A Security Sensitive Function Mining Approach Based on Precondition Pattern Analysis

Security-sensitive functions are the basis for building a taint-style vulnerability model.Current approaches for extracting security-sensitive functions either don’t analyze data flow accurately,or not conducting pattern analyzing of conditions,resulting in higher false positive rate or false negative rate,which increased manual confirmation workload.In this paper,we propose a security sensitive function mining approach based on preconditon pattern analyzing.Firstly,we propose an enhanced system dependency graph analysis algorithm for precisely extracting the conditional statements which check the function parameters and conducting statistical analysis of the conditional statements for selecting candidate security sensitive functions of the target program.Then we adopt a precondition pattern mining method based on conditional statements nomalizing and clustering.Functions with fixed precondition patterns are regarded as security-sensitive functions.The experimental results on four popular open source codebases of different scales show that the approach proposed is effective in reducing the false positive rate and false negative rate for detecting security sensitive functions.

An Emergency Shelter Location Model Based on the Sense of Security and the Reliability Level

Based on the value function of the prospect theory,this paper constructs a security function,which is used to describe the victims’feelings about the distance in emergency evacuation.Since different paths between the demand points and the emergency shelters are generally of different importance degrees,they are divided into main paths and auxiliary paths.The security function values and the reliability levels of main paths and auxiliary paths are given different weights.The weighted sum of the security function values and the weighted sum of the reliability level function values of all demand points are maximized to determine the location and the number of the emergency shelters,the transfer paths,the reinforced edges and the incremental reliability level of the selected edge.In order to solve the model,a two-stage simulated annealing-particle swarm optimization algorithm is proposed.In this algorithm,the particle swarm optimization(PSO)algorithm is embedded into the simulated annealing(SA)algorithm.The cumulative probability operator and the cost probability operator are formed to determine the evolution of the particles.Considering the budget constraint,the algorithm eliminates the shelter combinations that do not meet the constraint,which greatly saves the calculation time and improves the efficiency.The proposed algorithm is applied to a case,which verifies its feasibility and stability.The model and the algorithm of this paper provide a basis for emergency management departments to make the earthquake emergency planning.

Research on a provable security RFID authentication protocol based on Hash function

Research on existing radio frequency identification（RFID） authentication protocols security risks, poor performance and other problems, a RFID security authentication protocol based on dynamic identification（ID） and Key value renewal is proposed. Meanwhile, the security problems based on Hash function RFID security authentication protocol in recent years have been also sorted and analyzed. Then a security model to design and analyze RFID protocols is built. By using the computational complexity, its correctness and security have been proved. Compared with the safety performance, storage overhead, computational overhead and other aspects of other protocols, the protocol for RFID has more efficient performance and ability to withstand various attacks. And the C# programming language is used to simulate the authentication process on the visual studio platform, which verifies the feasibility of the protocol.

Secure communication based on spatiotemporal chaos

In this paper, we propose a novel approach to secure communication based on spatiotemporal chaos. At the transmitter end, the state variables of the coupled map lattice system are divided into two groups: one is used as the key to encrypt the plaintext in the N-shift encryption function, and the other is used to mix with the output of the N-shift function to further confuse the information to transmit. At the receiver end, the receiver lattices are driven by the received signal to synchronize with the transmitter lattices and an inverse procedure of the encoding is conducted to decode the information.Numerical simulation and experiment based on the TI TMS320C6713 Digital Signal Processor(DSP) show the feasibility and the validity of the proposed scheme.

从完美保密到完美安全:基于密码学的内生安全分析

In this paper,we propose a conjecture that endogenous security without any prior knowledge is similar to perfect secrecy without any prior knowledge.To prove the conjecture,we first establish a cryptography model of instinct function security to transform the security problem in the network domain into an encryption problem in the cryptographic domain.Then,we inherit and apply the established ideas and means of Perfect Secrecy,and propose the concept,definition and corollaries of the perfect instinct function security(PIFS)corresponding to Perfect Secrecy.Furthermore,we take the DHR system as a concrete implementation of PIFS and propose the DHR Perfect Security Theorem corresponding to Shannon’s Perfect Secrecy Theorem.Finally,we prove that the DHR satisfying the“OneTime Reconstruction”constraint is the sufficient and necessary condition to achieve perfect security.This means that the existence of PIFS is also proven.The analysis shows that any reconfigurable system can be encrypted by its construct and that the PIFS converts the oneway transparent superiority of the attacker into a double-blind problem for both the attacker and the defender,which leads to that the attacker is impossible to obtain useful construction information from the attacks and unable to find a better way than blind trial-and-error or brute-force attacks.Since the attackers are required to have the new powerful ability to crack the structure cryptogram,the threshold of cyber security is raised to at least the same level as cryptogram deciphering,thereafter the ubiquitous cyber threats are destined to be significantly reduced.

A verifiable privacy-preserving data collection scheme supporting multi-party computation in fog-based smart grid

Incorporation of fog computing with low latency,preprocession(e.g.,data aggregation)and location awareness,can facilitate fine-grained collection of smart metering data in smart grid and promotes the sustainability and efficiency of the grid.Recently,much attention has been paid to the research on smart grid,especially in protecting privacy and data aggregation.However,most previous works do not focus on privacy-preserving data aggregation and function computation query on enormous data simultaneously in smart grid based on fog computation.In this paper,we construct a novel verifiable privacy-preserving data collection scheme supporting multi-party computation(MPC),named VPDC-MPC,to achieve both functions simultaneously in smart grid based on fog computing.VPDC-MPC realizes verifiable secret sharing of users’data and data aggregation without revealing individual reports via practical cryptosystem and verifiable secret sharing scheme.Besides,we propose an efficient algorithm for batch verification of share consistency and detection of error reports if the external adversaries modify the SMs’report.Furthermore,VPDC-MPC allows both the control center and users with limited resources to obtain arbitrary arithmetic analysis(not only data aggregation)via secure multi-party computation between cloud servers in smart grid.Besides,VPDC-MPC tolerates fault of cloud servers and resists collusion.We also present security analysis and performance evaluation of our scheme,which indicates that even with tradeoff on computation and communication overhead,VPDC-MPC is practical with above features.

AMCheX: Accurate Analysis of Missing-Check Bugs for Linux Kernel

The Linux kernel adopts a large number of security checks to prevent security-sensitive operations from being executed under unsafe conditions.If a security-sensitive operation is unchecked,a missing-check issue arises.Missing check is a class of severe bugs in software programs especially in operating system kernels,which may cause a variety of security issues,such as out-of-bound accesses,permission bypasses,and privilege escalations.Due to the lack of security specifications,how to automatically identify security-sensitive operations and their required security checks in the Linux kernel becomes a challenge for missing-check analysis.In this paper,we present an accurate missing-check analysis method for Linux kernel,which can automatically infer possible security-sensitive operations.Particularly,we first automatically identify all possible security check functions of Linux.Then according to their callsites,a two-direction analysis method is leveraged to identify possible security-sensitive operations.A missing-check bug is reported when the security-sensitive operation is not protected by its corresponding security check.We have implemented our method as a tool,named AMCheX,on top of the LLVM(Low Level Virtual Machine)framework and evaluated it on the Linux kernel.AMCheX reported 12 new missing-check bugs which can cause security issues.Five of them have been confirmed by Linux maintainers.