Behavior based adaptive call predictor

Predicting future calls can be the next advanced feature of the next-generation telecommunication networks as the service providers are looking to offer new services to their customers. Call prediction can be useful to many applications such as planning daily schedules, avoiding unwanted communications (e.g. voice spam), and resource planning in call centers. Predicting calls is a very challenging task. We believe that this is an emerging area of research in ambient intelligence where the electronic devices are sensitive and responsive to people’s needs and behavior. In particular, we believe that the results of this research will lead to higher productivity and quality of life. In this article, we present a Call Predictor (CP) that offers two new advanced features for the next-generation phones namely “Incoming Call Forecast” and “Intelligent Address Book.” For the Incoming Call Forecast, the CP makes the next-24-hour incoming call prediction based on recent caller’s behavior and reciprocity. For the Intelligent Address Book, the CP generates a list of most likely contacts/numbers to be dialed at any given time based on the user’s behavior and reciprocity. The CP consists of two major components: Probability Estimator (PE) and Trend Detector (TD). The PE computes the probability of receiving/initiating a call based on the caller/user’s calling behavior and reciprocity. We show that the recent trend of the caller/user’s calling pattern has higher correlation to the future pattern than the pattern derived from the entire historical data. The TD detects the recent trend of the caller/user’s calling pattern and computes the adequacy of historical data in terms of reversed time (time that runs towards the past) based on a trace distance. The recent behavior detection mechanism allows CP to adapt its computation in response to the new calling behaviors. Therefore, CP is adaptive to the recent behavior. For our analysis, we use the real-life call logs of 94 mobile phone users over nine months, which were collected by the Reality Mining Project group at MIT. The performance of the CP is validated for two months based on seven months of training data. The experimental results show that the CP performs reasonably well as an incoming call predictor (Incoming Call Forecast) with false positive rate of 8%, false negative rate of 1%, and error rate of 9%, and as an outgoing call predictor (Intelligent Address Book) with the accuracy of 70% when the list has five entries. The functionality of the CP can be useful in assisting its user in carrying out everyday life activities such as scheduling daily plans by using the Incoming Call Forecast, and saving time from searching for the phone number in a typically lengthy contact book by using the Intelligent Address Book. Furthermore, we describe other useful applications of CP besides its own aforementioned features including Call Firewall and Call Reminder

Social Bots: Human-Like by Means of Human Control?

Social bots are currently regarded an influential but also somewhat mysterious factor in public discourse and opinion making. They are considered to be capable of massively distributing propaganda in social and online media and their application is even suspected to be partly responsible for recent election results. Astonishingly, the term `Social Bot' is not well defined and different scientific disciplines use divergent definitions. This work starts with a balanced definition attempt, before providing an overview of how social bots actually work (taking the example of Twitter) and what their current technical limitations are. Despite recent research progress in Deep Learning and Big Data, there are many activities bots cannot handle well. We then discuss how bot capabilities can be extended and controlled by integrating humans into the process and reason that this is currently the most promising way to go in order to realize effective interactions with other humans.Comment: 36 pages, 13 figure

A Comprehensive Survey of Voice over IP Security Research

We present a comprehensive survey of Voice over IP security academic research, using a set of 245 publications forming a closed cross-citation set. We classify these papers according to an extended version of the VoIP Security Alliance (VoIPSA) Threat Taxonomy. Our goal is to provide a roadmap for researchers seeking to understand existing capabilities and to identify gaps in addressing the numerous threats and vulnerabilities present in VoIP systems. We discuss the implications of our findings with respect to vulnerabilities reported in a variety of VoIP products. We identify two specific problem areas (denial of service, and service abuse) as requiring significant more attention from the research community. We also find that the overwhelming majority of the surveyed work takes a black box view of VoIP systems that avoids examining their internal structure and implementation. Such an approach may miss the mark in terms of addressing the main sources of vulnerabilities, i.e., implementation bugs and misconfigurations. Finally, we argue for further work on understanding cross-protocol and cross-mechanism vulnerabilities (emergent properties), which are the byproduct of a highly complex system-of-systems and an indication of the issues in future large-scale systems

Artificial intelligence in the cyber domain: Offense and defense

Artificial intelligence techniques have grown rapidly in recent years, and their applications in practice can be seen in many fields, ranging from facial recognition to image analysis. In the cybersecurity domain, AI-based techniques can provide better cyber defense tools and help adversaries improve methods of attack. However, malicious actors are aware of the new prospects too and will probably attempt to use them for nefarious purposes. This survey paper aims at providing an overview of how artificial intelligence can be used in the context of cybersecurity in both offense and defense.Web of Science123art. no. 41

From Understanding Telephone Scams to Implementing Authenticated Caller ID Transmission

abstract: The telephone network is used by almost every person in the modern world. With the rise of Internet access to the PSTN, the telephone network today is rife with telephone spam and scams. Spam calls are significant annoyances for telephone users, unlike email spam, spam calls demand immediate attention. They are not only significant annoyances but also result in significant financial losses in the economy. According to complaint data from the FTC, complaints on illegal calls have made record numbers in recent years. Americans lose billions to fraud due to malicious telephone communication, despite various efforts to subdue telephone spam, scam, and robocalls. In this dissertation, a study of what causes the users to fall victim to telephone scams is presented, and it demonstrates that impersonation is at the heart of the problem. Most solutions today primarily rely on gathering offending caller IDs, however, they do not work effectively when the caller ID has been spoofed. Due to a lack of authentication in the PSTN caller ID transmission scheme, fraudsters can manipulate the caller ID to impersonate a trusted entity and further a variety of scams. To provide a solution to this fundamental problem, a novel architecture and method to authenticate the transmission of the caller ID is proposed. The solution enables the possibility of a security indicator which can provide an early warning to help users stay vigilant against telephone impersonation scams, as well as provide a foundation for existing and future defenses to stop unwanted telephone communication based on the caller ID information.Dissertation/ThesisDoctoral Dissertation Computer Science 201

Local Broadband Access: Primum Non Nocere or Primum Processi - A Property Rights Approach

High-speed or "broadband" Internet access currently is provided, at the local level, chiefly by cable television and telephone companies, often in competition with each other. Wireless and satellite providers have a small but growing share of this business. An influential coalition of economic interests and academics have proposed that local broadband Internet access providers be prohibited from restricting access to their systems by upstream suppliers of Internet services. A recent term for this proposal is "net neutrality." We examine the potential costs and benefits of such a policy from an economic welfare perspective. Using a property rights approach, we ask whether transactions costs in the market for access rights are likely to be significant, and if so, whether owners of physical local broadband platforms are likely to be more or less efficient holders of access rights than Internet content providers. We conclude that transactions costs are likely to be lower if access rights are assigned initially to platform owners rather than content providers. In addition, platform hardware owners are likely to be more efficient holders of these rights because they can internalize demand-side interactions among content products. Further, failure to permit platform owners to control access threatens to result in inadequate incentives to invest in, to maintain, and to upgrade local broadband platforms. Inefficiently denying platform owners the ability to own access rights implies a need for price regulation; otherwise, there will be incentives to use pricing to circumvent the constraint on rights ownership. Price regulation is itself known to induce welfare losses through adaptive behavior of the constrained firm. The impact on welfare might produce a worse result than the initial problem, assuming one existed. Much of the academic interest in net neutrality arises from the belief that the open architecture of the Internet under current standards has been responsible for its remarkable success, and a wish to preserve this openness. We point out that the openness of the Internet was an unintended consequence of its military origins, and that other, less open, architectures might have been even more successful. A policy of denying platform owners the ability to own access rights could freeze the architecture of the Internet, preventing it from adapting to future technological and economic developments. Finally, we examine the net neutrality issue from the perspective of the "essential facility doctrine," a tool of the common law of antitrust. The doctrine establishes conditions under which federal courts will mandate access by competitors to the monopoly platform of a vertically-integrated firm. Because local broadband Internet access is not today a bottleneck monopoly (there are several competitors and the market is at an early stage of development), the essential facilities doctrine would not permit reassignment of access rights from platform owners to competitors. We conclude that "net neutrality" is a welfare-reducing policy proposal.Technology and Industry, Regulatory Reform

Evidence-informed regulatory practice: an adaptive response, 2005‑15

Overview: In this occasional paper, the ACMA reflects on its regulatory practice over the past 10 years; specifically, the role of research in evidence-informed decision-making and regulation. It looks at how the ACMA has used research in an environment of ongoing change to document and build evidence, inform public debate about regulation, and build capability among our stakeholders to make communications and media work in Australia’s national interest

Report on the Information Retrieval Festival (IRFest2017)

The Information Retrieval Festival took place in April 2017 in Glasgow. The focus of the workshop was to bring together IR researchers from the various Scottish universities and beyond in order to facilitate more awareness, increased interaction and reflection on the status of the field and its future. The program included an industry session, research talks, demos and posters as well as two keynotes. The first keynote was delivered by Prof. Jaana Kekalenien, who provided a historical, critical reflection of realism in Interactive Information Retrieval Experimentation, while the second keynote was delivered by Prof. Maarten de Rijke, who argued for more Artificial Intelligence usage in IR solutions and deployments. The workshop was followed by a "Tour de Scotland" where delegates were taken from Glasgow to Aberdeen for the European Conference in Information Retrieval (ECIR 2017