Edmond  Herzog

Edmond Herzog

1596478860

A Look at Deepfakes in 2020

Deepfakes are synthetic media, usually videos, created with deep learning technology. By manipulating images, videos, and voices of real people, a deepfake can portray someone doing things they never did, or saying things they never said.

By feeding a machine learning model thousands of target images, a deepfake algorithm can learn the details of a person’s face. With enough training data, the algorithm can then predict what that person’s face would look like when mimicking the expressions of someone else. A similar process is used for training deepfake algorithms to mimic the accent, intonation, and tone of a person’s voice.

The Public Response to Deepfakes

The start of 2020 came with an interesting shift in response to deepfake technology, when Facebook announced a ban on manipulated videos and images on their platforms. Facebook said it would remove AI-edited content that was likely to mislead people, but added that the ban doesn’t include parody or satire. Lawmakers, however, are skeptical as to whether the ban goes far enough to address the root problem: the ongoing spread of disinformation.

The speed and ease with which a deepfake can be made and deployed, as shown in this article by Ars Technica, have many worried about misuse in the near future, especially with an election on the horizon for the U.S. Many in America, including military leaders, have also weighed in with worries about the speed and ease with which the tech can be used. These concerns are heightened by the knowledge that deepfake technology is improving and becoming more accessible.

#deepfake-technology #ai #deepfakes #machine-learning #synthetic-media

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A Look at Deepfakes in 2020
Brain  Crist

Brain Crist

1594753020

Citrix Bugs Allow Unauthenticated Code Injection, Data Theft

Multiple vulnerabilities in the Citrix Application Delivery Controller (ADC) and Gateway would allow code injection, information disclosure and denial of service, the networking vendor announced Tuesday. Four of the bugs are exploitable by an unauthenticated, remote attacker.

The Citrix products (formerly known as NetScaler ADC and Gateway) are used for application-aware traffic management and secure remote access, respectively, and are installed in at least 80,000 companies in 158 countries, according to a December assessment from Positive Technologies.

Other flaws announced Tuesday also affect Citrix SD-WAN WANOP appliances, models 4000-WO, 4100-WO, 5000-WO and 5100-WO.

Attacks on the management interface of the products could result in system compromise by an unauthenticated user on the management network; or system compromise through cross-site scripting (XSS). Attackers could also create a download link for the device which, if downloaded and then executed by an unauthenticated user on the management network, could result in the compromise of a local computer.

“Customers who have configured their systems in accordance with Citrix recommendations [i.e., to have this interface separated from the network and protected by a firewall] have significantly reduced their risk from attacks to the management interface,” according to the vendor.

Threat actors could also mount attacks on Virtual IPs (VIPs). VIPs, among other things, are used to provide users with a unique IP address for communicating with network resources for applications that do not allow multiple connections or users from the same IP address.

The VIP attacks include denial of service against either the Gateway or Authentication virtual servers by an unauthenticated user; or remote port scanning of the internal network by an authenticated Citrix Gateway user.

“Attackers can only discern whether a TLS connection is possible with the port and cannot communicate further with the end devices,” according to the critical Citrix advisory. “Customers who have not enabled either the Gateway or Authentication virtual servers are not at risk from attacks that are applicable to those servers. Other virtual servers e.g. load balancing and content switching virtual servers are not affected by these issues.”

A final vulnerability has been found in Citrix Gateway Plug-in for Linux that would allow a local logged-on user of a Linux system with that plug-in installed to elevate their privileges to an administrator account on that computer, the company said.

#vulnerabilities #adc #citrix #code injection #critical advisory #cve-2020-8187 #cve-2020-8190 #cve-2020-8191 #cve-2020-8193 #cve-2020-8194 #cve-2020-8195 #cve-2020-8196 #cve-2020-8197 #cve-2020-8198 #cve-2020-8199 #denial of service #gateway #information disclosure #patches #security advisory #security bugs

Shawn  Durgan

Shawn Durgan

1597068204

Qualcomm Bugs Open 40 Percent of Android Handsets to Attack

Researchers identified serious flaws in Qualcomm’s Snapdragon SoC and the Hexagon architecture that impacts nearly half of Android handsets.

Six serious bugs in Qualcomm’s Snapdragon mobile chipset impact up to 40 percent of Android phones in use, according research released at the DEF CON Safe Mode security conference Friday.

The flaws open up handsets made by Google, Samsung, LG, Xiaomi and OnePlus to DoS and escalation-of-privileges attacks – ultimately giving hackers control of targeted handsets. Slava Makkaveev, a security researcher with Check Point, outlined his discoveryand said while Qualcomm has provided patches for the bug, most OEM handset makers have not yet pushed out the patches.

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The faulty Qualcomm component is the mobile chip giant’s Snapdragon SoC and the Hexagon architecture. Hexagon a brand name for Qualcomm’s digital signal processor (DSP), part of the SoC’s microarchitecture. DSP controls the processing of real-time request between the Android user environment and the Snapdragon processor’s firmware – in charge of turning voice, video and services such GPS location sensors into computationally actionable data.

Makkaveev said the DSP flaws can be used to harvest photos, videos, call recordings, real-time microphone data, and GPS and location data. A hacker could also cripple a targeted phone or implant malware that would go undetected.

The six flaws are CVE-2020-11201, CVE-2020-11202, CVE-2020-11206, CVE-2020-11207, CVE-2020-11208 and CVE-2020-11209. Using a fuzzing technique against handsets with the vulnerable chipset, Check Point was able to identify 400 discrete attacks.

The prerequisite for exploiting the vulnerabilities is the target would need to be coaxed into downloading and running a rogue executable.

Qualcomm declined to answer specific questions regarding the bugs and instead issued a statement:

“Providing technologies that support robust security and privacy is a priority for Qualcomm. Regarding the Qualcomm Compute DSP vulnerability disclosed by Check Point, we worked diligently to validate the issue and make appropriate mitigations available to OEMs. We have no evidence it is currently being exploited. We encourage end users to update their devices as patches become available and to only install applications from trusted locations such as the Google Play Store.” – Qualcomm Spokesperson

The flaws were brought to Qualcomm’s attention between February and March. Patches developed by Qualcomm in July. A cursory review of vulnerabilities patched in the July and August Google Android Security Bulletins reveal patches haven’t been yet been pushed to handsets. For that reason, Check Point chose not to reveal technical specifics of the flaws.

What technical details that are available can be found in a DEF CON Safe Mode video posted to online. Here Makkaveev shares some technical specifics.

#hacks #mobile security #vulnerabilities #cve-2020-11201 #cve-2020-11202 #cve-2020-11206 #cve-2020-11207 #cve-2020-11208 #cve-2020-11209 #def con safe mode #digital signal processor #dos #dsp #escalation of privileges attack #google #hexagon architecture #lg #oneplus #qualcomm #samsung #snapdragon #soc #xiaomi

Edmond  Herzog

Edmond Herzog

1596478860

A Look at Deepfakes in 2020

Deepfakes are synthetic media, usually videos, created with deep learning technology. By manipulating images, videos, and voices of real people, a deepfake can portray someone doing things they never did, or saying things they never said.

By feeding a machine learning model thousands of target images, a deepfake algorithm can learn the details of a person’s face. With enough training data, the algorithm can then predict what that person’s face would look like when mimicking the expressions of someone else. A similar process is used for training deepfake algorithms to mimic the accent, intonation, and tone of a person’s voice.

The Public Response to Deepfakes

The start of 2020 came with an interesting shift in response to deepfake technology, when Facebook announced a ban on manipulated videos and images on their platforms. Facebook said it would remove AI-edited content that was likely to mislead people, but added that the ban doesn’t include parody or satire. Lawmakers, however, are skeptical as to whether the ban goes far enough to address the root problem: the ongoing spread of disinformation.

The speed and ease with which a deepfake can be made and deployed, as shown in this article by Ars Technica, have many worried about misuse in the near future, especially with an election on the horizon for the U.S. Many in America, including military leaders, have also weighed in with worries about the speed and ease with which the tech can be used. These concerns are heightened by the knowledge that deepfake technology is improving and becoming more accessible.

#deepfake-technology #ai #deepfakes #machine-learning #synthetic-media

Mikel  Okuneva

Mikel Okuneva

1603735200

Top 10 Deep Learning Sessions To Look Forward To At DVDC 2020

The Deep Learning DevCon 2020, DLDC 2020, has exciting talks and sessions around the latest developments in the field of deep learning, that will not only be interesting for professionals of this field but also for the enthusiasts who are willing to make a career in the field of deep learning. The two-day conference scheduled for 29th and 30th October will host paper presentations, tech talks, workshops that will uncover some interesting developments as well as the latest research and advancement of this area. Further to this, with deep learning gaining massive traction, this conference will highlight some fascinating use cases across the world.

Here are ten interesting talks and sessions of DLDC 2020 that one should definitely attend:

Also Read: Why Deep Learning DevCon Comes At The Right Time


Adversarial Robustness in Deep Learning

By Dipanjan Sarkar

**About: **Adversarial Robustness in Deep Learning is a session presented by Dipanjan Sarkar, a Data Science Lead at Applied Materials, as well as a Google Developer Expert in Machine Learning. In this session, he will focus on the adversarial robustness in the field of deep learning, where he talks about its importance, different types of adversarial attacks, and will showcase some ways to train the neural networks with adversarial realisation. Considering abstract deep learning has brought us tremendous achievements in the fields of computer vision and natural language processing, this talk will be really interesting for people working in this area. With this session, the attendees will have a comprehensive understanding of adversarial perturbations in the field of deep learning and ways to deal with them with common recipes.

Read an interview with Dipanjan Sarkar.

Imbalance Handling with Combination of Deep Variational Autoencoder and NEATER

By Divye Singh

**About: **Imbalance Handling with Combination of Deep Variational Autoencoder and NEATER is a paper presentation by Divye Singh, who has a masters in technology degree in Mathematical Modeling and Simulation and has the interest to research in the field of artificial intelligence, learning-based systems, machine learning, etc. In this paper presentation, he will talk about the common problem of class imbalance in medical diagnosis and anomaly detection, and how the problem can be solved with a deep learning framework. The talk focuses on the paper, where he has proposed a synergistic over-sampling method generating informative synthetic minority class data by filtering the noise from the over-sampled examples. Further, he will also showcase the experimental results on several real-life imbalanced datasets to prove the effectiveness of the proposed method for binary classification problems.

Default Rate Prediction Models for Self-Employment in Korea using Ridge, Random Forest & Deep Neural Network

By Dongsuk Hong

About: This is a paper presentation given by Dongsuk Hong, who is a PhD in Computer Science, and works in the big data centre of Korea Credit Information Services. This talk will introduce the attendees with machine learning and deep learning models for predicting self-employment default rates using credit information. He will talk about the study, where the DNN model is implemented for two purposes — a sub-model for the selection of credit information variables; and works for cascading to the final model that predicts default rates. Hong’s main research area is data analysis of credit information, where she is particularly interested in evaluating the performance of prediction models based on machine learning and deep learning. This talk will be interesting for the deep learning practitioners who are willing to make a career in this field.


#opinions #attend dldc 2020 #deep learning #deep learning sessions #deep learning talks #dldc 2020 #top deep learning sessions at dldc 2020 #top deep learning talks at dldc 2020

Mitchel  Carter

Mitchel Carter

1603036800

Google’s Chrome 86: Critical Payments Bug, Password Checker Among Security Notables

Google’s latest version of its browser, Chrome 86, is now being rolled out with 35 security fixes – including a critical bug – and a feature that checks if users have any compromised passwords.

As of Tuesday, Chrome 86 is being promoted to the stable channel for Windows, Mac and Linux and will roll out over the coming days. The versions of the browser for Android and iOS were also released Tuesday, and will become available on Google Play and the App Store this week.

Included in the newest browser version is a critical flaw (CVE-2020-15967) existing in Chrome’s payments component. The flaw, reported by Man Yue Mo of GitHub Security Lab, is a use-after-free vulnerability. Use after free is a memory-corruption flaw where an attempt is made to access memory after it has been freed. This can cause an array of malicious impacts, from causing a program to crash, to potentially leading to execution of arbitrary code.

Use-after-free bugs have plagued Google Chrome in the past year. In fact, all seven high-severity vulnerabilities fixed by Google in Chrome 86 were use-after-free flaws – ranging from ones affecting Chrome’s printing (CVE-2020-15971), audio (CVE-2020-15972), password manager (CVE-2020-15991) and WebRTC (CVE-2020-15969) components (WebRTC is a protocol for rich-media web communication).

Further details of the bugs are not yet available, as “access to bug details and links may be kept restricted until a majority of users are updated with a fix,” according to Google’s Tuesday post.

Password Check

The Android and iOS versions of Chrome 86 will also come with a new security feature, which will send a copy of user’s usernames and passwords using a “special form of encryption.” That then lets Google check them against list of passwords known to be compromised.

“Passwords are often the first line of defense for our digital lives,” Abdel Karim Mardini, senior product manager with Chrome, said in a Tuesday post. “Today, we’re improving password security on both Android and iOS devices by telling you if the passwords you’ve asked Chrome to remember have been compromised, and if so, how to fix them.”

At the back end, when Google detects a username and password exposed by a data breach, it stores a strongly hashed and encrypted copy of the data. Then, when Chrome users log into a website, the feature sends a strongly hashed and encrypted version of their username and password to Google – meaning the company never derives usernames or passwords from the encrypted copy, it said.

#vulnerabilities #web security #android #chrome #chrome 86 #compromised password #credential stuffing #cve-2020-15967 #cve-2020-15969 #cve-2020-15971 #cve-2020-15972 #cve-2020-15991 #encryption #google #google payments #https #ios #linux #mac #password check #patches #safety check #security fix #security improvements #windows