:

Transistors are capable of receiving a small electric current at their input and releasing a much larger electric current at their output. This was first utilized for hearing aids; the transistors allowed for the electric currents generated by tiny microphones worn in the ear to then be converted into much louder sounds played out of a tiny loudspeaker.

Transistors can also function as switches in that the small current entering at the input then switches on a larger current that exits out the output. This is fundamental to how computer circuit boards function; whether or not a transistor is switched on (a current is run through it) can be read as a 0 or a 1, allowing for binary code to be stored via the presence or absence of an electric current. Computer chips contain billions of transistors.

transistor under microscopeBecause there are so many transistors, they have to be extremely tiny and correspond to extremely tiny electrical currents to all fit inside your smartphone. The most advances (and tiny) transistors work by controlling the movements of individual electrons, so they end up being so small you could fit 500 million to two billion on the surface of your fingernail.

You may be wondering how you even make something so small. Here’s how:

As mentioned before, transistors are made out of silicon, which is normally an insulator but in this case has been transformed into a semiconductor by introducing impurities (a process called chemical doping) into the material. The process works by either removing electrons from the silicon and making it more prone to being positively charged (called p-type) or adding electrons to make it more prone to being negatively charged (called n-type).

Once you’ve set up your two types of silicon, you can stick them together and fashion for yourself a kind of silicon sandwich; the junction between the two materials will become normal silicon because the lack and abundance of electrons will start to even out. Now you’ve got a diode (also called a rectifier). Diodes only allow for currents to flow through them in one direction because of the properties of the junction between the two slabs of different-typed silicon.

transistor under micro2To make a junction transistor, you have to actually use three layers of typed silicon, meaning your options are p-n-p or n-p-n. “Once electrical contacts are attached to all three layers, the component will either amplify a current or switch it on or off.

Check out a n-p-n transistor: let’s call the two contacts connected to the n-type silicon the emitter and the collector, and let’s call the contact connected to the p-type the base. Given that a small positive voltage is applied to the base, while the emitter is made negative and the collector is made positive, electrons are going to be pulled from the emitter into the base and then from the base to the collector. That means the transistor is turned on.

Remember that the base current can switch the amplified current on or off. It needs to be outfitted with a positive charge for the current to be amplified on its journey from the emitter to the collector.