Program Analysis of Commodity IoT Applications for Security and Privacy: Challenges and Opportunities

Recent advances in Internet of Things (IoT) have enabled myriad domains such as smart homes, personal monitoring devices, and enhanced manufacturing. IoT is now pervasive---new applications are being used in nearly every conceivable environment, which leads to the adoption of device-based interaction and automation. However, IoT has also raised issues about the security and privacy of these digitally augmented spaces. Program analysis is crucial in identifying those issues, yet the application and scope of program analysis in IoT remains largely unexplored by the technical community. In this paper, we study privacy and security issues in IoT that require program-analysis techniques with an emphasis on identified attacks against these systems and defenses implemented so far. Based on a study of five IoT programming platforms, we identify the key insights that result from research efforts in both the program analysis and security communities and relate the efficacy of program-analysis techniques to security and privacy issues. We conclude by studying recent IoT analysis systems and exploring their implementations. Through these explorations, we highlight key challenges and opportunities in calibrating for the environments in which IoT systems will be used.Comment: syntax and grammar error are fixed, and IoT platforms are updated to match with the submissio

Build It, Break It, Fix It: Contesting Secure Development

Typical security contests focus on breaking or mitigating the impact of buggy systems. We present the Build-it Break-it Fix-it BIBIFI contest which aims to assess the ability to securely build software not just break it. In BIBIFI teams build specified software with the goal of maximizing correctness performance and security. The latter is tested when teams attempt to break other teams submissions. Winners are chosen from among the best builders and the best breakers. BIBIFI was designed to be open-ended - teams can use any language tool process etc. that they like. As such contest outcomes shed light on factors that correlate with successfully building secure software and breaking insecure software. During we ran three contests involving a total of teams and two different programming problems. Quantitative analysis from these contests found that the most efficient build-it submissions used CC but submissions coded in a statically-typed language were less likely to have a security flaw build-it teams with diverse programming-language knowledge also produced more secure code. Shorter programs correlated with better scores. Break-it teams that were also build-it teams were significantly better at finding security bugs

Building and Maintaining a Third-Party Library Supply Chain for Productive and Secure SGX Enclave Development

The big data industry is facing new challenges as concerns about privacy leakage soar. One of the remedies to privacy breach incidents is to encapsulate computations over sensitive data within hardware-assisted Trusted Execution Environments (TEE). Such TEE-powered software is called secure enclaves. Secure enclaves hold various advantages against competing for privacy-preserving computation solutions. However, enclaves are much more challenging to build compared with ordinary software. The reason is that the development of TEE software must follow a restrictive programming model to make effective use of strong memory encryption and segregation enforced by hardware. These constraints transitively apply to all third-party dependencies of the software. If these dependencies do not officially support TEE hardware, TEE developers have to spend additional engineering effort in porting them. High development and maintenance cost is one of the major obstacles against adopting TEE-based privacy protection solutions in production. In this paper, we present our experience and achievements with regard to constructing and continuously maintaining a third-party library supply chain for TEE developers. In particular, we port a large collection of Rust third-party libraries into Intel SGX, one of the most mature trusted computing platforms. Our supply chain accepts upstream patches in a timely manner with SGX-specific security auditing. We have been able to maintain the SGX ports of 159 open-source Rust libraries with reasonable operational costs. Our work can effectively reduce the engineering cost of developing SGX enclaves for privacy-preserving data processing and exchange

Abstractions for AI-Based User Interfaces and Systems

Novel user interfaces based on artificial intelligence, such as natural-language agents, present new categories of engineering challenges. These systems need to cope with uncertainty and ambiguity, interface with machine learning algorithms, and compose information from multiple users to make decisions. We propose to treat these challenges as language-design problems. We describe three programming language abstractions for three core problems in intelligent system design. First, hypothetical worlds support nondeterministic search over spaces of alternative actions. Second, a feature type system abstracts the interaction between applications and learning algorithms. Finally, constructs for collaborative execution extend hypothetical worlds across multiple machines while controlling access to private data. We envision these features as first steps toward a complete language for implementing AI-based interfaces and applications

State of the Software Development Life-Cycle for the Internet-of-Things

Software has a longstanding association with a state of crisis considering its success rate. The explosion of Internet-connected devices, Internet-of-Things, adds to the complexity of software systems. The particular characteristics of these systems, such as being large-scale and its heterogeneity, pose increasingly new challenges. In this paper, we first briefly introduce the IoT paradigm and the current state of art of software development. Then, we delve into the particularities of developing software for IoT systems and systems of systems, given an overview of what are the current methodologies and tools for design, develop and test such systems. The findings are discussed, revealing open issues and research directions, and reveal that the nowadays IoT software development practices are still lagging behind of what are the current best practices.Comment: 38 page

Secondary use of data in EHR systems

We show how to use aspect-oriented programming to separate security and trust issues from the logical design of mobile, distributed systems. The main challenge is how to enforce various types of security policies, in particular predictive access control policies - policies based on the future behavior of a program. A novel feature of our approach is that advice is able to analyze the future use of data. We consider a number of different security policies, concerning both primary and secondary use of data, some of which can only be enforced by analysis of process continuations.Comment: 40 page

A Logic Programming Approach for Formal Verification of NetBill Security and Transactions Protocol

Use of formal techniques for verifying the security features of electronic commerce protocols would facilitate, the enhancement of reliability of such protocols, thereby increasing their usability. This paper projects the application of logic programming techniques for formal verification of a well referred security and transactions protocol, the NetBill. The paper uses ALSP (Action Language for Security Protocols) as an efficient formal specification language and SMODELS a model generator to formally analyze and plan attacks on the protocol.Comment: ICSCI-09, Hyderabad. Indi

Java Card: an analysis of the most successful smart card operating system to date

To explain why the Java Card operating system has become the most successful smart card operating system to date, we analyze the realized features of the current Java Card version, we argue it could be enhanced by adding a number of intended features and we discuss a set of complementary features that have been suggested. No technology can be successful without the right people and the right circumstances, so we provide some insights in the personal and historical historic aspects of the success of Java Car

Finding Tizen security bugs through whole-system static analysis

Tizen is a new Linux-based open source platform for consumer devices including smartphones, televisions, vehicles, and wearables. While Tizen provides kernel-level mandatory policy enforcement, it has a large collection of libraries, implemented in a mix of C and C++, which make their own security checks. In this research, we describe the design and engineering of a static analysis engine which drives a full information flow analysis for apps and a control flow analysis for the full library stack. We implemented these static analyses as extensions to LLVM, requiring us to improve LLVM's native analysis features to get greater precision and scalability, including knotty issues like the coexistence of C++ inheritance with C function pointer use. With our tools, we found several unexpected behaviors in the Tizen system, including paths through the system libraries that did not have inline security checks. We show how our tools can help the Tizen app store to verify important app properties as well as helping the Tizen development process avoid the accidental introduction of subtle vulnerabilities

When Coding Style Survives Compilation: De-anonymizing Programmers from Executable Binaries

The ability to identify authors of computer programs based on their coding style is a direct threat to the privacy and anonymity of programmers. While recent work found that source code can be attributed to authors with high accuracy, attribution of executable binaries appears to be much more difficult. Many distinguishing features present in source code, e.g. variable names, are removed in the compilation process, and compiler optimization may alter the structure of a program, further obscuring features that are known to be useful in determining authorship. We examine programmer de-anonymization from the standpoint of machine learning, using a novel set of features that include ones obtained by decompiling the executable binary to source code. We adapt a powerful set of techniques from the domain of source code authorship attribution along with stylistic representations embedded in assembly, resulting in successful de-anonymization of a large set of programmers. We evaluate our approach on data from the Google Code Jam, obtaining attribution accuracy of up to 96% with 100 and 83% with 600 candidate programmers. We present an executable binary authorship attribution approach, for the first time, that is robust to basic obfuscations, a range of compiler optimization settings, and binaries that have been stripped of their symbol tables. We perform programmer de-anonymization using both obfuscated binaries, and real-world code found "in the wild" in single-author GitHub repositories and the recently leaked Nulled.IO hacker forum. We show that programmers who would like to remain anonymous need to take extreme countermeasures to protect their privacy.Comment: 15 page