Autonomic communications seek to improve the ability of network and services to cope with unpredicted change, including changes in topology, load, task, the physical and logical characteristics of the networks that can be accessed, and so forth. Broad-ranging autonomic solutions require designers to account for a range of end-to-end issues affecting programming models, network and contextual modeling and reasoning, decentralised algorithms, trust acquisition and maintenance---issues whose solutions may draw on approaches and results from a surprisingly broad range of disciplines. We survey the current state of autonomic communications research and identify significant emerging trends and techniques.

(U.S.) Rule-based policies for mitigating software risk suggest using the CVSS score to measure the risk of an individual vulnerability and act accordingly. A key issue is whether the ‘danger’ score does actually match the risk of exploitation in the wild, and if and how such a score could be improved. To address this question, we propose using a case-control study methodology similar to the procedure used to link lung cancer and smoking in the 1950s. A case-control study allows the researcher to draw conclusions on the relation between some risk factor (e.g., smoking) and an effect (e.g., cancer) by looking backward at the cases (e.g., patients) and comparing them with controls (e.g., randomly selected patients with similar characteristics). The methodology allows us to quantify the risk reduction achievable by acting on the risk factor. We illustrate the methodology by using publicly available data on vulnerabilities, exploits, and exploits in the wild to (1) evaluate the performances of the current risk factor in the industry, the CVSS base score; (2) determine whether it can be improved by considering additional factors such the existence of a proof-of-concept exploit, or of an exploit in the black markets. Our analysis reveals that (a) fixing a vulnerability just because it was assigned a high CVSS score is equivalent to randomly picking vulnerabilities to fix; (b) the existence of proof-of-concept exploits is a significantly better risk factor; (c) fixing in response to exploit presence in black markets yields the largest risk reduction.

Security requirements engineering is emerging as a branch of software engineering, spurred by the realization that security must be dealt with early on during the requirements phase. Methodologies in this field are challenging, as they must take into account subtle notions such as trust (or lack thereof), delegation, and permission; they must also model entire organizations and not only systems-to-be. In our previous work we introduced Secure Tropos, a formal framework for modeling and analyzing security requirements. Secure Tropos is founded on three main notions: ownership, trust, and delegation. In this paper, we refine Secure Tropos introducing the notions of at-least delegation and trust of execution; also, at-most delegation and trust of permission. We also propose monitoring as a security design pattern intended to overcome the problem of lack of trust between actors. The paper presents a semantic for these notions, and describes an implemented formal reasoning tool based on Datalog.