Tag Archives: MIT

MIT Artificial Intelligence System Detects 85 Percent Of Cyber Attacks

While the number of cyber attacks continues to increase it is becoming even more difficult to detect and mitigate them in order to avoid serious consequences. A group of researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) is working on an ambitious project, the development of a technology that is able to early detect cyber attacks. The experts in collaboration with peers from the startup PatternEx have designed an Artificial Intelligence system that is able to detect 85 percent of attacks by using data from more than 3.6 Billion lines of log files each day.

The researchers have developed a system that combines an Artificial Intelligence engine with human inputs. , which researchers call Analyst Intuition (AI), which is why it has been given the name of AI2. The AI2 system first performs an automatic scan of the content with machine-learning techniques and then reports the results to human analysts which have to discriminate events linked to cyber attacks. According to the experts at the MIT the approach implemented by the AI2 system is 3 times better than modern automated cyber attack detection systems.

“The team showed that AI2 can detect 85 percent of attacks, which is roughly three times better than previous benchmarks, while also reducing the number of false positives by a factor of 5. The system was tested on 3.6 billion pieces of data known as “log lines,” which were generated by millions of users over a period of three months.” states a description of the AI2 published by the MIT.

The greater the number of analyzes carried out by the system, the more accurate the subsequent estimates thanks to the feedback mechanism.

“You can think about the system as a virtual analyst,” says CSAIL research scientist Kalyan Veeramachaneni, who developed AI2 with Ignacio Arnaldo, a chief data scientist at PatternEx and a former CSAIL postdoc. “It continuously generates new models that it can refine in as little as a few hours, meaning it can improve its detection rates significantly and rapidly.”

Source: http://ai2.appinventor.mit.edu/

Nanoparticles Cross The Blood-Brain Barrier, Shrink Glioblastoma Tumors

Glioblastoma multiforme, a type of brain tumor, is one of the most difficult-to-treat cancers. Only a handful of drugs are approved to treat glioblastoma, and the median life expectancy for patients diagnosed with the disease is less than 15 months.

MIT researchers have now devised a new drug-delivering nanoparticle that could offer a better way to treat glioblastoma. The particles, which carry two different drugs, are designed so that they can easily cross the blood-brain barrier and bind directly to tumor cells. One drug damages tumor cells’ DNA, while the other interferes with the systems cells normally use to repair such damage.

In a study of mice, the researchers showed that the particles could shrink tumors and prevent them from growing back.

What is unique here is we are not only able to use this mechanism to get across the blood-brain barrier and target tumors very effectively, we are using it to deliver this unique drug combination,” says Paula Hammond, a David H. Koch Professor in Engineering, the head of MIT’s Department of Chemical Engineering, and a member of MIT’s Koch Institute for Integrative Cancer Research.

Source: http://news.mit.edu/

Human Internal Verbalizations Understood Instantly By Computers

MIT researchers have developed a computer interface that can transcribe words that the user verbalizes internally but does not actually speak aloud. The system consists of a wearable device and an associated computing system. Electrodes in the device pick up neuromuscular signals in the jaw and face that are triggered by internal verbalizations — saying wordsin your head” — but are undetectable to the human eye. The signals are fed to a machine-learning system that has been trained to correlate particular signals with particular words. The device also includes a pair of bone-conduction headphones, which transmit vibrations through the bones of the face to the inner ear. Because they don’t obstruct the ear canal, the headphones enable the system to convey information to the user without interrupting conversation or otherwise interfering with the user’s auditory experience.

The device is thus part of a complete silent-computing system that lets the user undetectably pose and receive answers to difficult computational problems. In one of the researchers’ experiments, for instance, subjects used the system to silently report opponents’ moves in a chess game and just as silently receive computer-recommended responses.

The motivation for this was to build an IA device — an intelligence-augmentation device,” says Arnav Kapur, a graduate student at the MIT Media Lab, who led the development of the new system. “Our idea was: Could we have a computing platform that’s more internal, that melds human and machine in some ways and that feels like an internal extension of our own cognition?” “We basically can’t live without our cellphones, our digital devices,” adds Pattie Maes, a professor of media arts and sciences and Kapur’s thesis advisor. “But at the moment, the use of those devices is very disruptive. If I want to look something up that’s relevant to a conversation I’m having, I have to find my phone and type in the passcode and open an app and type in some search keyword, and the whole thing requires that I completely shift attention from my environment and the people that I’m with to the phone itself. So, my students and I have for a very long time been experimenting with new form factors and new types of experience that enable people to still benefit from all the wonderful knowledge and services that these devices give us, but do it in a way that lets them remain in the present.”

Source: http://news.mit.edu/