Tight Arms Race: Overview of Current Malware Threats and Trends in Their Detection

Cyber attacks are currently blooming, as the attackers reap significant profits from them and face a limited risk when compared to committing the "classical" crimes. One of the major components that leads to the successful compromising of the targeted system is malicious software. It allows using the victim's machine for various nefarious purposes, e.g., making it a part of the botnet, mining cryptocurrencies, or holding hostage the data stored there. At present, the complexity, proliferation, and variety of malware pose a real challenge for the existing countermeasures and require their constant improvements. That is why, in this paper we first perform a detailed meta-review of the existing surveys related to malware and its detection techniques, showing an arms race between these two sides of a barricade. On this basis, we review the evolution of modern threats in the communication networks, with a particular focus on the techniques employing information hiding. Next, we present the bird's eye view portraying the main development trends in detection methods with a special emphasis on the machine learning techniques. The survey is concluded with the description of potential future research directions in the field of malware detection

Completely Automated Public Physical test to tell Computers and Humans Apart: A usability study on mobile devices

A very common approach adopted to fight the increasing sophistication and dangerousness of malware and hacking is to introduce more complex authentication mechanisms. This approach, however, introduces additional cognitive burdens for users and lowers the whole authentication mechanism acceptability to the point of making it unusable. On the contrary, what is really needed to fight the onslaught of automated attacks to users data and privacy is to first tell human and computers apart and then distinguish among humans to guarantee correct authentication. Such an approach is capable of completely thwarting any automated attempt to achieve unwarranted access while it allows keeping simple the mechanism dedicated to recognizing the legitimate user. This kind of approach is behind the concept of Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA), yet CAPTCHA leverages cognitive capabilities, thus the increasing sophistication of computers calls for more and more difficult cognitive tasks that make them either very long to solve or very prone to false negatives. We argue that this problem can be overcome by substituting the cognitive component of CAPTCHA with a different property that programs cannot mimic: the physical nature. In past work we have introduced the Completely Automated Public Physical test to tell Computer and Humans Apart (CAPPCHA) as a way to enhance the PIN authentication method for mobile devices and we have provided a proof of concept implementation. Similarly to CAPTCHA, this mechanism can also be used to prevent automated programs from abusing online services. However, to evaluate the real efficacy of the proposed scheme, an extended empirical assessment of CAPPCHA is required as well as a comparison of CAPPCHA performance with the existing state of the art. To this aim, in this paper we carry out an extensive experimental study on both the performance and the usability of CAPPCHA involving a high number of physical users, and we provide comparisons of CAPPCHA with existing flavors of CAPTCHA

The Rise of Mobile and the Diffusion of Technology-Facilitated Trafficking

In this report, researchers at the USC Annenberg Center on Communication Leadership & Policy (CCLP) reveal how those involved in human trafficking have been quick to adapt to the 21st-century global landscape. While the rapid diffusion of digital technologies such as mobile phones, social networking sites, and the Internet has provided significant benefits to society, new channels and opportunities for exploitation have also emerged. Increasingly, the business of human trafficking is taking place online and over mobile phones. But the same technologies that are being used for trafficking can become a powerful tool to combat trafficking. The precise role that digital technologies play in human trafficking still remains unclear, however, and a closer examination of the phenomenon is vital to identify and respond to new threats and opportunities.This investigation indicates that mobile devices and networks have risen in prominence and are now of central importance to the sex trafficking of minors in the United States. While online platforms such as online classifieds and social networking sites remain a potential venue for exploitation, this research suggests that technology facilitated trafficking is more diffuse and adaptive than initially thought. This report presents a review of current literature, trends, and policies; primary research based on mobile phone data collected from online classified sites; a series of firsthand interviews with law enforcement; and key recommendations to policymakers and stakeholders moving forward

The Internet of Things Connectivity Binge: What are the Implications?

Despite wide concern about cyberattacks, outages and privacy violations, most experts believe the Internet of Things will continue to expand successfully the next few years, tying machines to machines and linking people to valuable resources, services and opportunities